diff --git a/eftnas-s1-bert-base-cola/EFTNAS_S1_subnet.pth b/eftnas-s1-bert-base-cola/EFTNAS_S1_subnet.pth new file mode 100644 index 0000000000000000000000000000000000000000..3e8db174fb05cbacd47ef6c9fcce0d84b5e17517 --- /dev/null +++ b/eftnas-s1-bert-base-cola/EFTNAS_S1_subnet.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2910e999a73c61cd32fa5380b0bb3293b0766659d053377f14193de8197b19c8 +size 961 diff --git a/eftnas-s1-bert-base-cola/README.md b/eftnas-s1-bert-base-cola/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e06294f7416b7d70af23f94cd0cc2a63a4e725f8 --- /dev/null +++ b/eftnas-s1-bert-base-cola/README.md @@ -0,0 +1,100 @@ +--- +language: +- en +license: apache-2.0 +tags: +- generated_from_trainer +datasets: +- glue +metrics: +- matthews_correlation +model-index: +- name: first_try + results: + - task: + name: Text Classification + type: text-classification + dataset: + name: GLUE COLA + type: glue + config: cola + split: validation + args: cola + metrics: + - name: Matthews Correlation + type: matthews_correlation + value: 0.554912808282685 +--- + + + +# first_try + +This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE COLA dataset. +It achieves the following results on the evaluation set: +- Loss: 0.8516 +- Matthews Correlation: 0.5549 + +## Model description + +More information needed + +## Intended uses & limitations + +More information needed + +## Training and evaluation data + +More information needed + +## Training procedure + +### Training hyperparameters + +The following hyperparameters were used during training: +- learning_rate: 2e-05 +- train_batch_size: 32 +- eval_batch_size: 128 +- seed: 42 +- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 +- lr_scheduler_type: linear +- num_epochs: 30 +- mixed_precision_training: Native AMP + +### Training results + +| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | | +|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| +| No log | 1.0 | 268 | 0.7150 | 0.3947 | OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})]) | +| No log | 1.0 | 268 | 0.6399 | 0.5222 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.8522 | 2.0 | 536 | 0.7287 | 0.4630 | OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})]) | +| 0.8522 | 2.0 | 536 | 0.6622 | 0.5624 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.8522 | 3.0 | 804 | 0.7320 | 0.4775 | OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})]) | +| 0.8522 | 3.0 | 804 | 0.6782 | 0.5573 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.3135 | 4.0 | 1072 | 0.8995 | 0.4830 | OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})]) | +| 0.3135 | 4.0 | 1072 | 0.7692 | 0.5549 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.3135 | 5.0 | 1340 | 0.8262 | 0.5107 | OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})]) | +| 0.3135 | 5.0 | 1340 | 0.6901 | 0.5834 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.155 | 6.0 | 1608 | 0.8722 | 0.5076 | OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})]) | +| 0.155 | 6.0 | 1608 | 0.7215 | 0.5925 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.155 | 7.0 | 1876 | 0.9456 | 0.5054 | OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})]) | +| 0.155 | 7.0 | 1876 | 0.8113 | 0.5765 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0957 | 8.0 | 2144 | 0.9191 | 0.5049 | OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})]) | +| 0.0957 | 8.0 | 2144 | 0.7811 | 0.5885 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0957 | 9.0 | 2412 | 0.9647 | 0.4994 | OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})]) | +| 0.0957 | 9.0 | 2412 | 0.8087 | 0.5598 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0729 | 10.0 | 2680 | 0.9290 | 0.4990 | OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})]) | +| 0.0729 | 10.0 | 2680 | 0.8079 | 0.5754 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0729 | 11.0 | 2948 | 0.9496 | 0.4982 | OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})]) | +| 0.0729 | 11.0 | 2948 | 0.8124 | 0.5728 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0626 | 12.0 | 3216 | 0.9496 | 0.4982 | OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})]) | +| 0.0626 | 12.0 | 3216 | 0.8131 | 0.5728 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | + + +### Framework versions + +- Transformers 4.29.1 +- Pytorch 1.12.1 +- Datasets 2.13.1 +- Tokenizers 0.13.3 diff --git a/eftnas-s1-bert-base-cola/all_results.json b/eftnas-s1-bert-base-cola/all_results.json new file mode 100644 index 0000000000000000000000000000000000000000..5fa1ac3f4b86274e0fb01a37343f73e0b2ff6ae0 --- /dev/null +++ b/eftnas-s1-bert-base-cola/all_results.json @@ -0,0 +1,14 @@ +{ + "epoch": 12.0, + "eval_loss": 0.8515769839286804, + "eval_matthews_correlation": 0.554912808282685, + "eval_runtime": 0.8897, + "eval_samples": 1043, + "eval_samples_per_second": 1172.255, + "eval_steps_per_second": 10.115, + "train_loss": 0.244898120265695, + "train_runtime": 5953.5704, + "train_samples": 8551, + "train_samples_per_second": 17.235, + "train_steps_per_second": 0.54 +} \ No newline at end of file diff --git a/eftnas-s1-bert-base-cola/cache_MACs.csv 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4)",7741.507072 +"(2, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 4, 1, 0, 0, 1, 0, 1, 1, 2, 1, 3)",9067.431424 +"(3, 0, 0, 3, 0, 1, 0, 2, 1, 2, 1, 2, 1, 4, 2, 3, 2, 2, 0, 4, 3, 4, 3, 4)",6677.136896 +"(3, 2, 0, 3, 0, 1, 0, 2, 1, 2, 1, 2, 1, 4, 2, 4, 0, 2, 2, 2, 3, 4, 3, 4)",6652.691968 +"(3, 3, 3, 3, 2, 1, 0, 2, 1, 1, 1, 2, 3, 1, 1, 2, 3, 2, 2, 2, 3, 4, 1, 3)",6903.82592 +"(3, 2, 3, 2, 0, 1, 0, 0, 0, 1, 1, 2, 1, 4, 4, 1, 2, 3, 0, 2, 1, 4, 1, 3)",7247.365632 +"(3, 0, 3, 3, 0, 1, 0, 0, 1, 2, 1, 2, 1, 4, 4, 3, 2, 2, 3, 4, 4, 4, 4, 4)",5865.211392 +"(2, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 4, 1, 0, 0, 1, 0, 1, 1, 4, 1, 3)",8755.283456 +"(3, 4, 0, 3, 0, 1, 0, 2, 1, 2, 1, 1, 1, 4, 1, 4, 2, 1, 0, 4, 3, 1, 1, 4)",7129.990656 +"(3, 0, 3, 3, 0, 1, 0, 1, 0, 2, 1, 2, 2, 4, 3, 4, 4, 3, 4, 4, 4, 4, 4, 4)",5315.23328 +"(3, 0, 0, 2, 0, 1, 0, 2, 1, 2, 1, 2, 1, 4, 1, 4, 2, 1, 0, 4, 3, 4, 3, 4)",6763.382272 +"(2, 2, 3, 1, 0, 1, 0, 1, 1, 2, 1, 2, 2, 4, 1, 0, 0, 4, 2, 2, 4, 2, 3, 4)",6808.14336 +"(2, 0, 1, 1, 0, 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "32 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"32 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "33 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"33 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "34 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"34 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "35 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"35 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "38 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"36 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "38 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"37 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "38 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"38 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "39 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"39 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "40 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"40 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "41 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"41 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "44 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"41 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"42 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "44 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"43 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "44 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"44 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"46 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"47 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" -> "51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"52 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"53 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"56 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"324 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"330 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"333 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"334 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"339 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"340 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"342 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"343 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"347 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"348 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "359 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"359 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "361 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"361 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "362 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"362 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "363 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"363 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"364 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"365 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "367 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"367 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"370 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"371 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "373 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"373 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"374 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"375 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "377 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"377 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"380 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"381 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "393 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"383 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"384 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "386 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"386 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "387 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"387 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "395 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"388 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"389 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "391 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"391 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "392 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"392 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"393 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "394 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"394 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"395 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "397 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"397 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "398 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"398 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "399 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"399 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "400 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"400 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "402 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"402 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "403 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"403 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "404 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"404 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"405 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"406 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "408 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"408 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"411 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"412 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "414 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"414 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"415 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"416 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "418 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"418 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"421 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"422 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "434 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"424 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"425 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "427 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"427 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "428 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"428 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "436 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"429 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"430 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "432 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"432 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "433 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"433 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"434 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "435 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"435 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"436 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "438 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"438 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "439 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"439 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "440 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"440 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "441 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"441 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "443 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"443 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "444 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"444 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "445 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"445 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"446 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"447 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "449 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"449 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"452 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"453 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "455 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"455 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"456 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"457 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "459 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"459 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" -> "461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "491 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"462 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"463 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"42 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "43 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"43 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"44 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "46 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"46 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"47 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "52 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"52 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "53 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"53 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "56 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"56 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "311 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0000000000000000000000000000000000000000..f2ee63a0ce224160067a911d12caf45c34d8b514 --- /dev/null +++ b/eftnas-s1-bert-base-cola/search_progression.csv @@ -0,0 +1,1000 @@ +"OrderedDict([(, {0: 768, 1: 448, 2: 640, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 768, 10: 768, 11: 768, 12: 1588, 13: 1609, 14: 1110, 15: 3072, 16: 2771, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 928, 22: 814, 23: 3072})])",MACs,7774.537216,top1_acc,-55.54433905906734 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 768, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2134, 13: 3072, 14: 1762, 15: 1739, 16: 1788, 17: 1062, 18: 2797, 19: 3072, 20: 670, 21: 2187, 22: 814, 23: 3072})])",MACs,7724.074496,top1_acc,-55.982394228103175 +"OrderedDict([(, {0: 704, 1: 768, 2: 640, 3: 640, 4: 768, 5: 768, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 768, 12: 2692, 13: 959, 14: 1762, 15: 2312, 16: 2316, 17: 1062, 18: 2297, 19: 2245, 20: 3072, 21: 928, 22: 3072, 23: 799})])",MACs,7813.79328,top1_acc,-53.64243566130295 +"OrderedDict([(, {0: 768, 1: 704, 2: 448, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 448, 9: 320, 10: 768, 11: 320, 12: 2134, 13: 2685, 14: 2275, 15: 3072, 16: 1158, 17: 1774, 18: 2797, 19: 2245, 20: 1863, 21: 436, 22: 3072, 23: 370})])",MACs,7749.24032,top1_acc,-56.267276480756976 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2771, 17: 2797, 18: 2797, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7301.95712,top1_acc,-59.56649094312695 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 320, 10: 768, 11: 768, 12: 949, 13: 3072, 14: 3072, 15: 2788, 16: 2771, 17: 1062, 18: 1719, 19: 2245, 20: 670, 21: 3072, 22: 348, 23: 1322})])",MACs,7484.671488,top1_acc,-56.01977832642419 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 640, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 768, 11: 384, 12: 2692, 13: 1609, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 1469, 22: 348, 23: 1322})])",MACs,6751.389184,top1_acc,-53.41430411919947 +"OrderedDict([(, {0: 512, 1: 768, 2: 448, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 2171, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 1028, 19: 3072, 20: 3072, 21: 2187, 22: 3072, 23: 799})])",MACs,8761.312768,top1_acc,-55.73810919249996 +"OrderedDict([(, {0: 704, 1: 704, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 512, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 2685, 14: 1110, 15: 2788, 16: 1158, 17: 1774, 18: 2797, 19: 2245, 20: 1863, 21: 436, 22: 3072, 23: 799})])",MACs,7760.38144,top1_acc,-55.76106804001113 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 640, 4: 640, 5: 768, 6: 768, 7: 768, 8: 512, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 959, 14: 1110, 15: 2312, 16: 1788, 17: 1774, 18: 2797, 19: 2762, 20: 1261, 21: 436, 22: 3072, 23: 370})])",MACs,7486.572032,top1_acc,-57.56414302422657 +"OrderedDict([(, {0: 704, 1: 704, 2: 320, 3: 640, 4: 640, 5: 768, 6: 768, 7: 576, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 959, 14: 2275, 15: 2788, 16: 1158, 17: 2312, 18: 1028, 19: 2245, 20: 1261, 21: 2187, 22: 2037, 23: 1322})])",MACs,7587.825152,top1_acc,-51.26143737721263 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 3072, 13: 959, 14: 3072, 15: 1096, 16: 2316, 17: 3072, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 1991})])",MACs,7545.226752,top1_acc,-58.04732682978748 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 576, 9: 320, 10: 768, 11: 768, 12: 2692, 13: 3072, 14: 3072, 15: 2788, 16: 1158, 17: 2797, 18: 2297, 19: 1014, 20: 2487, 21: 3072, 22: 2037, 23: 3072})])",MACs,9056.224768,top1_acc,-57.296574949882284 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1762, 15: 1739, 16: 2316, 17: 3072, 18: 1719, 19: 2762, 20: 1261, 21: 3072, 22: 348, 23: 370})])",MACs,8020.035072,top1_acc,-56.52516382961122 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 512, 4: 704, 5: 640, 6: 768, 7: 640, 8: 448, 9: 768, 10: 384, 11: 384, 12: 1588, 13: 2171, 14: 2733, 15: 2788, 16: 2771, 17: 2797, 18: 1028, 19: 2762, 20: 1863, 21: 1469, 22: 2037, 23: 1991})])",MACs,8056.407552,top1_acc,-54.963110834407246 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 3072, 14: 2733, 15: 1739, 16: 1158, 17: 2797, 18: 2797, 19: 1014, 20: 1863, 21: 928, 22: 348, 23: 799})])",MACs,7449.41312,top1_acc,-55.999999270612186 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 320, 12: 949, 13: 1609, 14: 3072, 15: 2312, 16: 3072, 17: 1062, 18: 2297, 19: 1014, 20: 1863, 21: 2187, 22: 3072, 23: 3072})])",MACs,8110.736896,top1_acc,-56.25095574827523 +"OrderedDict([(, {0: 768, 1: 256, 2: 448, 3: 448, 4: 704, 5: 768, 6: 768, 7: 768, 8: 448, 9: 320, 10: 768, 11: 768, 12: 2692, 13: 1609, 14: 1110, 15: 1096, 16: 2771, 17: 2312, 18: 1719, 19: 2245, 20: 670, 21: 3072, 22: 348, 23: 799})])",MACs,7100.564992,top1_acc,-54.95609631481372 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 576, 8: 512, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 2788, 16: 3072, 17: 2312, 18: 1028, 19: 1014, 20: 1261, 21: 3072, 22: 814, 23: 1322})])",MACs,6797.854208,top1_acc,-53.584710740463734 +"OrderedDict([(, {0: 704, 1: 768, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 576, 8: 576, 9: 320, 10: 768, 11: 384, 12: 949, 13: 2685, 14: 1762, 15: 1096, 16: 2316, 17: 1774, 18: 2797, 19: 2762, 20: 3072, 21: 3072, 22: 1360, 23: 1991})])",MACs,8230.60224,top1_acc,-55.999999270612186 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 512, 9: 256, 10: 384, 11: 384, 12: 3072, 13: 959, 14: 1110, 15: 2788, 16: 3072, 17: 3072, 18: 3072, 19: 2245, 20: 670, 21: 3072, 22: 3072, 23: 3072})])",MACs,8482.784768,top1_acc,-58.43483922385055 +"OrderedDict([(, {0: 512, 1: 256, 2: 448, 3: 640, 4: 704, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 320, 12: 3072, 13: 1609, 14: 1762, 15: 1096, 16: 1788, 17: 1774, 18: 1028, 19: 1014, 20: 2487, 21: 1469, 22: 814, 23: 3072})])",MACs,6907.233792,top1_acc,-54.16589932124241 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 512, 9: 320, 10: 384, 11: 384, 12: 2134, 13: 1609, 14: 1110, 15: 2788, 16: 2316, 17: 2312, 18: 2797, 19: 3072, 20: 1863, 21: 436, 22: 1360, 23: 799})])",MACs,7278.495232,top1_acc,-57.388262229281274 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 3072, 13: 1609, 14: 1762, 15: 2312, 16: 3072, 17: 1774, 18: 2297, 19: 2762, 20: 2487, 21: 3072, 22: 814, 23: 370})])",MACs,7748.58496,top1_acc,-58.81447302014868 +"OrderedDict([(, {0: 768, 1: 704, 2: 640, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 512, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 3072, 15: 2312, 16: 2316, 17: 2312, 18: 1028, 19: 3072, 20: 670, 21: 1469, 22: 1360, 23: 1991})])",MACs,7119.504896,top1_acc,-56.33840892174439 +"OrderedDict([(, {0: 704, 1: 256, 2: 640, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 768, 10: 768, 11: 384, 12: 949, 13: 2171, 14: 1762, 15: 1739, 16: 1788, 17: 2312, 18: 1719, 19: 2245, 20: 2487, 21: 928, 22: 1360, 23: 3072})])",MACs,7674.85696,top1_acc,-57.882074372510814 +"OrderedDict([(, {0: 704, 1: 704, 2: 640, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 320, 10: 384, 11: 320, 12: 949, 13: 2685, 14: 1762, 15: 2788, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 3072})])",MACs,8022.328832,top1_acc,-59.124353911192514 +"OrderedDict([(, {0: 704, 1: 448, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 320, 10: 768, 11: 768, 12: 2692, 13: 2171, 14: 2733, 15: 2312, 16: 3072, 17: 1774, 18: 1028, 19: 2245, 20: 2487, 21: 928, 22: 814, 23: 1322})])",MACs,7798.72,top1_acc,-54.44111532535151 +"OrderedDict([(, {0: 704, 1: 448, 2: 640, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 768, 12: 2692, 13: 2171, 14: 1762, 15: 2312, 16: 2771, 17: 2797, 18: 1028, 19: 1654, 20: 1863, 21: 436, 22: 814, 23: 1991})])",MACs,7709.26336,top1_acc,-56.25095574827523 +"OrderedDict([(, {0: 768, 1: 768, 2: 640, 3: 512, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 2685, 14: 1110, 15: 1096, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 3072, 23: 1991})])",MACs,7712.86784,top1_acc,-58.296380069576934 +"OrderedDict([(, {0: 704, 1: 704, 2: 640, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 448, 9: 320, 10: 768, 11: 384, 12: 2692, 13: 1609, 14: 3072, 15: 2312, 16: 3072, 17: 2312, 18: 2297, 19: 2245, 20: 1863, 21: 436, 22: 348, 23: 3072})])",MACs,8061.388288,top1_acc,-58.05514135255713 +"OrderedDict([(, {0: 768, 1: 704, 2: 320, 3: 768, 4: 704, 5: 640, 6: 768, 7: 640, 8: 768, 9: 320, 10: 384, 11: 384, 12: 2692, 13: 1609, 14: 1762, 15: 2312, 16: 2316, 17: 2312, 18: 1719, 19: 3072, 20: 1863, 21: 1469, 22: 814, 23: 1991})])",MACs,7759.07072,top1_acc,-57.56414302422657 +"OrderedDict([(, {0: 512, 1: 704, 2: 768, 3: 640, 4: 640, 5: 768, 6: 768, 7: 640, 8: 448, 9: 320, 10: 768, 11: 320, 12: 1588, 13: 959, 14: 3072, 15: 1739, 16: 1788, 17: 1062, 18: 2797, 19: 2245, 20: 1863, 21: 2187, 22: 814, 23: 1991})])",MACs,7454.590464,top1_acc,-52.12174394953254 +"OrderedDict([(, {0: 768, 1: 704, 2: 320, 3: 512, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 3072, 15: 3072, 16: 1158, 17: 2797, 18: 2297, 19: 1014, 20: 1261, 21: 928, 22: 3072, 23: 3072})])",MACs,8128.497152,top1_acc,-58.07606001872874 +"OrderedDict([(, {0: 512, 1: 320, 2: 640, 3: 448, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 384, 12: 1588, 13: 2171, 14: 1762, 15: 1096, 16: 1788, 17: 3072, 18: 2797, 19: 1014, 20: 1863, 21: 436, 22: 3072, 23: 3072})])",MACs,7692.486144,top1_acc,-54.9719450045872 +"OrderedDict([(, {0: 704, 1: 320, 2: 448, 3: 512, 4: 704, 5: 640, 6: 768, 7: 576, 8: 768, 9: 320, 10: 768, 11: 768, 12: 1588, 13: 2685, 14: 2733, 15: 2312, 16: 1788, 17: 1774, 18: 1719, 19: 3072, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,7357.859328,top1_acc,-59.06042341193154 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 2685, 14: 2275, 15: 3072, 16: 3072, 17: 3072, 18: 2297, 19: 2245, 20: 2487, 21: 3072, 22: 348, 23: 799})])",MACs,8854.50496,top1_acc,-59.81008799238268 +"OrderedDict([(, {0: 512, 1: 320, 2: 640, 3: 512, 4: 640, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 768, 12: 2692, 13: 3072, 14: 1762, 15: 3072, 16: 1158, 17: 1062, 18: 1028, 19: 2762, 20: 1261, 21: 3072, 22: 348, 23: 799})])",MACs,7478.511104,top1_acc,-53.117084680197216 +"OrderedDict([(, {0: 512, 1: 768, 2: 448, 3: 640, 4: 704, 5: 640, 6: 768, 7: 640, 8: 448, 9: 320, 10: 768, 11: 320, 12: 2692, 13: 3072, 14: 2275, 15: 2312, 16: 1158, 17: 2312, 18: 2297, 19: 3072, 20: 3072, 21: 1469, 22: 2037, 23: 799})])",MACs,8195.54048,top1_acc,-58.79759000771466 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 768, 4: 704, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 2171, 14: 1762, 15: 1739, 16: 1788, 17: 2797, 18: 2797, 19: 2245, 20: 670, 21: 436, 22: 3072, 23: 1991})])",MACs,8042.382848,top1_acc,-57.80903072486336 +"OrderedDict([(, {0: 512, 1: 256, 2: 640, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 1788, 17: 2797, 18: 2797, 19: 2245, 20: 1261, 21: 928, 22: 2037, 23: 3072})])",MACs,7554.205184,top1_acc,-55.30217811194 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3072, 13: 2685, 14: 3072, 15: 1739, 16: 2316, 17: 3072, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 1991})])",MACs,8310.88384,top1_acc,-57.57702121003263 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 768, 11: 320, 12: 3072, 13: 3072, 14: 2275, 15: 2312, 16: 3072, 17: 2312, 18: 2297, 19: 2762, 20: 2487, 21: 3072, 22: 814, 23: 370})])",MACs,8733.59104,top1_acc,-59.56102836701802 +"OrderedDict([(, {0: 768, 1: 448, 2: 640, 3: 768, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 320, 10: 768, 11: 768, 12: 2692, 13: 3072, 14: 3072, 15: 2788, 16: 2771, 17: 2797, 18: 2297, 19: 1014, 20: 2487, 21: 3072, 22: 2037, 23: 3072})])",MACs,9536.931328,top1_acc,-58.05514135255713 +"OrderedDict([(, {0: 704, 1: 320, 2: 448, 3: 512, 4: 704, 5: 640, 6: 768, 7: 576, 8: 768, 9: 320, 10: 768, 11: 768, 12: 1588, 13: 2685, 14: 1762, 15: 2312, 16: 1788, 17: 1774, 18: 1719, 19: 3072, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,7166.95296,top1_acc,-57.78111402851518 +"OrderedDict([(, {0: 704, 1: 704, 2: 320, 3: 640, 4: 640, 5: 768, 6: 768, 7: 576, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3072, 14: 2275, 15: 2788, 16: 1788, 17: 2312, 18: 2797, 19: 3072, 20: 1261, 21: 2187, 22: 2037, 23: 3072})])",MACs,8981.579264,top1_acc,-59.319703754488195 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 640, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 1609, 14: 1110, 15: 1096, 16: 2316, 17: 3072, 18: 3072, 19: 1014, 20: 670, 21: 3072, 22: 348, 23: 1322})])",MACs,7041.975808,top1_acc,-57.03980726573153 +"OrderedDict([(, {0: 704, 1: 768, 2: 640, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 512, 9: 320, 10: 384, 11: 384, 12: 2134, 13: 2685, 14: 1110, 15: 2788, 16: 3072, 17: 2312, 18: 2797, 19: 3072, 20: 1863, 21: 436, 22: 1360, 23: 3072})])",MACs,8303.67488,top1_acc,-56.29066123861417 +"OrderedDict([(, {0: 768, 1: 320, 2: 640, 3: 512, 4: 704, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 768, 12: 2692, 13: 1609, 14: 1762, 15: 3072, 16: 2771, 17: 2312, 18: 1719, 19: 2245, 20: 1261, 21: 3072, 22: 348, 23: 799})])",MACs,7924.286976,top1_acc,-57.26811598747922 +"OrderedDict([(, {0: 704, 1: 704, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 384, 12: 3072, 13: 2685, 14: 2275, 15: 2788, 16: 1158, 17: 3072, 18: 2797, 19: 2245, 20: 1863, 21: 3072, 22: 3072, 23: 799})])",MACs,9062.778368,top1_acc,-58.3024886611504 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 320, 12: 3072, 13: 959, 14: 3072, 15: 1739, 16: 2771, 17: 3072, 18: 2797, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 1991})])",MACs,7843.350016,top1_acc,-59.561622728650995 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 320, 10: 768, 11: 768, 12: 949, 13: 2685, 14: 3072, 15: 2788, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 3072})])",MACs,8416.200192,top1_acc,-59.124353911192514 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1762, 15: 3072, 16: 2316, 17: 3072, 18: 1719, 19: 2762, 20: 1261, 21: 3072, 22: 348, 23: 370})])",MACs,8363.902464,top1_acc,-57.535934835985316 +"OrderedDict([(, {0: 704, 1: 768, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 576, 8: 576, 9: 320, 10: 768, 11: 320, 12: 2692, 13: 2685, 14: 1762, 15: 1096, 16: 3072, 17: 1774, 18: 2797, 19: 2762, 20: 2487, 21: 3072, 22: 348, 23: 1991})])",MACs,8380.67968,top1_acc,-56.75682416159784 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1609, 14: 1110, 15: 2788, 16: 2316, 17: 1774, 18: 2797, 19: 3072, 20: 2487, 21: 436, 22: 814, 23: 799})])",MACs,7481.52576,top1_acc,-59.052091345546444 +"OrderedDict([(, {0: 704, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 512, 9: 256, 10: 384, 11: 384, 12: 3072, 13: 2685, 14: 1110, 15: 2788, 16: 3072, 17: 1774, 18: 2797, 19: 2245, 20: 1863, 21: 436, 22: 3072, 23: 799})])",MACs,7755.007488,top1_acc,-59.55860617587142 +"OrderedDict([(, {0: 768, 1: 704, 2: 320, 3: 768, 4: 704, 5: 640, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 3072, 14: 1762, 15: 2312, 16: 1158, 17: 2312, 18: 1719, 19: 3072, 20: 1863, 21: 1469, 22: 348, 23: 799})])",MACs,7683.900928,top1_acc,-57.799531805516345 +"OrderedDict([(, {0: 704, 1: 768, 2: 640, 3: 768, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 2171, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 1719, 19: 3072, 20: 3072, 21: 2187, 22: 3072, 23: 799})])",MACs,9088.009728,top1_acc,-57.53011877541249 +"OrderedDict([(, {0: 512, 1: 448, 2: 448, 3: 640, 4: 704, 5: 640, 6: 768, 7: 640, 8: 448, 9: 320, 10: 768, 11: 320, 12: 2692, 13: 3072, 14: 2275, 15: 2312, 16: 1158, 17: 2312, 18: 2297, 19: 3072, 20: 3072, 21: 1469, 22: 814, 23: 799})])",MACs,7818.774016,top1_acc,-59.052309924674326 +"OrderedDict([(, {0: 704, 1: 320, 2: 640, 3: 448, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 768, 12: 1588, 13: 2171, 14: 2733, 15: 1096, 16: 3072, 17: 3072, 18: 2797, 19: 2245, 20: 1863, 21: 436, 22: 3072, 23: 3072})])",MACs,8623.228416,top1_acc,-57.01743615529957 +"OrderedDict([(, {0: 704, 1: 320, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 768, 10: 768, 11: 384, 12: 2692, 13: 2171, 14: 1762, 15: 1739, 16: 2771, 17: 2312, 18: 1719, 19: 1014, 20: 2487, 21: 436, 22: 1360, 23: 370})])",MACs,7422.608896,top1_acc,-56.773484921502835 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 2733, 15: 1096, 16: 1158, 17: 2797, 18: 2797, 19: 1014, 20: 1863, 21: 928, 22: 348, 23: 799})])",MACs,6735.463936,top1_acc,-56.245532335716454 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 512, 4: 704, 5: 640, 6: 768, 7: 640, 8: 448, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 1762, 15: 2312, 16: 1158, 17: 1774, 18: 2297, 19: 3072, 20: 3072, 21: 1469, 22: 2037, 23: 799})])",MACs,7210.5344,top1_acc,-59.30837029344534 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 768, 10: 768, 11: 768, 12: 1588, 13: 1609, 14: 1110, 15: 3072, 16: 1158, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 928, 22: 814, 23: 3072})])",MACs,7293.830656,top1_acc,-55.36405531329313 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 576, 8: 512, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2733, 15: 2788, 16: 3072, 17: 2312, 18: 1028, 19: 1014, 20: 1261, 21: 3072, 22: 814, 23: 1322})])",MACs,6988.760576,top1_acc,-54.278833816077956 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 768, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1739, 16: 1158, 17: 1062, 18: 1028, 19: 2245, 20: 670, 21: 2187, 22: 814, 23: 1322})])",MACs,6330.320384,top1_acc,-51.2652366007397 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 512, 9: 256, 10: 768, 11: 384, 12: 3072, 13: 959, 14: 1110, 15: 2788, 16: 3072, 17: 1774, 18: 3072, 19: 2245, 20: 1261, 21: 1469, 22: 3072, 23: 3072})])",MACs,8192.198144,top1_acc,-58.886326969667344 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 320, 10: 384, 11: 320, 12: 949, 13: 1609, 14: 1762, 15: 2788, 16: 2316, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6997.149184,top1_acc,-58.45760203069087 +"OrderedDict([(, {0: 512, 1: 256, 2: 448, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 448, 9: 320, 10: 768, 11: 768, 12: 2692, 13: 3072, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 2762, 20: 670, 21: 3072, 22: 348, 23: 799})])",MACs,6654.78912,top1_acc,-47.50135924085151 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 512, 9: 320, 10: 768, 11: 320, 12: 2692, 13: 2685, 14: 1110, 15: 3072, 16: 3072, 17: 1062, 18: 2297, 19: 2245, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,7412.123136,top1_acc,-56.503225581458295 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7003.833856,top1_acc,-59.81135922805257 +"OrderedDict([(, {0: 704, 1: 320, 2: 640, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 320, 10: 384, 11: 320, 12: 949, 13: 3072, 14: 1762, 15: 2788, 16: 2771, 17: 1062, 18: 1719, 19: 2245, 20: 670, 21: 3072, 22: 348, 23: 1322})])",MACs,7090.800128,top1_acc,-57.52407929937235 +"OrderedDict([(, {0: 512, 1: 256, 2: 640, 3: 512, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 768, 12: 2692, 13: 3072, 14: 1762, 15: 1739, 16: 1158, 17: 1062, 18: 1028, 19: 2762, 20: 1261, 21: 3072, 22: 348, 23: 799})])",MACs,7134.643712,top1_acc,-53.65057053910051 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 384, 12: 949, 13: 2685, 14: 2275, 15: 3072, 16: 2316, 17: 3072, 18: 2297, 19: 2245, 20: 3072, 21: 3072, 22: 1360, 23: 799})])",MACs,8704.42752,top1_acc,-57.2739655014278 +"OrderedDict([(, {0: 576, 1: 256, 2: 448, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 1609, 14: 1762, 15: 2312, 16: 3072, 17: 2312, 18: 2297, 19: 2762, 20: 1863, 21: 3072, 22: 1360, 23: 370})])",MACs,7600.080384,top1_acc,-57.791810761975015 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 512, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 959, 14: 1110, 15: 2788, 16: 1158, 17: 3072, 18: 3072, 19: 2245, 20: 670, 21: 3072, 22: 3072, 23: 3072})])",MACs,8488.15872,top1_acc,-57.84786967005595 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 2797, 19: 1014, 20: 1863, 21: 928, 22: 814, 23: 1991})])",MACs,7524.582912,top1_acc,-56.01977832642419 +"OrderedDict([(, {0: 512, 1: 256, 2: 448, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 384, 12: 949, 13: 2171, 14: 1762, 15: 1739, 16: 1788, 17: 2312, 18: 1028, 19: 2245, 20: 2487, 21: 928, 22: 1360, 23: 3072})])",MACs,7348.16,top1_acc,-55.22294868395369 +"OrderedDict([(, {0: 768, 1: 768, 2: 640, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 768, 10: 768, 11: 768, 12: 1588, 13: 1609, 14: 1110, 15: 3072, 16: 2771, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 928, 22: 2037, 23: 3072})])",MACs,8151.30368,top1_acc,-58.31040124744803 +"OrderedDict([(, {0: 512, 1: 448, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 320, 10: 768, 11: 384, 12: 2692, 13: 2171, 14: 1762, 15: 2312, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 2487, 21: 928, 22: 814, 23: 1322})])",MACs,6744.114688,top1_acc,-54.16832977810567 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2275, 15: 1096, 16: 3072, 17: 2312, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7528.842752,top1_acc,-60.33168402681876 +"OrderedDict([(, {0: 704, 1: 320, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 768, 10: 768, 11: 384, 12: 2692, 13: 2171, 14: 1762, 15: 1739, 16: 2771, 17: 2312, 18: 1719, 19: 1014, 20: 2487, 21: 436, 22: 1360, 23: 1322})])",MACs,7718.831616,top1_acc,-57.78590180299453 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 959, 14: 3072, 15: 1096, 16: 2771, 17: 3072, 18: 2797, 19: 1014, 20: 1261, 21: 436, 22: 1360, 23: 1322})])",MACs,7479.55968,top1_acc,-59.30840237241851 +"OrderedDict([(, {0: 768, 1: 704, 2: 448, 3: 448, 4: 704, 5: 768, 6: 768, 7: 768, 8: 448, 9: 768, 10: 768, 11: 768, 12: 2692, 13: 1609, 14: 1110, 15: 1096, 16: 2771, 17: 2312, 18: 1719, 19: 2245, 20: 670, 21: 3072, 22: 348, 23: 799})])",MACs,7482.246656,top1_acc,-55.728939309428405 +"OrderedDict([(, {0: 704, 1: 704, 2: 768, 3: 512, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 3072, 13: 2685, 14: 1110, 15: 2788, 16: 3072, 17: 1774, 18: 2797, 19: 2245, 20: 1863, 21: 436, 22: 3072, 23: 799})])",MACs,8000.374272,top1_acc,-58.57509882742485 +"OrderedDict([(, {0: 704, 1: 704, 2: 320, 3: 512, 4: 704, 5: 640, 6: 768, 7: 640, 8: 768, 9: 320, 10: 768, 11: 320, 12: 949, 13: 1609, 14: 1762, 15: 2312, 16: 2316, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,7084.115456,top1_acc,-57.111785854249064 +"OrderedDict([(, {0: 704, 1: 704, 2: 320, 3: 640, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 2788, 16: 3072, 17: 2797, 18: 3072, 19: 3072, 20: 1261, 21: 2187, 22: 2037, 23: 3072})])",MACs,9649.194496,top1_acc,-59.33815828411364 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 2733, 15: 1096, 16: 1158, 17: 2797, 18: 1028, 19: 1014, 20: 1863, 21: 928, 22: 814, 23: 799})])",MACs,6479.283712,top1_acc,-51.79821135635028 +"OrderedDict([(, {0: 512, 1: 448, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 320, 10: 768, 11: 768, 12: 2692, 13: 3072, 14: 1762, 15: 2312, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 2487, 21: 928, 22: 814, 23: 1322})])",MACs,7084.836352,top1_acc,-54.71054662620462 +"OrderedDict([(, {0: 576, 1: 256, 2: 448, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 320, 12: 3072, 13: 1609, 14: 1762, 15: 2312, 16: 3072, 17: 1774, 18: 2297, 19: 2762, 20: 2487, 21: 3072, 22: 814, 23: 799})])",MACs,7914.71872,top1_acc,-56.53000167449913 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 320, 10: 384, 11: 768, 12: 2692, 13: 3072, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7773.685248,top1_acc,-57.55298089385917 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 512, 9: 256, 10: 384, 11: 320, 12: 949, 13: 2685, 14: 3072, 15: 2312, 16: 2316, 17: 3072, 18: 1028, 19: 3072, 20: 670, 21: 3072, 22: 1360, 23: 1991})])",MACs,7977.96096,top1_acc,-56.046499517765305 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 256, 10: 768, 11: 320, 12: 3072, 13: 1609, 14: 1762, 15: 1739, 16: 3072, 17: 1062, 18: 2297, 19: 2245, 20: 2487, 21: 3072, 22: 814, 23: 1322})])",MACs,7963.149824,top1_acc,-57.52957675685067 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 512, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 768, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 1158, 17: 2797, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,6718.817792,top1_acc,-55.20601255693537 +"OrderedDict([(, {0: 512, 1: 256, 2: 448, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 448, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 3072, 19: 2762, 20: 670, 21: 3072, 22: 348, 23: 3072})])",MACs,7523.730944,top1_acc,-51.34084664186066 +"OrderedDict([(, {0: 512, 1: 448, 2: 448, 3: 512, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 768, 10: 768, 11: 384, 12: 2692, 13: 2171, 14: 1762, 15: 2312, 16: 1788, 17: 1774, 18: 1028, 19: 2245, 20: 2487, 21: 928, 22: 814, 23: 1322})])",MACs,7191.791104,top1_acc,-54.694510176889025 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 2733, 15: 2788, 16: 2316, 17: 2797, 18: 2797, 19: 1014, 20: 1863, 21: 928, 22: 2037, 23: 799})])",MACs,7655.130624,top1_acc,-56.046499517765305 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 320, 12: 3072, 13: 959, 14: 3072, 15: 2788, 16: 3072, 17: 3072, 18: 2797, 19: 1014, 20: 1261, 21: 3072, 22: 2037, 23: 1991})])",MACs,8627.029504,top1_acc,-59.561622728650995 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 768, 11: 320, 12: 3072, 13: 3072, 14: 2733, 15: 2312, 16: 2316, 17: 2797, 18: 2297, 19: 1014, 20: 2487, 21: 3072, 22: 814, 23: 370})])",MACs,8208.582144,top1_acc,-58.80544551678445 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1739, 16: 1158, 17: 1062, 18: 1028, 19: 2245, 20: 670, 21: 2187, 22: 814, 23: 370})])",MACs,6034.097664,top1_acc,-50.462160864783925 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 640, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 1609, 14: 1110, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 1469, 22: 814, 23: 1991})])",MACs,7073.695232,top1_acc,-54.4421655829423 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 640, 4: 640, 5: 768, 6: 768, 7: 768, 8: 512, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 959, 14: 1110, 15: 2312, 16: 1788, 17: 1774, 18: 2797, 19: 2762, 20: 1261, 21: 436, 22: 3072, 23: 370})])",MACs,7104.890368,top1_acc,-54.72224847569017 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 320, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2771, 17: 2797, 18: 2797, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7056.590336,top1_acc,-58.586615151475115 +"OrderedDict([(, {0: 512, 1: 320, 2: 448, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 320, 10: 384, 11: 768, 12: 1588, 13: 2685, 14: 2733, 15: 2788, 16: 1788, 17: 2797, 18: 1719, 19: 3072, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,7270.893056,top1_acc,-57.57702121003263 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 320, 10: 384, 11: 768, 12: 949, 13: 2685, 14: 2275, 15: 2788, 16: 1788, 17: 2312, 18: 2797, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 3072})])",MACs,7748.58496,top1_acc,-57.6660981486724 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 576, 8: 512, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2733, 15: 2788, 16: 3072, 17: 2312, 18: 2797, 19: 1014, 20: 1261, 21: 3072, 22: 348, 23: 1322})])",MACs,7244.9408,top1_acc,-56.94075373847854 +"OrderedDict([(, {0: 512, 1: 256, 2: 640, 3: 512, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 2692, 13: 2171, 14: 1762, 15: 1739, 16: 1158, 17: 1062, 18: 1028, 19: 2762, 20: 1261, 21: 3072, 22: 348, 23: 799})])",MACs,6793.922048,top1_acc,-52.09512852126564 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 448, 9: 256, 10: 768, 11: 768, 12: 2692, 13: 3072, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 2762, 20: 670, 21: 3072, 22: 348, 23: 370})])",MACs,6488.65536,top1_acc,-47.801701262661275 +"OrderedDict([(, {0: 704, 1: 704, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 3072, 13: 959, 14: 2275, 15: 2788, 16: 1788, 17: 2312, 18: 2797, 19: 3072, 20: 1261, 21: 2187, 22: 2037, 23: 3072})])",MACs,8211.727872,top1_acc,-56.44979995646169 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2275, 15: 3072, 16: 3072, 17: 2312, 18: 2297, 19: 2245, 20: 2487, 21: 1469, 22: 348, 23: 799})])",MACs,7996.048896,top1_acc,-59.810735565977936 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 2312, 16: 1158, 17: 1774, 18: 1028, 19: 2762, 20: 670, 21: 2187, 22: 814, 23: 370})])",MACs,6115.75552,top1_acc,-53.16372091056994 +"OrderedDict([(, {0: 512, 1: 256, 2: 640, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 320, 12: 2692, 13: 3072, 14: 1762, 15: 1739, 16: 2771, 17: 1062, 18: 2797, 19: 2762, 20: 1261, 21: 3072, 22: 348, 23: 799})])",MACs,7717.78304,top1_acc,-57.78590180299453 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 512, 4: 640, 5: 768, 6: 768, 7: 640, 8: 512, 9: 256, 10: 768, 11: 384, 12: 2692, 13: 959, 14: 1110, 15: 2788, 16: 3072, 17: 1774, 18: 1028, 19: 2245, 20: 1261, 21: 1469, 22: 3072, 23: 799})])",MACs,7323.25632,top1_acc,-55.74138665741355 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 320, 10: 768, 11: 384, 12: 949, 13: 2171, 14: 1762, 15: 1739, 16: 1158, 17: 2312, 18: 1028, 19: 1014, 20: 2487, 21: 928, 22: 1360, 23: 3072})])",MACs,6900.483584,top1_acc,-54.963110834407246 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 1609, 14: 1762, 15: 1096, 16: 1158, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6077.482496,top1_acc,-55.14555448601601 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 576, 8: 512, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2733, 15: 1739, 16: 2771, 17: 2312, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 1322})])",MACs,6205.081088,top1_acc,-56.27810283916928 +"OrderedDict([(, {0: 512, 1: 704, 2: 768, 3: 640, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 320, 10: 768, 11: 320, 12: 949, 13: 1609, 14: 1762, 15: 2788, 16: 2316, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 1469, 22: 2037, 23: 799})])",MACs,7636.452864,top1_acc,-57.174438236555645 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 640, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 768, 11: 320, 12: 3072, 13: 1609, 14: 1762, 15: 2312, 16: 3072, 17: 1774, 18: 2297, 19: 2762, 20: 2487, 21: 1469, 22: 814, 23: 370})])",MACs,7869.629952,top1_acc,-57.269997080775724 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 1609, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 1322})])",MACs,6112.085504,top1_acc,-55.34186082067715 +"OrderedDict([(, {0: 512, 1: 256, 2: 448, 3: 640, 4: 704, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 320, 12: 3072, 13: 3072, 14: 2275, 15: 1096, 16: 1788, 17: 2312, 18: 1028, 19: 1014, 20: 2487, 21: 3072, 22: 814, 23: 3072})])",MACs,7771.19488,top1_acc,-54.963110834407246 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 512, 4: 704, 5: 640, 6: 768, 7: 640, 8: 576, 9: 320, 10: 768, 11: 320, 12: 2692, 13: 1609, 14: 1762, 15: 2312, 16: 1158, 17: 1774, 18: 3072, 19: 3072, 20: 3072, 21: 1469, 22: 2037, 23: 799})])",MACs,7608.272384,top1_acc,-57.53011877541249 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 320, 12: 3072, 13: 1609, 14: 3072, 15: 1096, 16: 1158, 17: 2797, 18: 2797, 19: 1014, 20: 1261, 21: 436, 22: 1360, 23: 1322})])",MACs,6990.792192,top1_acc,-56.03228770167558 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 448, 9: 256, 10: 768, 11: 768, 12: 2692, 13: 3072, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 2797, 19: 2762, 20: 1261, 21: 3072, 22: 348, 23: 1322})])",MACs,7139.821056,top1_acc,-51.57664784865402 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2275, 15: 1096, 16: 3072, 17: 1774, 18: 1028, 19: 2762, 20: 670, 21: 2187, 22: 2037, 23: 370})])",MACs,6704.006656,top1_acc,-56.304919157109346 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2275, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 2487, 21: 436, 22: 2037, 23: 799})])",MACs,7457.27744,top1_acc,-59.845263312315645 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 959, 14: 2733, 15: 1739, 16: 2771, 17: 3072, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 1991})])",MACs,7565.215232,top1_acc,-56.75517176765141 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 384, 12: 3072, 13: 2685, 14: 2275, 15: 3072, 16: 3072, 17: 3072, 18: 2797, 19: 3072, 20: 2487, 21: 3072, 22: 814, 23: 799})])",MACs,9445.312,top1_acc,-58.29211024374039 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 768, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 2312, 16: 1158, 17: 1774, 18: 1028, 19: 2762, 20: 670, 21: 2187, 22: 814, 23: 370})])",MACs,6497.437184,top1_acc,-53.37975510473064 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2275, 15: 1096, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7542.408704,top1_acc,-60.079161428273785 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 2733, 15: 2788, 16: 1158, 17: 2797, 18: 2797, 19: 2762, 20: 1863, 21: 928, 22: 2037, 23: 799})])",MACs,7771.129344,top1_acc,-57.03054933279827 +"OrderedDict([(, {0: 512, 1: 448, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 320, 10: 768, 11: 384, 12: 2692, 13: 2171, 14: 1762, 15: 2312, 16: 1158, 17: 1774, 18: 2797, 19: 1014, 20: 2487, 21: 928, 22: 814, 23: 1322})])",MACs,7091.91424,top1_acc,-57.52393119535992 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6763.382272,top1_acc,-59.55747684873348 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 640, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 2692, 13: 1609, 14: 2733, 15: 1096, 16: 1158, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6401.1648,top1_acc,-56.548659976463256 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2733, 15: 1739, 16: 2771, 17: 2312, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 1322})])",MACs,6177.818112,top1_acc,-55.992798722501256 +"OrderedDict([(, {0: 512, 1: 320, 2: 448, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 320, 10: 384, 11: 320, 12: 1588, 13: 2685, 14: 2733, 15: 2312, 16: 1788, 17: 2312, 18: 1719, 19: 3072, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6891.111936,top1_acc,-58.800949377178846 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 640, 4: 640, 5: 640, 6: 768, 7: 768, 8: 448, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 1609, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 2297, 19: 1014, 20: 1261, 21: 1469, 22: 348, 23: 1322})])",MACs,6353.6512,top1_acc,-55.75034099514093 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 384, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2771, 17: 3072, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6566.249984,top1_acc,-57.308974406677834 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 1609, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5542.708736,top1_acc,-53.980851421647245 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2134, 13: 959, 14: 1762, 15: 2312, 16: 1158, 17: 2312, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6940.591616,top1_acc,-58.3024886611504 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 2297, 19: 2245, 20: 1261, 21: 1469, 22: 348, 23: 370})])",MACs,7542.605312,top1_acc,-60.32121451400153 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 3072, 15: 1739, 16: 1158, 17: 2797, 18: 2797, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,6996.952576,top1_acc,-56.009004195227384 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 1110, 15: 2788, 16: 2316, 17: 1774, 18: 2297, 19: 2245, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,6890.71872,top1_acc,-60.32121451400153 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1739, 16: 1158, 17: 1062, 18: 1028, 19: 2245, 20: 670, 21: 2187, 22: 814, 23: 370})])",MACs,5652.416,top1_acc,-51.27103010689016 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2771, 17: 2312, 18: 2797, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7288.391168,top1_acc,-56.046499517765305 +"OrderedDict([(, {0: 704, 1: 704, 2: 640, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 2685, 14: 1762, 15: 1096, 16: 3072, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 3072})])",MACs,6986.663424,top1_acc,-57.5435670477595 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 320, 12: 3072, 13: 959, 14: 3072, 15: 2788, 16: 3072, 17: 3072, 18: 1028, 19: 1014, 20: 1261, 21: 3072, 22: 2037, 23: 1991})])",MACs,8279.229952,top1_acc,-55.23181756655187 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 2733, 15: 1096, 16: 1158, 17: 2797, 18: 1028, 19: 1014, 20: 1863, 21: 928, 22: 2037, 23: 799})])",MACs,6719.735296,top1_acc,-51.5322969522302 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 512, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 768, 11: 768, 12: 2692, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 3072, 18: 1028, 19: 1014, 20: 1261, 21: 3072, 22: 2037, 23: 1322})])",MACs,7359.6288,top1_acc,-54.72224847569017 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 959, 14: 3072, 15: 1096, 16: 2771, 17: 3072, 18: 2797, 19: 1014, 20: 1261, 21: 436, 22: 1360, 23: 1322})])",MACs,7506.822656,top1_acc,-58.551086611815464 +"OrderedDict([(, {0: 768, 1: 704, 2: 640, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 512, 9: 256, 10: 384, 11: 768, 12: 949, 13: 959, 14: 3072, 15: 2788, 16: 2316, 17: 2797, 18: 1028, 19: 3072, 20: 670, 21: 1469, 22: 1360, 23: 1991})])",MACs,7499.286016,top1_acc,-54.91920151313351 +"OrderedDict([(, {0: 512, 1: 704, 2: 768, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 320, 10: 768, 11: 320, 12: 2134, 13: 1609, 14: 1762, 15: 2788, 16: 1158, 17: 2797, 18: 1028, 19: 2245, 20: 670, 21: 2187, 22: 814, 23: 799})])",MACs,6984.4352,top1_acc,-54.68753188432375 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 1609, 14: 2733, 15: 2312, 16: 1158, 17: 2797, 18: 1028, 19: 2762, 20: 1863, 21: 2187, 22: 814, 23: 370})])",MACs,6951.929344,top1_acc,-54.426941035487495 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2134, 13: 959, 14: 3072, 15: 1739, 16: 2771, 17: 2312, 18: 2797, 19: 1014, 20: 1261, 21: 3072, 22: 814, 23: 1322})])",MACs,7519.471104,top1_acc,-55.78770438298012 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 1609, 14: 2275, 15: 1096, 16: 1158, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 3072, 22: 348, 23: 799})])",MACs,6696.601088,top1_acc,-57.08231055399866 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1739, 16: 2316, 17: 1062, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6046.811648,top1_acc,-56.63656369027515 +"OrderedDict([(, {0: 576, 1: 256, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1774, 18: 2797, 19: 1014, 20: 670, 21: 928, 22: 348, 23: 799})])",MACs,5899.290112,top1_acc,-53.41430411919947 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 320, 10: 384, 11: 320, 12: 3072, 13: 959, 14: 2733, 15: 2788, 16: 3072, 17: 3072, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 1991})])",MACs,7312.639488,top1_acc,-56.29066123861417 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 2685, 14: 1762, 15: 3072, 16: 3072, 17: 3072, 18: 2297, 19: 2245, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,8235.386368,top1_acc,-59.55827154899262 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 576, 9: 256, 10: 768, 11: 384, 12: 2134, 13: 959, 14: 2275, 15: 1096, 16: 3072, 17: 2312, 18: 3072, 19: 2762, 20: 1261, 21: 2187, 22: 2037, 23: 370})])",MACs,7599.81824,top1_acc,-56.57894359264041 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1739, 16: 1158, 17: 1062, 18: 1028, 19: 2245, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5963.122176,top1_acc,-52.060268370665185 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2275, 15: 3072, 16: 3072, 17: 2312, 18: 2297, 19: 2245, 20: 2487, 21: 2187, 22: 814, 23: 799})])",MACs,8310.621696,top1_acc,-59.55827154899262 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 2685, 14: 2275, 15: 3072, 16: 1158, 17: 3072, 18: 2297, 19: 2245, 20: 2487, 21: 1469, 22: 348, 23: 799})])",MACs,7972.193792,top1_acc,-57.78590180299453 +"OrderedDict([(, {0: 704, 1: 320, 2: 768, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 2312, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 2187, 22: 814, 23: 3072})])",MACs,7779.583488,top1_acc,-56.5965534490769 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 2245, 20: 670, 21: 2187, 22: 814, 23: 370})])",MACs,5525.997056,top1_acc,-50.46330570516372 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2275, 15: 1096, 16: 3072, 17: 1774, 18: 1719, 19: 2762, 20: 670, 21: 2187, 22: 2037, 23: 370})])",MACs,6948.914688,top1_acc,-58.586615151475115 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7429.293568,top1_acc,-57.84786967005595 +"OrderedDict([(, {0: 512, 1: 448, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 2797, 19: 2245, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,7328.761344,top1_acc,-60.31932328167873 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2275, 15: 1096, 16: 3072, 17: 2312, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,7613.187584,top1_acc,-60.33168402681876 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 1609, 14: 1762, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6739.068416,top1_acc,-56.09903802347734 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 2685, 14: 2733, 15: 3072, 16: 1158, 17: 3072, 18: 2797, 19: 1014, 20: 1863, 21: 3072, 22: 348, 23: 799})])",MACs,8165.524992,top1_acc,-57.07798240133651 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2771, 17: 2797, 18: 2797, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,7197.361664,top1_acc,-58.3024886611504 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1739, 16: 1158, 17: 1062, 18: 2797, 19: 2245, 20: 670, 21: 2187, 22: 814, 23: 799})])",MACs,6221.530624,top1_acc,-51.57664784865402 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 2297, 19: 2245, 20: 2487, 21: 1469, 22: 348, 23: 799})])",MACs,8086.09536,top1_acc,-61.07363335829461 +"OrderedDict([(, {0: 512, 1: 320, 2: 448, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 320, 10: 384, 11: 320, 12: 2134, 13: 2685, 14: 2733, 15: 1739, 16: 1788, 17: 1062, 18: 1028, 19: 3072, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6419.84256,top1_acc,-51.79481406500624 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1739, 16: 2316, 17: 1062, 18: 1028, 19: 2762, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,6237.914624,top1_acc,-53.379999660538225 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 1609, 14: 3072, 15: 1739, 16: 2771, 17: 3072, 18: 2797, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 1991})])",MACs,7998.408192,top1_acc,-58.05514135255713 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 2692, 13: 1609, 14: 2733, 15: 1096, 16: 2771, 17: 2797, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,6135.41632,top1_acc,-54.99492780843731 +"OrderedDict([(, {0: 512, 1: 320, 2: 640, 3: 512, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1739, 16: 1158, 17: 1062, 18: 1028, 19: 2245, 20: 670, 21: 1469, 22: 348, 23: 370})])",MACs,5719.524864,top1_acc,-51.00320295795891 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 512, 4: 704, 5: 640, 6: 768, 7: 640, 8: 448, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 1762, 15: 2312, 16: 3072, 17: 1774, 18: 2297, 19: 3072, 20: 3072, 21: 3072, 22: 2037, 23: 799})])",MACs,8092.845568,top1_acc,-57.78590180299453 +"OrderedDict([(, {0: 576, 1: 704, 2: 640, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 2685, 14: 1762, 15: 1096, 16: 1158, 17: 2797, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5704.51712,top1_acc,-53.68907320630954 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6889.801216,top1_acc,-60.82844689817133 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5297.800704,top1_acc,-52.63656926265686 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2134, 13: 959, 14: 1762, 15: 2312, 16: 1158, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6515.131904,top1_acc,-54.7116568580723 +"OrderedDict([(, {0: 576, 1: 320, 2: 640, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2771, 17: 2797, 18: 2297, 19: 1014, 20: 1261, 21: 1469, 22: 2037, 23: 370})])",MACs,7515.801088,top1_acc,-57.53011877541249 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2275, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 2487, 21: 436, 22: 2037, 23: 370})])",MACs,7372.932608,top1_acc,-59.591867485247874 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 640, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 2297, 19: 1014, 20: 1261, 21: 1469, 22: 348, 23: 1322})])",MACs,5661.394432,top1_acc,-51.87251192358523 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 2275, 15: 1096, 16: 3072, 17: 2797, 18: 2297, 19: 2245, 20: 2487, 21: 928, 22: 348, 23: 799})])",MACs,7424.443904,top1_acc,-57.011767123169385 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2771, 17: 3072, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6670.84544,top1_acc,-57.4317075204954 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 928, 22: 348, 23: 370})])",MACs,5330.175488,top1_acc,-51.265857163760685 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2275, 15: 3072, 16: 3072, 17: 2312, 18: 2297, 19: 2245, 20: 1261, 21: 1469, 22: 348, 23: 370})])",MACs,7452.558848,top1_acc,-59.052091345546444 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 320, 12: 1588, 13: 959, 14: 1762, 15: 2312, 16: 1158, 17: 2312, 18: 1719, 19: 2245, 20: 670, 21: 2187, 22: 814, 23: 799})])",MACs,6505.36704,top1_acc,-54.76439491636352 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1739, 16: 1158, 17: 1062, 18: 3072, 19: 2245, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,5772.0192,top1_acc,-53.71884165342511 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5387.65056,top1_acc,-54.99492780843731 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 640, 4: 640, 5: 768, 6: 768, 7: 576, 8: 512, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2733, 15: 1739, 16: 1158, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 1322})])",MACs,6470.829568,top1_acc,-55.28474752734607 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 2187, 22: 2037, 23: 370})])",MACs,7474.513408,top1_acc,-60.32460132601336 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2733, 15: 1739, 16: 2771, 17: 2312, 18: 1028, 19: 3072, 20: 1261, 21: 436, 22: 814, 23: 1322})])",MACs,6691.48928,top1_acc,-55.21069582827845 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 2733, 15: 2788, 16: 2316, 17: 2797, 18: 2297, 19: 2245, 20: 2487, 21: 436, 22: 814, 23: 799})])",MACs,7529.825792,top1_acc,-57.2872414543731 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 2245, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5181.736448,top1_acc,-49.68948635850979 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 512, 9: 320, 10: 384, 11: 320, 12: 1588, 13: 2685, 14: 2733, 15: 2312, 16: 1788, 17: 2312, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6404.703744,top1_acc,-57.526154597643256 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 1863, 21: 928, 22: 348, 23: 799})])",MACs,5840.17664,top1_acc,-50.9956265936642 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 768, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 2788, 16: 2771, 17: 3072, 18: 3072, 19: 1014, 20: 2487, 21: 436, 22: 2037, 23: 799})])",MACs,7299.073536,top1_acc,-58.64941797290588 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 768, 8: 448, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 1609, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 2297, 19: 2762, 20: 1261, 21: 1469, 22: 348, 23: 1322})])",MACs,6751.847936,top1_acc,-55.50196600183235 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 576, 8: 512, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2275, 15: 1739, 16: 1158, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 1322})])",MACs,6408.04608,top1_acc,-55.77353353156735 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1719, 19: 2245, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5399.381504,top1_acc,-50.52340847713823 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 3072, 19: 2245, 20: 2487, 21: 1469, 22: 814, 23: 799})])",MACs,8425.440768,top1_acc,-59.55860617587142 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,6110.381568,top1_acc,-57.07798240133651 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2275, 15: 1096, 16: 3072, 17: 2312, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,7197.09952,top1_acc,-59.70998520092551 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 928, 22: 348, 23: 370})])",MACs,5924.193792,top1_acc,-56.33929042001022 +"OrderedDict([(, {0: 512, 1: 768, 2: 640, 3: 512, 4: 640, 5: 768, 6: 768, 7: 768, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2275, 15: 1739, 16: 1158, 17: 1062, 18: 3072, 19: 2762, 20: 670, 21: 1469, 22: 2037, 23: 370})])",MACs,7092.831744,top1_acc,-55.72402547619279 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 512, 9: 320, 10: 384, 11: 384, 12: 1588, 13: 2685, 14: 2733, 15: 2312, 16: 2316, 17: 2312, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6651.971072,top1_acc,-56.82065493651185 +"OrderedDict([(, {0: 512, 1: 704, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 1609, 14: 1762, 15: 1096, 16: 1158, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 928, 22: 348, 23: 799})])",MACs,6365.054464,top1_acc,-53.80177942438959 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1739, 16: 2316, 17: 1062, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6294.734336,top1_acc,-56.94075373847854 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 512, 4: 704, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2275, 15: 1096, 16: 3072, 17: 1774, 18: 2297, 19: 2762, 20: 670, 21: 1469, 22: 2037, 23: 370})])",MACs,6839.60064,top1_acc,-57.90158367915327 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 3072, 19: 2762, 20: 2487, 21: 436, 22: 2037, 23: 799})])",MACs,8659.928576,top1_acc,-62.571055947554335 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 1609, 14: 1762, 15: 1096, 16: 2771, 17: 3072, 18: 2797, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6832.195072,top1_acc,-58.631264874319825 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2134, 13: 959, 14: 1762, 15: 2312, 16: 1158, 17: 2312, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6886.065664,top1_acc,-57.799531805516345 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 2297, 19: 1014, 20: 670, 21: 1469, 22: 348, 23: 370})])",MACs,6023.02208,top1_acc,-55.21069582827845 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 1609, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1719, 19: 2245, 20: 670, 21: 2187, 22: 348, 23: 370})])",MACs,5734.073856,top1_acc,-50.7910414966408 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 2297, 19: 2245, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6262.490624,top1_acc,-55.26896422396545 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2275, 15: 1096, 16: 3072, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7130.646016,top1_acc,-57.833231073345246 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7605.192192,top1_acc,-59.57317644481708 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5170.005504,top1_acc,-53.16372091056994 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2312, 18: 2297, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6550.455808,top1_acc,-58.811771770032706 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 2797, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5950.801408,top1_acc,-54.278833816077956 +"OrderedDict([(, {0: 512, 1: 704, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 1609, 14: 2275, 15: 1096, 16: 1158, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 3072, 22: 348, 23: 799})])",MACs,7112.689152,top1_acc,-56.763284101096225 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 2797, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6021.907968,top1_acc,-51.27103010689016 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 3072, 17: 2797, 18: 1028, 19: 2245, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6169.101824,top1_acc,-54.16589932124241 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 1788, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,6516.114944,top1_acc,-58.79759000771466 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5042.60352,top1_acc,-53.65747584120986 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 1609, 14: 2275, 15: 1096, 16: 1158, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 3072, 22: 348, 23: 370})])",MACs,6448.6784,top1_acc,-56.631961518949936 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 1762, 15: 2312, 16: 1158, 17: 1774, 18: 1028, 19: 3072, 20: 3072, 21: 2187, 22: 2037, 23: 799})])",MACs,7074.940416,top1_acc,-56.24034645452709 +"OrderedDict([(, {0: 512, 1: 448, 2: 640, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2275, 15: 1096, 16: 3072, 17: 2312, 18: 2297, 19: 2245, 20: 1261, 21: 1469, 22: 348, 23: 799})])",MACs,7039.354368,top1_acc,-58.04132033917235 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5218.24,top1_acc,-55.15294062595535 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6944.327168,top1_acc,-59.81451281520205 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 640, 4: 640, 5: 640, 6: 768, 7: 768, 8: 448, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 1322})])",MACs,5718.27968,top1_acc,-56.548659976463256 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5334.631936,top1_acc,-53.51348879153569 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7741.507072,top1_acc,-60.82844689817133 +"OrderedDict([(, {0: 576, 1: 768, 2: 640, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 2487, 21: 1469, 22: 2037, 23: 799})])",MACs,9067.431424,top1_acc,-60.81725386037139 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2275, 15: 1739, 16: 2316, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6677.136896,top1_acc,-58.82977917441249 +"OrderedDict([(, {0: 512, 1: 448, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2275, 15: 1096, 16: 3072, 17: 2312, 18: 2297, 19: 2245, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6652.691968,top1_acc,-57.535934835985316 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 320, 10: 384, 11: 320, 12: 1588, 13: 2685, 14: 2733, 15: 2312, 16: 1788, 17: 2312, 18: 2297, 19: 2245, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6903.82592,top1_acc,-57.03980726573153 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 2788, 16: 2316, 17: 1774, 18: 3072, 19: 2245, 20: 2487, 21: 436, 22: 2037, 23: 799})])",MACs,7247.365632,top1_acc,-59.124353911192514 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 2312, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5865.211392,top1_acc,-54.03785768297347 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 2487, 21: 436, 22: 2037, 23: 799})])",MACs,8755.283456,top1_acc,-62.06837048829764 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 2187, 22: 2037, 23: 370})])",MACs,7129.990656,top1_acc,-58.5467058423594 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5315.23328,top1_acc,-53.395013361982755 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6763.382272,top1_acc,-60.06236595789939 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1062, 18: 2297, 19: 2245, 20: 670, 21: 1469, 22: 814, 23: 370})])",MACs,6808.14336,top1_acc,-60.59691562850315 +"OrderedDict([(, {0: 576, 1: 768, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 2297, 19: 2245, 20: 2487, 21: 1469, 22: 348, 23: 799})])",MACs,8249.673216,top1_acc,-60.81922660758651 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 1774, 18: 2797, 19: 1014, 20: 1261, 21: 2187, 22: 2037, 23: 370})])",MACs,6900.22144,top1_acc,-54.473843943581116 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 2245, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5549.393408,top1_acc,-56.57894359264041 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 2297, 19: 1014, 20: 670, 21: 1469, 22: 348, 23: 370})])",MACs,5795.350016,top1_acc,-53.388112595817006 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5580.195328,top1_acc,-56.806289679694025 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2312, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,7155.877376,top1_acc,-59.17933256968625 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 2487, 21: 1469, 22: 2037, 23: 799})])",MACs,9121.957376,top1_acc,-60.566125739927365 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 2275, 15: 2788, 16: 3072, 17: 1774, 18: 2297, 19: 2245, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,7268.402688,top1_acc,-58.320084227297656 +"OrderedDict([(, {0: 512, 1: 448, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 512, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2275, 15: 1096, 16: 3072, 17: 2312, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,6153.569792,top1_acc,-56.773484921502835 +"OrderedDict([(, {0: 576, 1: 768, 2: 640, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 384, 12: 2692, 13: 1609, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 2297, 19: 2762, 20: 2487, 21: 1469, 22: 348, 23: 799})])",MACs,8710.784512,top1_acc,-58.800949377178846 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2275, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6199.576064,top1_acc,-54.690750658701326 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 2312, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7646.152192,top1_acc,-60.82844689817133 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 928, 22: 348, 23: 370})])",MACs,6142.2976,top1_acc,-58.669159833736984 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 2797, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5678.171648,top1_acc,-53.151394575781175 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1739, 16: 2771, 17: 3072, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6797.264384,top1_acc,-59.66820103744048 +"OrderedDict([(, {0: 512, 1: 256, 2: 640, 3: 512, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 2312, 18: 1028, 19: 2245, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,6459.688448,top1_acc,-53.388112595817006 +"OrderedDict([(, {0: 512, 1: 448, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6599.804416,top1_acc,-58.54419516220256 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6021.514752,top1_acc,-57.833231073345246 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4802.348544,top1_acc,-49.661307313831756 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5270.275584,top1_acc,-54.259825608761616 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2134, 13: 1609, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5297.145344,top1_acc,-51.829869936311276 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 1788, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,6642.533888,top1_acc,-59.052309924674326 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1762, 15: 3072, 16: 3072, 17: 1062, 18: 3072, 19: 2762, 20: 2487, 21: 436, 22: 2037, 23: 799})])",MACs,7798.785536,top1_acc,-57.30766020227869 +"OrderedDict([(, {0: 512, 1: 768, 2: 640, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7686.98112,top1_acc,-59.34998758283692 +"OrderedDict([(, {0: 512, 1: 448, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 2312, 18: 2297, 19: 2245, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6275.008,top1_acc,-53.14083843246411 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 2245, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5291.443712,top1_acc,-50.475914996409564 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 928, 22: 814, 23: 370})])",MACs,6206.653952,top1_acc,-56.42446874338215 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2312, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6432.94976,top1_acc,-58.320084227297656 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 1609, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5188.09344,top1_acc,-52.61360919387727 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6607.341056,top1_acc,-60.88262979015748 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 1788, 17: 2797, 18: 2297, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6633.620992,top1_acc,-58.79880120258366 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 2797, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5823.399424,top1_acc,-52.419810709802036 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5827.462656,top1_acc,-57.59775781817433 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5542.97088,top1_acc,-56.75517176765141 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 2797, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5907.613184,top1_acc,-55.23181756655187 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6024.070656,top1_acc,-56.304919157109346 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 640, 4: 640, 5: 640, 6: 768, 7: 768, 8: 512, 9: 320, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 2312, 16: 2316, 17: 2312, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 1322})])",MACs,6436.750848,top1_acc,-58.869698658969924 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,7743.145472,top1_acc,-59.319703754488195 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 1609, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5269.882368,top1_acc,-51.87251192358523 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2275, 15: 1739, 16: 2316, 17: 2312, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6156.38784,top1_acc,-56.516042388622424 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 2245, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5193.532928,top1_acc,-51.803306809459635 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 1788, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6550.91456,top1_acc,-58.79831868448624 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1028, 19: 1014, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,7340.230144,top1_acc,-60.09540363352785 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7865.173504,top1_acc,-60.11053198493792 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5712.05376,top1_acc,-54.226716488854066 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 640, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 1322})])",MACs,6019.876352,top1_acc,-55.54433905906734 +"OrderedDict([(, {0: 512, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 2297, 19: 1014, 20: 2487, 21: 1469, 22: 348, 23: 370})])",MACs,7732.463104,top1_acc,-59.30546484314362 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 928, 22: 348, 23: 370})])",MACs,5266.73664,top1_acc,-53.938782690026166 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 2797, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5521.147392,top1_acc,-57.388262229281274 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 2187, 22: 2037, 23: 370})])",MACs,6837.175808,top1_acc,-58.33150512387887 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,6126.962176,top1_acc,-55.49128082826849 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 1588, 13: 2685, 14: 1110, 15: 1096, 16: 1788, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,5686.232576,top1_acc,-52.877458262390284 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2312, 18: 2297, 19: 2762, 20: 2487, 21: 436, 22: 2037, 23: 370})])",MACs,7467.238912,top1_acc,-58.39395532441031 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 1110, 15: 2788, 16: 2316, 17: 1774, 18: 2297, 19: 2245, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,6808.929792,top1_acc,-59.31328329100475 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5323.0976,top1_acc,-50.62132225102124 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5158.209024,top1_acc,-53.49285081048897 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 2312, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5956.83072,top1_acc,-53.51348879153569 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 2312, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6362.301952,top1_acc,-55.623736875649776 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 3072, 17: 1774, 18: 1028, 19: 1014, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,6160.385536,top1_acc,-56.56296906477638 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6282.937856,top1_acc,-59.56649094312695 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5278.598656,top1_acc,-56.56296906477638 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 2245, 20: 1261, 21: 2187, 22: 2037, 23: 799})])",MACs,7828.145664,top1_acc,-59.56649094312695 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5044.962816,top1_acc,-56.29066123861417 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 512, 9: 320, 10: 384, 11: 320, 12: 1588, 13: 959, 14: 2733, 15: 2312, 16: 2316, 17: 2797, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6455.363072,top1_acc,-57.063556044501475 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7741.507072,top1_acc,-60.82844689817133 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 2733, 15: 2788, 16: 2316, 17: 1774, 18: 3072, 19: 2245, 20: 3072, 21: 436, 22: 348, 23: 799})])",MACs,7449.937408,top1_acc,-58.33150512387887 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5560.927744,top1_acc,-57.03054933279827 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 2685, 14: 2733, 15: 1739, 16: 1788, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6839.141888,top1_acc,-59.56649094312695 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2312, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5926.159872,top1_acc,-57.833231073345246 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 2312, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5988.746752,top1_acc,-54.50362181686306 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2771, 17: 3072, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6402.672128,top1_acc,-57.05114473535801 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5333.58336,top1_acc,-53.4406644277161 +"OrderedDict([(, {0: 576, 1: 320, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 2797, 18: 2297, 19: 2245, 20: 2487, 21: 436, 22: 348, 23: 370})])",MACs,7069.30432,top1_acc,-57.5435670477595 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 2245, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6524.962304,top1_acc,-58.35943612387946 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6971.590144,top1_acc,-60.819133045274 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2245, 20: 2487, 21: 436, 22: 814, 23: 799})])",MACs,6345.590272,top1_acc,-59.30546484314362 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6170.1504,top1_acc,-55.86081818464569 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5115.479552,top1_acc,-54.74865115851942 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5564.59776,top1_acc,-58.631264874319825 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 3072, 19: 1014, 20: 2487, 21: 436, 22: 2037, 23: 370})])",MACs,8190.95296,top1_acc,-59.819513518083454 +"OrderedDict([(, {0: 512, 1: 256, 2: 640, 3: 640, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 3072, 16: 1158, 17: 2797, 18: 2297, 19: 1014, 20: 2487, 21: 1469, 22: 348, 23: 799})])",MACs,7017.793024,top1_acc,-59.32805322494611 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 2797, 18: 3072, 19: 2762, 20: 2487, 21: 2187, 22: 2037, 23: 370})])",MACs,8403.092992,top1_acc,-59.33815828411364 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6364.726784,top1_acc,-60.06707792285204 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 640, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6244.271616,top1_acc,-57.5435670477595 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5837.096448,top1_acc,-55.48848010257114 +"OrderedDict([(, {0: 512, 1: 448, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 2733, 15: 2788, 16: 2316, 17: 1774, 18: 3072, 19: 2245, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,7553.025536,top1_acc,-58.5467058423594 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 1609, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5871.63392,top1_acc,-57.296574949882284 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 2312, 18: 2297, 19: 1014, 20: 670, 21: 1469, 22: 348, 23: 799})])",MACs,7038.305792,top1_acc,-57.388262229281274 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5307.36896,top1_acc,-53.798066544186 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4963.173888,top1_acc,-55.58086597524819 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 1110, 15: 2788, 16: 2316, 17: 1774, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6125.323776,top1_acc,-57.791810761975015 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4815.52128,top1_acc,-53.08567193176762 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5333.124608,top1_acc,-56.29066123861417 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5196.61312,top1_acc,-55.46666671852067 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,7327.712768,top1_acc,-59.14107788502262 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5296.424448,top1_acc,-53.938782690026166 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 2312, 18: 2297, 19: 2245, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6589.449728,top1_acc,-60.072215253513185 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,7731.348992,top1_acc,-59.60380981891474 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5461.181952,top1_acc,-55.982394228103175 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 3072, 16: 3072, 17: 2797, 18: 1028, 19: 2762, 20: 2487, 21: 436, 22: 2037, 23: 370})])",MACs,7669.220864,top1_acc,-56.536047483703555 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5572.593152,top1_acc,-54.485984828394265 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 2797, 18: 2297, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6227.4944,top1_acc,-57.063556044501475 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5517.346304,top1_acc,-56.37833320596455 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5360.846336,top1_acc,-52.62420102371838 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2312, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6514.738688,top1_acc,-57.296574949882284 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 2685, 14: 2733, 15: 1739, 16: 3072, 17: 2312, 18: 3072, 19: 1014, 20: 2487, 21: 436, 22: 814, 23: 799})])",MACs,7580.550656,top1_acc,-60.11053198493792 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 2187, 22: 2037, 23: 370})])",MACs,7038.305792,top1_acc,-59.33815828411364 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 3072, 15: 1739, 16: 1788, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,6518.343168,top1_acc,-58.33150512387887 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 1788, 17: 2312, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7918.519808,top1_acc,-59.36351080219947 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 1609, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,6546.589184,top1_acc,-58.2897151722857 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 1788, 17: 2312, 18: 3072, 19: 1014, 20: 2487, 21: 436, 22: 814, 23: 799})])",MACs,7659.78368,top1_acc,-57.32046470010711 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7642.678784,top1_acc,-61.86174601668025 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 2788, 16: 2316, 17: 2797, 18: 3072, 19: 2245, 20: 2487, 21: 436, 22: 814, 23: 370})])",MACs,7688.160768,top1_acc,-60.06707792285204 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 3072, 19: 2245, 20: 2487, 21: 1469, 22: 348, 23: 799})])",MACs,8565.622272,top1_acc,-60.81922660758651 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 1609, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,6519.326208,top1_acc,-58.79759000771466 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 768, 10: 768, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 2245, 20: 2487, 21: 436, 22: 814, 23: 799})])",MACs,7264.404992,top1_acc,-58.81989399089292 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5030.020608,top1_acc,-51.819177404562986 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6497.895936,top1_acc,-58.79759000771466 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5245.502976,top1_acc,-55.439725452868075 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 640, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 2297, 19: 2245, 20: 670, 21: 1469, 22: 814, 23: 370})])",MACs,7218.136576,top1_acc,-60.56594364604692 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 1609, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6979.19232,top1_acc,-59.56649094312695 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7494.043136,top1_acc,-60.64593797294897 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 1110, 15: 1739, 16: 2316, 17: 1774, 18: 2297, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6174.148096,top1_acc,-56.29066123861417 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 2297, 19: 2762, 20: 2487, 21: 436, 22: 2037, 23: 799})])",MACs,8180.401664,top1_acc,-62.069223130672 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 2312, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,6998.459904,top1_acc,-60.592891861794605 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2312, 18: 2297, 19: 2245, 20: 2487, 21: 1469, 22: 348, 23: 799})])",MACs,7167.28064,top1_acc,-58.03450615832939 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 2312, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6205.277696,top1_acc,-57.30766020227869 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 2797, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,5826.41408,top1_acc,-54.58278835785596 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6580.07808,top1_acc,-60.11053198493792 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5516.166656,top1_acc,-56.49788851042796 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 2312, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6538.593792,top1_acc,-58.04732682978748 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,7038.436864,top1_acc,-59.82632727547974 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 640, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5286.004224,top1_acc,-50.163717805422415 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6059.001344,top1_acc,-58.90456886654597 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 2487, 21: 436, 22: 2037, 23: 799})])",MACs,8148.68224,top1_acc,-58.551086611815464 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 2312, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5431.232,top1_acc,-56.91684038863919 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 2297, 19: 1014, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,7218.333184,top1_acc,-58.344632541408515 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6480.922112,top1_acc,-59.819513518083454 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 2762, 20: 670, 21: 928, 22: 348, 23: 370})])",MACs,5255.9232,top1_acc,-53.9019545585709 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 3072, 19: 2245, 20: 2487, 21: 1469, 22: 348, 23: 799})])",MACs,8265.729536,top1_acc,-60.079161428273785 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 1028, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7159.023104,top1_acc,-58.296380069576934 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5523.96544,top1_acc,-55.528527919647594 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6123.94752,top1_acc,-60.12439770925611 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5653.136896,top1_acc,-57.79057511117575 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 640, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 2312, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6962.742784,top1_acc,-58.157758060789135 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,6430.393856,top1_acc,-57.80903072486336 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5701.89568,top1_acc,-57.174438236555645 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1739, 16: 2316, 17: 1774, 18: 2297, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5647.82848,top1_acc,-57.59775781817433 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 3072, 17: 2797, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6364.268032,top1_acc,-57.799531805516345 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 640, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1062, 18: 3072, 19: 2762, 20: 2487, 21: 436, 22: 348, 23: 370})])",MACs,7206.536704,top1_acc,-58.811771770032706 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 3072, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6604.98176,top1_acc,-58.05514135255713 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1739, 16: 3072, 17: 1062, 18: 1028, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5894.112768,top1_acc,-51.68734231170929 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5340.726784,top1_acc,-53.7031102939668 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2312, 18: 3072, 19: 1014, 20: 2487, 21: 436, 22: 814, 23: 799})])",MACs,7256.147456,top1_acc,-59.33815828411364 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5646.386688,top1_acc,-59.591867485247874 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 3072, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 928, 22: 348, 23: 370})])",MACs,7186.810368,top1_acc,-58.800949377178846 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1110, 15: 3072, 16: 3072, 17: 2312, 18: 3072, 19: 1014, 20: 2487, 21: 436, 22: 2037, 23: 799})])",MACs,7642.74432,top1_acc,-57.864160394400734 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 2297, 19: 2762, 20: 2487, 21: 436, 22: 814, 23: 799})])",MACs,8335.197696,top1_acc,-59.55747684873348 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5388.109312,top1_acc,-55.26896422396545 +"OrderedDict([(, {0: 576, 1: 768, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 3072, 19: 2245, 20: 2487, 21: 1469, 22: 348, 23: 799})])",MACs,8470.13632,top1_acc,-60.31431608368663 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6974.146048,top1_acc,-60.82844689817133 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,5787.026944,top1_acc,-53.49285081048897 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5865.604608,top1_acc,-58.45760203069087 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4907.533824,top1_acc,-53.49285081048897 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,8375.371264,top1_acc,-61.58979909555603 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4960.814592,top1_acc,-53.42661861783563 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 3072, 17: 2312, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,6676.350464,top1_acc,-58.25149539847667 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 640, 4: 640, 5: 768, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5980.358144,top1_acc,-58.64941797290588 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 2797, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,5616.240128,top1_acc,-55.32122564572604 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1739, 16: 1158, 17: 1062, 18: 3072, 19: 2762, 20: 670, 21: 928, 22: 348, 23: 370})])",MACs,5556.536832,top1_acc,-53.700374505592805 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2312, 18: 2297, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6196.03712,top1_acc,-58.12018675459495 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5480.252928,top1_acc,-58.631264874319825 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6511.986176,top1_acc,-60.39307167689609 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 2312, 18: 2297, 19: 2762, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,7563.380224,top1_acc,-59.60380981891474 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5008.918016,top1_acc,-53.08567193176762 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 320, 12: 2692, 13: 1609, 14: 1110, 15: 2788, 16: 2316, 17: 1774, 18: 3072, 19: 2245, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,7043.08992,top1_acc,-58.61472777603488 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 2245, 20: 2487, 21: 436, 22: 2037, 23: 799})])",MACs,7668.499968,top1_acc,-60.35894895952164 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6470.567424,top1_acc,-57.01743615529957 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6634.604032,top1_acc,-60.363441905438464 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 2797, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5620.63104,top1_acc,-56.5965534490769 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1062, 18: 1028, 19: 2245, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5831.394816,top1_acc,-54.94968980251971 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6212.355584,top1_acc,-58.57509882742485 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 640, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 2762, 20: 2487, 21: 436, 22: 814, 23: 799})])",MACs,7432.37376,top1_acc,-57.62564573315502 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 768, 8: 448, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 2797, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5616.502272,top1_acc,-53.40667882909217 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5015.340544,top1_acc,-53.92823485107089 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5203.232256,top1_acc,-53.911905631753044 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1110, 15: 3072, 16: 2316, 17: 1062, 18: 2297, 19: 1014, 20: 670, 21: 1469, 22: 348, 23: 370})])",MACs,6006.769152,top1_acc,-54.473843943581116 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7031.096832,top1_acc,-60.82287537654698 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,7241.00864,top1_acc,-60.363441905438464 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5170.005504,top1_acc,-53.16372091056994 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2312, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,7504.856576,top1_acc,-61.325209769523894 +"OrderedDict([(, {0: 576, 1: 256, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 2297, 19: 1014, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,6998.394368,top1_acc,-58.64941797290588 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2245, 20: 2487, 21: 436, 22: 814, 23: 799})])",MACs,6318.327296,top1_acc,-59.052309924674326 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 448, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5912.462848,top1_acc,-58.57509882742485 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6453.462528,top1_acc,-61.08743288323454 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5015.340544,top1_acc,-53.42661861783563 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 640, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,5695.473152,top1_acc,-55.061208125601105 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2134, 13: 959, 14: 1762, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6507.6608,top1_acc,-59.14107788502262 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5772.0192,top1_acc,-56.79361809424823 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5241.898496,top1_acc,-53.17778138042816 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1110, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6151.210496,top1_acc,-60.139919434750965 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7550.600704,top1_acc,-59.37869861492439 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7360.93952,top1_acc,-60.15706950519473 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5803.345408,top1_acc,-58.669159833736984 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5142.742528,top1_acc,-54.74865115851942 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5691.7376,top1_acc,-57.13110471171509 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6697.780736,top1_acc,-58.31040124744803 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5196.61312,top1_acc,-53.67676459034164 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 3072, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,7688.816128,top1_acc,-59.82632727547974 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6095.832576,top1_acc,-55.20661099098646 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 640, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1739, 16: 3072, 17: 1062, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6686.180864,top1_acc,-56.5965534490769 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6763.382272,top1_acc,-60.06236595789939 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5251.33568,top1_acc,-56.304919157109346 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 2245, 20: 2487, 21: 436, 22: 814, 23: 799})])",MACs,7170.360832,top1_acc,-60.335866942767524 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 2312, 18: 1719, 19: 1014, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,6262.162944,top1_acc,-54.50362181686306 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5735.908864,top1_acc,-57.36888466492201 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6766.331392,top1_acc,-60.56824785510757 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 2487, 21: 436, 22: 2037, 23: 799})])",MACs,8700.757504,top1_acc,-61.58979909555603 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 2245, 20: 2487, 21: 436, 22: 814, 23: 799})])",MACs,6666.126848,top1_acc,-56.548659976463256 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6139.807232,top1_acc,-58.320084227297656 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 2797, 18: 3072, 19: 1014, 20: 2487, 21: 436, 22: 2037, 23: 799})])",MACs,6774.39232,top1_acc,-56.046499517765305 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6524.831232,top1_acc,-59.871070260181426 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5469.89824,top1_acc,-53.980851421647245 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 640, 4: 640, 5: 768, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6103.827968,top1_acc,-59.09585115904812 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 2297, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7855.015424,top1_acc,-61.81942347761422 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2312, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,7184.32,top1_acc,-60.567664902577135 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1739, 16: 2316, 17: 2797, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5476.45184,top1_acc,-55.109144491924724 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 3072, 16: 3072, 17: 2797, 18: 2297, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,7502.038528,top1_acc,-59.591867485247874 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5079.369216,top1_acc,-56.68277832443891 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5114.824192,top1_acc,-55.74138665741355 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4954.392064,top1_acc,-53.34876461854267 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2312, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7629.112832,top1_acc,-61.08743288323454 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6682.510848,top1_acc,-59.319703754488195 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,5695.079936,top1_acc,-53.12017201039245 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2312, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6150.424064,top1_acc,-58.94578624224634 +"OrderedDict([(, {0: 576, 1: 768, 2: 640, 3: 640, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 3072, 19: 2245, 20: 2487, 21: 1469, 22: 2037, 23: 799})])",MACs,8761.378304,top1_acc,-61.06810410474487 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,7151.87968,top1_acc,-59.36351080219947 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5224.531456,top1_acc,-54.4421655829423 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6347.163136,top1_acc,-59.10926879747481 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 2312, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5846.861312,top1_acc,-56.73499023091504 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 2487, 21: 436, 22: 2037, 23: 370})])",MACs,8425.57184,top1_acc,-61.325209769523894 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,8280.016384,top1_acc,-62.100932236102956 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5387.65056,top1_acc,-56.773484921502835 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2312, 18: 2297, 19: 2762, 20: 2487, 21: 436, 22: 2037, 23: 799})])",MACs,8207.66464,top1_acc,-61.569331679601525 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 3072, 16: 1158, 17: 2797, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,6708.20096,top1_acc,-56.01977832642419 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 2312, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,7006.38976,top1_acc,-59.56649094312695 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 2797, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5888.148992,top1_acc,-54.71613867597193 +"OrderedDict([(, {0: 512, 1: 448, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2312, 18: 2297, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6953.829888,top1_acc,-59.591867485247874 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5861.869056,top1_acc,-56.548659976463256 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4692.64128,top1_acc,-47.801701262661275 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1774, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4977.329664,top1_acc,-54.68655257933821 +"OrderedDict([(, {0: 512, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1062, 18: 1028, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,6962.546176,top1_acc,-56.766090665998846 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,7972.3904,top1_acc,-62.341245340663974 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7724.467712,top1_acc,-61.348185195952546 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5005.772288,top1_acc,-54.48788961504227 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5452.989952,top1_acc,-58.37588651574037 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 2797, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5363.664384,top1_acc,-53.34876461854267 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4899.866112,top1_acc,-53.11394546988002 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 2297, 19: 2762, 20: 2487, 21: 436, 22: 2037, 23: 799})])",MACs,8602.912256,top1_acc,-59.81135922805257 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7615.415808,top1_acc,-62.11254337621169 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7633.307136,top1_acc,-60.34053904179437 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1062, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5065.016832,top1_acc,-51.58855550567928 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5333.124608,top1_acc,-56.79361809424823 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 2245, 20: 2487, 21: 1469, 22: 348, 23: 799})])",MACs,8132.691456,top1_acc,-62.581164868039274 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6480.725504,top1_acc,-59.591867485247874 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,7631.865344,top1_acc,-59.591867485247874 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 1719, 19: 2762, 20: 2487, 21: 436, 22: 814, 23: 799})])",MACs,7031.9488,top1_acc,-60.11053198493792 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,6698.960384,top1_acc,-60.88262979015748 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 640, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2134, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,6890.653184,top1_acc,-60.34053904179437 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,8176.797184,top1_acc,-62.31873551222902 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6798.181888,top1_acc,-61.07991646384716 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 2797, 18: 1028, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6599.542272,top1_acc,-55.26896422396545 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6710.625792,top1_acc,-59.41395545037332 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4735.501824,top1_acc,-54.4509467622167 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2312, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7710.90176,top1_acc,-61.09671005868332 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2312, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,7589.201408,top1_acc,-61.325209769523894 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 640, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 3072, 19: 2245, 20: 670, 21: 1469, 22: 348, 23: 370})])",MACs,7483.295232,top1_acc,-61.58197390467447 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1062, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5065.016832,top1_acc,-51.58855550567928 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5030.020608,top1_acc,-51.819177404562986 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6773.671424,top1_acc,-59.07413763612096 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 3072, 16: 1158, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6062.016,top1_acc,-56.37833320596455 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 1062, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5301.536256,top1_acc,-53.21096681799615 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,7112.55808,top1_acc,-59.304527125232084 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1774, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5205.001728,top1_acc,-55.629743503011674 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 640, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7533.62688,top1_acc,-61.6383370327138 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4823.188992,top1_acc,-53.49285081048897 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,7014.123008,top1_acc,-58.2897151722857 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 2797, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5410.522624,top1_acc,-55.10400717227824 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4726.72,top1_acc,-52.98746530730193 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,8095.008256,top1_acc,-62.815498383581584 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7233.734144,top1_acc,-60.63017263508896 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5610.341888,top1_acc,-55.78770438298012 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2312, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,7110.854144,top1_acc,-58.90456886654597 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 2245, 20: 2487, 21: 1469, 22: 348, 23: 799})])",MACs,8159.954432,top1_acc,-62.58978986785575 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6797.00224,top1_acc,-58.33150512387887 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,7330.334208,top1_acc,-61.31894280886927 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6917.91616,top1_acc,-59.92215466535732 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1774, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5320.017408,top1_acc,-54.781790671712 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4870.047232,top1_acc,-53.08567193176762 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5008.262656,top1_acc,-56.548659976463256 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6352.0128,top1_acc,-59.66820103744048 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 2797, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5493.884416,top1_acc,-57.151997763701715 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 1062, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5615.38816,top1_acc,-55.02476813761963 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7211.18976,top1_acc,-60.139919434750965 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6514.54208,top1_acc,-58.39395532441031 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4459.6608,top1_acc,-49.73395495279609 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4776.986112,top1_acc,-47.801701262661275 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6560.024064,top1_acc,-58.54419516220256 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6226.576896,top1_acc,-58.07606001872874 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,5928.846848,top1_acc,-59.07413763612096 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 768, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6748.767744,top1_acc,-58.55730181125508 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 1062, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5432.149504,top1_acc,-55.58086597524819 +"OrderedDict([(, {0: 512, 1: 768, 2: 640, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 1469, 22: 348, 23: 799})])",MACs,7642.482176,top1_acc,-61.57026456344282 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6288.246272,top1_acc,-57.36888466492201 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 512, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1110, 15: 1739, 16: 1158, 17: 1062, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5874.320896,top1_acc,-53.151394575781175 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5081.859584,top1_acc,-57.011767123169385 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 640, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7560.889856,top1_acc,-62.351304129941646 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5017.69984,top1_acc,-54.892506017528355 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,8149.534208,top1_acc,-63.066448105689865 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6027.544064,top1_acc,-57.99504696103684 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5091.362304,top1_acc,-56.01668097291345 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,7558.727168,top1_acc,-58.81989399089292 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4687.332864,top1_acc,-54.01724857356367 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5302.519296,top1_acc,-56.49812173768567 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6634.604032,top1_acc,-61.134806440703215 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7163.217408,top1_acc,-59.55827154899262 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1774, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,5745.673728,top1_acc,-56.75682416159784 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4726.72,top1_acc,-52.09512852126564 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 1719, 19: 2245, 20: 2487, 21: 1469, 22: 348, 23: 799})])",MACs,6672.025088,top1_acc,-58.10381850664859 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 2245, 20: 2487, 21: 436, 22: 348, 23: 799})])",MACs,7847.806464,top1_acc,-62.0844043646687 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5518.198272,top1_acc,-55.77353353156735 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 2312, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6323.17696,top1_acc,-57.78482239390005 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5024.187904,top1_acc,-53.965125501237424 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 448, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6178.473472,top1_acc,-60.37743021259655 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5285.74208,top1_acc,-57.5435670477595 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7588.152832,top1_acc,-61.37218790341886 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,5228.267008,top1_acc,-47.60180026275787 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4849.141248,top1_acc,-53.08567193176762 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6569.788928,top1_acc,-58.296380069576934 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4938.204672,top1_acc,-50.50885375584 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5079.369216,top1_acc,-56.82065493651185 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5360.387584,top1_acc,-56.773484921502835 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 640, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5854.135808,top1_acc,-58.39395532441031 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,7326.664192,top1_acc,-61.672552346682096 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 640, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6103.827968,top1_acc,-59.90351356363471 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6940.919296,top1_acc,-61.569331679601525 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5175.96928,top1_acc,-56.00481335616141 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 2312, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6566.118912,top1_acc,-61.074192279472896 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 2245, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6652.036608,top1_acc,-60.566125739927365 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 640, 4: 640, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1110, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6926.370304,top1_acc,-60.616057621372846 +"OrderedDict([(, {0: 512, 1: 448, 2: 640, 3: 640, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 768, 10: 768, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 2487, 21: 1469, 22: 348, 23: 370})])",MACs,6443.828736,top1_acc,-52.12174394953254 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4665.378304,top1_acc,-48.33402215116177 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 640, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 768, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6336.808448,top1_acc,-58.841395412761074 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 640, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 768, 10: 768, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 3072, 19: 2245, 20: 2487, 21: 436, 22: 348, 23: 370})])",MACs,6923.224576,top1_acc,-59.14107788502262 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 640, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7260.99712,top1_acc,-59.66820103744048 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1062, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6447.433216,top1_acc,-56.76052483913692 +"OrderedDict([(, {0: 576, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6972.442112,top1_acc,-63.3176717769807 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1062, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5319.49312,top1_acc,-54.43521169935567 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,7473.792512,top1_acc,-62.567409296993745 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4827.31776,top1_acc,-55.528527919647594 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4959.70048,top1_acc,-52.85368344613508 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 2297, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5742.069248,top1_acc,-56.25095574827523 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1774, 18: 2297, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5205.001728,top1_acc,-54.747134231033016 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 2245, 20: 2487, 21: 1469, 22: 348, 23: 370})])",MACs,7526.09024,top1_acc,-58.79831868448624 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6071.8464,top1_acc,-60.616057621372846 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5364.0576,top1_acc,-57.882074372510814 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4432.397824,top1_acc,-49.23279883713507 +"OrderedDict([(, {0: 576, 1: 320, 2: 640, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1062, 18: 1719, 19: 1014, 20: 1261, 21: 1469, 22: 348, 23: 799})])",MACs,6522.471936,top1_acc,-57.565840039155525 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5780.145664,top1_acc,-58.82977917441249 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 640, 4: 640, 5: 768, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 2797, 18: 1028, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6212.290048,top1_acc,-55.26838482765232 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5636.752896,top1_acc,-50.1912506520387 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 1739, 16: 2316, 17: 2797, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6041.830912,top1_acc,-56.37833320596455 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2312, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6368.527872,top1_acc,-60.39307167689609 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4877.714944,top1_acc,-53.05886020670072 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 2797, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5064.820224,top1_acc,-55.26838482765232 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4735.501824,top1_acc,-53.755256301159704 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 640, 4: 640, 5: 640, 6: 768, 7: 768, 8: 448, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6812.337664,top1_acc,-59.08413057707468 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6707.807744,top1_acc,-60.8558135506955 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 640, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7677.085184,top1_acc,-61.86174601668025 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,7239.304704,top1_acc,-60.576676853873344 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6127.945216,top1_acc,-57.01743615529957 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,8350.664192,top1_acc,-61.09671005868332 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 2797, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5258.741248,top1_acc,-57.09406887467645 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6913.65632,top1_acc,-60.15706950519473 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4762.7648,top1_acc,-54.46151814563016 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 640, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,7174.292992,top1_acc,-61.6383370327138 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4660.069888,top1_acc,-53.23002583628187 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6293.227008,top1_acc,-59.55747684873348 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 640, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5902.697984,top1_acc,-59.124353911192514 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 640, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 1762, 15: 1739, 16: 3072, 17: 1062, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,7028.868608,top1_acc,-58.41361508452911 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 2797, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,7815.955968,top1_acc,-61.58197390467447 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2312, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6596.331008,top1_acc,-60.39307167689609 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 2297, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6494.619136,top1_acc,-57.791810761975015 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6496.323072,top1_acc,-60.56594364604692 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4893.050368,top1_acc,-49.97185526543391 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5963.646464,top1_acc,-59.845263312315645 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5551.949312,top1_acc,-53.16372091056994 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 640, 4: 640, 5: 768, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5317.592576,top1_acc,-55.009007320050095 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,7653.88544,top1_acc,-62.82530013172366 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4486.923776,top1_acc,-49.77212766483547 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,8122.271232,top1_acc,-62.56796544244645 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1110, 15: 1739, 16: 3072, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5073.995264,top1_acc,-53.32198659134496 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 1158, 17: 2797, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6372.394496,top1_acc,-58.12018675459495 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,7904.167424,top1_acc,-62.626964805823185 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5479.990784,top1_acc,-57.279168863510776 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,7049.31584,top1_acc,-60.8358147712731 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6480.922112,top1_acc,-58.29211024374039 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 1158, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,7029.98272,top1_acc,-59.30546484314362 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5548.279296,top1_acc,-58.43483922385055 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 1158, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6434.194944,top1_acc,-59.90351356363471 +"OrderedDict([(, {0: 576, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1762, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6645.220864,top1_acc,-60.64593797294897 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6017.320448,top1_acc,-60.63017263508896 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6913.65632,top1_acc,-62.06837048829764 +"OrderedDict([(, {0: 576, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 2788, 16: 1158, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,6428.68992,top1_acc,-58.33150512387887 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2771, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5429.26592,top1_acc,-57.32046470010711 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6879.970816,top1_acc,-59.82632727547974 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5725.48864,top1_acc,-55.52849676135797 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,5222.565376,top1_acc,-52.74611768595587 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 512, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,7392.986624,top1_acc,-62.601411843965934 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 2312, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 814, 23: 799})])",MACs,5994.51392,top1_acc,-56.27810283916928 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5828.05248,top1_acc,-58.33150512387887 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,4943.513088,top1_acc,-55.80354863452468 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1774, 18: 2297, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5518.001664,top1_acc,-56.01977832642419 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,5807.343104,top1_acc,-58.39395532441031 +"OrderedDict([(, {0: 576, 1: 704, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 1158, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6209.537536,top1_acc,-59.07413763612096 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6152.652288,top1_acc,-59.30837029344534 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5231.67488,top1_acc,-54.278833816077956 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5721.032192,top1_acc,-60.139919434750965 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5448.402432,top1_acc,-58.138175837447115 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5456.13568,top1_acc,-57.14877134063284 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 2312, 16: 2316, 17: 1062, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 814, 23: 799})])",MACs,6173.623808,top1_acc,-58.320084227297656 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,4824.892928,top1_acc,-53.7031102939668 +"OrderedDict([(, {0: 576, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 768, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,7142.04928,top1_acc,-59.08413057707468 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4820.829696,top1_acc,-51.537427784188935 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,5988.222464,top1_acc,-58.08909972587557 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4599.645696,top1_acc,-51.421533289518976 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 640, 4: 640, 5: 768, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6746.801664,top1_acc,-61.85029155864712 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6290.08128,top1_acc,-58.886326969667344 +"OrderedDict([(, {0: 512, 1: 448, 2: 640, 3: 640, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 2312, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6764.23424,top1_acc,-60.06707792285204 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6828.983808,top1_acc,-63.814106686714545 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6099.109376,top1_acc,-61.10771753348959 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6823.151104,top1_acc,-59.305518684780765 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6537.938432,top1_acc,-62.570012821477505 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 320, 12: 2134, 13: 959, 14: 1110, 15: 3072, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5415.437824,top1_acc,-49.92198958165368 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6406.211072,top1_acc,-60.072215253513185 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4571.268608,top1_acc,-49.52437657124396 +"OrderedDict([(, {0: 576, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1110, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5947.393536,top1_acc,-58.35943612387946 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4963.173888,top1_acc,-56.5965534490769 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5609.358848,top1_acc,-57.90158367915327 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5004.59264,top1_acc,-52.38644265545665 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6742.803968,top1_acc,-61.074192279472896 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,4878.960128,top1_acc,-54.03785768297347 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5258.479104,top1_acc,-57.535934835985316 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,7047.415296,top1_acc,-59.834921155466205 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 768, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5934.417408,top1_acc,-55.49749054428224 +"OrderedDict([(, {0: 576, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6903.82592,top1_acc,-60.079161428273785 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,7435.781632,top1_acc,-61.82197264087645 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 640, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 2312, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6692.603392,top1_acc,-61.58197390467447 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,7011.30496,top1_acc,-62.11254337621169 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5336.794624,top1_acc,-57.882074372510814 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6463.882752,top1_acc,-61.134806440703215 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4944.823808,top1_acc,-52.86178863044644 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5776.213504,top1_acc,-58.59983483284835 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,5978.4576,top1_acc,-60.175821153228526 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,4630.38208,top1_acc,-50.53968650343078 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,4830.791168,top1_acc,-53.535697224275516 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 640, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5929.96096,top1_acc,-57.833231073345246 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,7833.1264,top1_acc,-61.82318665058879 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5336.794624,top1_acc,-58.9687102846644 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5395.777024,top1_acc,-55.48273578107759 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5854.59456,top1_acc,-58.85471185335819 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4769.121792,top1_acc,-53.47381322825221 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6999.705088,top1_acc,-62.82530013172366 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5436.605952,top1_acc,-53.642149379322326 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6005.720576,top1_acc,-60.139919434750965 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6142.821888,top1_acc,-59.455541946478164 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,4963.763712,top1_acc,-53.379999660538225 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4854.580736,top1_acc,-54.50362181686306 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5457.577472,top1_acc,-55.93209709812511 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,4657.645056,top1_acc,-50.27162727680555 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,5873.27232,top1_acc,-54.71613867597193 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5109.646848,top1_acc,-55.50196600183235 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6347.556352,top1_acc,-59.55747684873348 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6371.6736,top1_acc,-60.363441905438464 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6044.583424,top1_acc,-59.92215466535732 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,5616.502272,top1_acc,-57.279168863510776 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4708.238848,top1_acc,-54.50362181686306 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6166.414848,top1_acc,-59.581646002674226 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5313.005056,top1_acc,-56.079904783944286 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4935.910912,top1_acc,-56.35758105599825 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,4851.697152,top1_acc,-54.01724857356367 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5969.479168,top1_acc,-59.31314229261737 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4792.58368,top1_acc,-54.50362181686306 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5825.889792,top1_acc,-57.833231073345246 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4790.027776,top1_acc,-53.965125501237424 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6153.635328,top1_acc,-61.07991646384716 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6235.35872,top1_acc,-57.76533213099373 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5393.87648,top1_acc,-58.157758060789135 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5133.69856,top1_acc,-55.00793243102087 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5849.548288,top1_acc,-57.799531805516345 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6338.57792,top1_acc,-59.60380981891474 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5562.304,top1_acc,-55.840134871210765 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,4548.593152,top1_acc,-49.98659010492951 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6756.04224,top1_acc,-60.817272939320674 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 2797, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4828.038656,top1_acc,-53.559447186425814 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5700.91264,top1_acc,-58.344632541408515 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6625.822208,top1_acc,-61.623674908457446 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5452.989952,top1_acc,-58.37588651574037 +"OrderedDict([(, {0: 576, 1: 704, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1062, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5919.606272,top1_acc,-60.08475155631261 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 2797, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5501.224448,top1_acc,-55.788273514772705 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5738.399232,top1_acc,-59.834921155466205 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4819.846656,top1_acc,-54.01724857356367 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2771, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6406.604288,top1_acc,-61.134806440703215 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1739, 16: 1158, 17: 1062, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5051.647488,top1_acc,-51.564120146882274 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6482.626048,top1_acc,-60.11053198493792 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6329.533952,top1_acc,-60.37743021259655 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5258.479104,top1_acc,-56.5965534490769 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,4657.645056,top1_acc,-49.668820567172006 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,4632.937984,top1_acc,-49.73395495279609 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6031.672832,top1_acc,-60.34053904179437 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 640, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 1110, 15: 3072, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5811.01312,top1_acc,-54.76439491636352 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5391.451648,top1_acc,-56.49788851042796 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 2692, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6549.538304,top1_acc,-56.85434392735081 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5507.515904,top1_acc,-58.37588651574037 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 3072, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5273.748992,top1_acc,-53.013123482343694 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6171.198976,top1_acc,-60.567664902577135 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 2797, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5395.056128,top1_acc,-56.29066123861417 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5258.020352,top1_acc,-57.62564573315502 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4946.003456,top1_acc,-56.49788851042796 +"OrderedDict([(, {0: 576, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 1788, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6692.734464,top1_acc,-59.81451281520205 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5252.580864,top1_acc,-55.47527490659778 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5619.123712,top1_acc,-58.43483922385055 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4642.375168,top1_acc,-52.98746530730193 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6332.548608,top1_acc,-61.33109050075183 +"OrderedDict([(, {0: 576, 1: 256, 2: 640, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 768, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1062, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5535.041024,top1_acc,-52.59770638545269 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4826.203648,top1_acc,-54.29943706677067 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5892.802048,top1_acc,-58.631264874319825 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6801.720832,top1_acc,-64.05767700619003 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 1158, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6425.41312,top1_acc,-60.079161428273785 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5194.057216,top1_acc,-57.30766020227869 +"OrderedDict([(, {0: 512, 1: 448, 2: 640, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4926.342656,top1_acc,-51.28707947122957 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,5999.887872,top1_acc,-58.41361508452911 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1062, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5802.231296,top1_acc,-57.52407929937235 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5837.22752,top1_acc,-59.17933256968625 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 640, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 768, 11: 320, 12: 2692, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6695.552512,top1_acc,-60.34053904179437 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5933.827584,top1_acc,-60.32460132601336 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 512, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 2797, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5920.13056,top1_acc,-57.688653433060985 +"OrderedDict([(, {0: 512, 1: 704, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6639.584768,top1_acc,-59.561622728650995 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,4827.448832,top1_acc,-53.965125501237424 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5090.77248,top1_acc,-54.9719450045872 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5876.811264,top1_acc,-58.71330527374325 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4823.188992,top1_acc,-53.32198659134496 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6223.955456,top1_acc,-58.31040124744803 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6344.541696,top1_acc,-62.56673855627156 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5881.857536,top1_acc,-59.37869861492439 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5482.808832,top1_acc,-58.14477644432363 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5188.42112,top1_acc,-56.06238208505129 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5133.895168,top1_acc,-55.15294062595535 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5782.701568,top1_acc,-58.841395412761074 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,4776.265216,top1_acc,-53.980851421647245 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2771, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6761.022976,top1_acc,-62.31873551222902 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,4950.459904,top1_acc,-51.62458987125488 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6391.00672,top1_acc,-59.857322945429026 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4800.054784,top1_acc,-55.49128082826849 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5695.66976,top1_acc,-54.71613867597193 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6293.0304,top1_acc,-59.07413763612096 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4377.871872,top1_acc,-49.816788996099575 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6942.230016,top1_acc,-60.72497164582199 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5366.613504,top1_acc,-59.503255638976974 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1762, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6102.844928,top1_acc,-60.37743021259655 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6662.850048,top1_acc,-61.59937744560633 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6248.203776,top1_acc,-61.33109050075183 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5891.753472,top1_acc,-58.811771770032706 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5050.79552,top1_acc,-52.505969227479746 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5089.46176,top1_acc,-57.52407929937235 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5626.070528,top1_acc,-58.64941797290588 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6780.880384,top1_acc,-61.23085786668939 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,5249.69728,top1_acc,-54.950939208938166 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5102.044672,top1_acc,-54.892506017528355 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4683.990528,top1_acc,-51.15526483965838 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6195.70944,top1_acc,-60.12439770925611 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5619.582464,top1_acc,-58.54419516220256 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1110, 15: 3072, 16: 3072, 17: 1062, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6369.904128,top1_acc,-58.811771770032706 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4959.962624,top1_acc,-50.0030526422662 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,5944.0512,top1_acc,-60.12439770925611 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4735.501824,top1_acc,-54.4509467622167 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6062.933504,top1_acc,-61.31894280886927 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4572.38272,top1_acc,-51.11154619148318 +"OrderedDict([(, {0: 512, 1: 704, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6965.298688,top1_acc,-61.35933777663026 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5393.87648,top1_acc,-58.25149539847667 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6082.070016,top1_acc,-60.12439770925611 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5118.035456,top1_acc,-54.74865115851942 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2771, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6270.354944,top1_acc,-59.834921155466205 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6831.212032,top1_acc,-59.124353911192514 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,5484.97152,top1_acc,-52.703091982567194 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6774.457856,top1_acc,-61.59937744560633 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5765.662208,top1_acc,-60.35113508865858 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5245.502976,top1_acc,-56.079904783944286 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6421.48096,top1_acc,-61.82197264087645 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 1158, 17: 1062, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6021.645824,top1_acc,-55.46831669515506 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5728.175616,top1_acc,-58.344632541408515 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6225.52832,top1_acc,-59.41395545037332 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,5216.470528,top1_acc,-56.046499517765305 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5524.882944,top1_acc,-57.279168863510776 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 768, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 3072, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,7353.927168,top1_acc,-63.142677068873375 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 2316, 17: 1062, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5035.72224,top1_acc,-53.40667882909217 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,5808.195072,top1_acc,-59.561622728650995 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6589.777408,top1_acc,-60.8358147712731 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5225.44896,top1_acc,-56.245532335716454 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4820.305408,top1_acc,-53.67676459034164 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4699.457024,top1_acc,-53.250686993557785 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5419.042304,top1_acc,-56.85434392735081 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 3072, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5904.991744,top1_acc,-60.39307167689609 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4894.16448,top1_acc,-57.33495702281163 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6621.69344,top1_acc,-59.39552264856284 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5611.980288,top1_acc,-58.586615151475115 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 1158, 17: 1062, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5841.749504,top1_acc,-57.011767123169385 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5488.313856,top1_acc,-54.76439491636352 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 799})])",MACs,6236.079616,top1_acc,-62.0774050860113 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5057.611264,top1_acc,-57.52407929937235 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2771, 17: 1774, 18: 1719, 19: 2762, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,5997.856256,top1_acc,-59.591867485247874 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6751.716864,top1_acc,-61.85029155864712 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6828.983808,top1_acc,-61.57593279004692 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5002.561024,top1_acc,-57.07798240133651 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 2762, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6349.39136,top1_acc,-60.37743021259655 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6099.961344,top1_acc,-59.857322945429026 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6176.37632,top1_acc,-61.35933777663026 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5711.136256,top1_acc,-58.201595634177764 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,5972.362752,top1_acc,-58.03487303998695 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6000.477696,top1_acc,-61.33109050075183 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5364.0576,top1_acc,-58.737658665959614 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6762.137088,top1_acc,-62.32638366157678 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5230.757376,top1_acc,-56.63656369027515 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5300.225536,top1_acc,-56.046499517765305 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5819.401728,top1_acc,-59.64966623441297 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6415.123968,top1_acc,-61.40286859373326 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4738.51648,top1_acc,-53.95109128667313 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5173.67552,top1_acc,-57.36888466492201 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,5550.114304,top1_acc,-57.833231073345246 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 799})])",MACs,5512.758784,top1_acc,-59.20081056690501 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 3072, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5932.25472,top1_acc,-60.39307167689609 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4963.173888,top1_acc,-56.5965534490769 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,5852.169728,top1_acc,-61.06810410474487 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 370})])",MACs,4733.994496,top1_acc,-52.94768861655004 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5251.139072,top1_acc,-56.836682972278005 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,5070.587392,top1_acc,-51.324792963612886 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4790.027776,top1_acc,-53.45640705889373 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 448, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5881.988608,top1_acc,-56.046499517765305 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6089.934336,top1_acc,-62.56673855627156 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6149.113344,top1_acc,-61.348185195952546 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4711.253504,top1_acc,-53.19354120310512 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 370})])",MACs,6364.399104,top1_acc,-61.57593279004692 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5196.809728,top1_acc,-57.07798240133651 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6018.172416,top1_acc,-60.079161428273785 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6171.723264,top1_acc,-61.81875257246454 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4993.45152,top1_acc,-55.50196600183235 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5255.005696,top1_acc,-59.01906662198131 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5530.19136,top1_acc,-58.10381850664859 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4792.58368,top1_acc,-54.50362181686306 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5905.253888,top1_acc,-59.10926879747481 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4979.164672,top1_acc,-55.02476813761963 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4973.266432,top1_acc,-57.52407929937235 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4517.856768,top1_acc,-51.909383850845 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5654.0544,top1_acc,-59.834921155466205 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 799})])",MACs,6240.732672,top1_acc,-61.09671005868332 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4654.171648,top1_acc,-53.95109128667313 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 799})])",MACs,6218.843648,top1_acc,-57.791810761975015 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6917.91616,top1_acc,-63.08143863677894 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 2037, 23: 799})])",MACs,6312.887808,top1_acc,-57.5435670477595 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6342.313472,top1_acc,-60.34053904179437 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4462.216704,top1_acc,-49.816788996099575 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4735.960576,top1_acc,-53.666219888905495 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6469.64992,top1_acc,-63.81004342223774 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,5797.643776,top1_acc,-59.09585115904812 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 3072, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5045.22496,top1_acc,-54.98256238592481 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5955.716608,top1_acc,-60.616057621372846 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 3072, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6157.501952,top1_acc,-60.84494723188813 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5814.748672,top1_acc,-59.617442948065225 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6144.460288,top1_acc,-61.81999490554073 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6258.165248,top1_acc,-61.31862438295605 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4893.050368,top1_acc,-53.27292010480984 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 799})])",MACs,5661.394432,top1_acc,-59.632737797139356 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5554.898432,top1_acc,-59.07413763612096 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4587.849216,top1_acc,-52.76996324917579 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5500.37248,top1_acc,-59.33815828411364 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5221.18912,top1_acc,-57.01789905913004 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5510.596096,top1_acc,-57.90158367915327 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,5124.654592,top1_acc,-54.278833816077956 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4714.59584,top1_acc,-52.65067723079826 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1062, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5925.111296,top1_acc,-57.2739655014278 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,5031.200256,top1_acc,-51.31045571647604 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5393.87648,top1_acc,-58.157758060789135 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5248.452096,top1_acc,-56.26231409496051 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 799})])",MACs,6092.097024,top1_acc,-60.576676853873344 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6309.217792,top1_acc,-59.871070260181426 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 1158, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6077.285888,top1_acc,-57.52407929937235 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6195.906048,top1_acc,-61.06988552195535 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5520.295424,top1_acc,-58.669159833736984 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4948.690432,top1_acc,-57.03980726573153 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 3072, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5771.232768,top1_acc,-58.307266222770615 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 3072, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5297.145344,top1_acc,-58.33150512387887 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1739, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,5379.655168,top1_acc,-55.22294868395369 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6385.960448,top1_acc,-59.4786450396496 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5500.634624,top1_acc,-57.26811598747922 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4432.397824,top1_acc,-50.598502511711494 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5617.092096,top1_acc,-60.567664902577135 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5711.136256,top1_acc,-59.88647643057969 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 384, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6638.142976,top1_acc,-61.87489151157926 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1762, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4587.849216,top1_acc,-52.45973684146213 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,6325.011968,top1_acc,-61.56883886202732 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5393.87648,top1_acc,-58.25149539847667 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5085.005312,top1_acc,-57.33495702281163 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 3072, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5233.509888,top1_acc,-54.94767866076017 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 1158, 17: 1062, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 370})])",MACs,6146.55744,top1_acc,-56.245532335716454 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 799})])",MACs,5309.859328,top1_acc,-55.10400717227824 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,5762.713088,top1_acc,-58.82977917441249 +"OrderedDict([(, {0: 512, 1: 256, 2: 768, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 768, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5978.719744,top1_acc,-58.811771770032706 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5084.54656,top1_acc,-59.617442948065225 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6610.88,top1_acc,-61.37218790341886 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 448, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,4494.0672,top1_acc,-50.309391622695664 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 1158, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,4656.727552,top1_acc,-51.37796232907349 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6399.067648,top1_acc,-62.072425022140784 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,6096.029184,top1_acc,-59.88647643057969 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6060.115456,top1_acc,-61.82318665058879 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5428.807168,top1_acc,-57.92266130251226 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 3072, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5033.035264,top1_acc,-57.03980726573153 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1739, 16: 2771, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5580.391936,top1_acc,-59.55827154899262 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5426.251264,top1_acc,-57.90158367915327 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 348, 23: 370})])",MACs,6176.310784,top1_acc,-61.81875257246454 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5864.621568,top1_acc,-57.799531805516345 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 799})])",MACs,5448.861184,top1_acc,-59.561622728650995 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6005.589504,top1_acc,-62.56673855627156 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,5562.566144,top1_acc,-59.834921155466205 +"OrderedDict([(, {0: 512, 1: 256, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 1158, 17: 1062, 18: 1028, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,4806.01856,top1_acc,-54.690750658701326 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 1096, 16: 2316, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 814, 23: 799})])",MACs,5676.33664,top1_acc,-59.32805322494611 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 2788, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 670, 21: 436, 22: 348, 23: 370})])",MACs,6004.278784,top1_acc,-60.819133045274 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 448, 4: 640, 5: 640, 6: 768, 7: 576, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 1110, 15: 1096, 16: 2771, 17: 1774, 18: 1719, 19: 1014, 20: 1261, 21: 436, 22: 814, 23: 370})])",MACs,5451.286016,top1_acc,-58.05514135255713 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 11: 320, 12: 949, 13: 959, 14: 2733, 15: 3072, 16: 3072, 17: 1774, 18: 3072, 19: 1014, 20: 670, 21: 436, 22: 2037, 23: 799})])",MACs,6747.19488,top1_acc,-61.40286859373326 +"OrderedDict([(, {0: 512, 1: 704, 2: 320, 3: 448, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 256, 10: 384, 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+1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7dcfcc29406016efee99b21c55a55ec1915d43fecbec62e603b3126702f3403e +size 961 diff --git a/eftnas-s1-bert-base-mnli/README.md b/eftnas-s1-bert-base-mnli/README.md new file mode 100644 index 0000000000000000000000000000000000000000..2a260467cdcfeeb2569c8aa72801d9ef0b11525c --- /dev/null +++ b/eftnas-s1-bert-base-mnli/README.md @@ -0,0 +1,84 @@ +--- +language: +- en +license: apache-2.0 +tags: +- generated_from_trainer +datasets: +- glue +metrics: +- accuracy +model-index: +- name: first_try + results: + - task: + name: Text Classification + type: text-classification + dataset: + name: GLUE MNLI + type: glue + config: mnli + split: validation_matched + args: mnli + metrics: + - name: Accuracy + type: accuracy + value: 0.8417412530512612 +--- + + + +# first_try + +This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE MNLI dataset. +It achieves the following results on the evaluation set: +- Loss: 0.4506 +- Accuracy: 0.8417 + +## Model description + +More information needed + +## Intended uses & limitations + +More information needed + +## Training and evaluation data + +More information needed + +## Training procedure + +### Training hyperparameters + +The following hyperparameters were used during training: +- learning_rate: 2e-05 +- train_batch_size: 32 +- eval_batch_size: 128 +- seed: 42 +- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 +- lr_scheduler_type: linear +- num_epochs: 6 +- mixed_precision_training: Native AMP + +### Training results + +| Training Loss | Epoch | Step | Validation Loss | Accuracy | | +|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| +| 0.3038 | 1.0 | 12272 | 0.4950 | 0.8238 | OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 128, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})]) | +| 0.3038 | 1.0 | 12272 | 0.4592 | 0.8385 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.1683 | 2.0 | 24544 | 0.4678 | 0.8326 | OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 128, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})]) | +| 0.1683 | 2.0 | 24544 | 0.4285 | 0.8479 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.1132 | 3.0 | 36816 | 0.4638 | 0.8381 | OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 128, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})]) | +| 0.1132 | 3.0 | 36816 | 0.4231 | 0.8492 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0894 | 4.0 | 49088 | 0.4678 | 0.8383 | OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 128, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})]) | +| 0.0894 | 4.0 | 49088 | 0.4261 | 0.8497 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | + + +### Framework versions + +- Transformers 4.29.1 +- Pytorch 1.12.1 +- Datasets 2.13.1 +- Tokenizers 0.13.3 diff --git a/eftnas-s1-bert-base-mnli/all_results.json b/eftnas-s1-bert-base-mnli/all_results.json new file mode 100644 index 0000000000000000000000000000000000000000..d7610709c3b03ef966a1541f89fc0b85873b7578 --- /dev/null +++ b/eftnas-s1-bert-base-mnli/all_results.json @@ -0,0 +1,21 @@ +{ + "epoch": 4.0, + "epoch_mm": 4.0, + "eval_accuracy": 0.8382068262862965, + "eval_accuracy_mm": 0.8417412530512612, + "eval_loss": 0.4647368788719177, + "eval_loss_mm": 0.4505881071090698, + "eval_runtime": 6.7365, + "eval_runtime_mm": 6.425, + "eval_samples": 9815, + "eval_samples_mm": 9832, + "eval_samples_per_second": 1456.986, + 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"46 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"47 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" -> "51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"56 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"324 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"330 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"333 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"334 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"339 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"340 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"342 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"343 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"347 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"348 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "359 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"359 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "361 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"361 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "362 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"362 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "363 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"363 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"364 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"365 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "367 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"367 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"370 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"371 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "373 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"373 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"374 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"375 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "377 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"377 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"380 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"381 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "393 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"383 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"384 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "386 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"386 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "387 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"387 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "395 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"388 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"389 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "391 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"391 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "392 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"392 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"393 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "394 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"394 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"395 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "397 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"397 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "398 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"398 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "399 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"399 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "400 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"400 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "402 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"402 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "403 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"403 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "404 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"404 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"405 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"406 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "408 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"408 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"411 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"412 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "414 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"414 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"415 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"416 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "418 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"418 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"421 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"422 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "434 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"424 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"425 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "427 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"427 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "428 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"428 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "436 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"429 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"430 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "432 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"432 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "433 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"433 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"434 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "435 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"435 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"436 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "438 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"438 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "439 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"439 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "440 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"440 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "441 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"441 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "443 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"443 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "444 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"444 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "445 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"445 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"446 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"447 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "449 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"449 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"452 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"453 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "455 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"455 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"456 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"457 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "459 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"459 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" -> "461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "491 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"462 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"463 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "475 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"465 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"466 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "468 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"468 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "469 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"469 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "477 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"42 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "43 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"43 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"44 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "46 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"46 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"47 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "52 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"52 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "53 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"53 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "56 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"56 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "311 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0000000000000000000000000000000000000000..2309ef60e241efd2af98b63bf2abfa6712f4e316 --- /dev/null +++ b/eftnas-s1-bert-base-mnli/search_progression.csv @@ -0,0 +1,1000 @@ +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 128, 7: 512, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 2606, 15: 2589, 16: 2564, 17: 3072, 18: 2438, 19: 2318, 20: 2969, 21: 3072, 22: 345, 23: 3072})])",MACs,8052.47616,top1_acc,-84.35048395313297 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 512, 4: 192, 5: 768, 6: 128, 7: 512, 8: 256, 9: 768, 10: 192, 11: 256, 12: 2448, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 1790, 18: 2438, 19: 2985, 20: 3072, 21: 2664, 22: 1988, 23: 1040})])",MACs,8383.629568,top1_acc,-84.381049414162 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 768, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2527, 18: 1678, 19: 2318, 20: 2969, 21: 1277, 22: 692, 23: 1040})])",MACs,6564.350208,top1_acc,-84.09577177789099 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 2606, 15: 2589, 16: 3024, 17: 2527, 18: 2438, 19: 2985, 20: 3072, 21: 3072, 22: 345, 23: 213})])",MACs,7975.14368,top1_acc,-84.68670402445237 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 768, 5: 576, 6: 128, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 1542, 13: 3032, 14: 3038, 15: 2589, 16: 2564, 17: 3072, 18: 2438, 19: 1544, 20: 2969, 21: 3072, 22: 692, 23: 3072})])",MACs,8496.679168,top1_acc,-84.4727457972491 +"OrderedDict([(, {0: 256, 1: 768, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 768, 8: 768, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 3072, 15: 1877, 16: 3072, 17: 3072, 18: 2438, 19: 2985, 20: 2035, 21: 2664, 22: 692, 23: 1040})])",MACs,7558.465792,top1_acc,-84.37086092715231 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 320, 4: 640, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 2589, 16: 2564, 17: 2527, 18: 3072, 19: 1544, 20: 1223, 21: 2664, 22: 692, 23: 3072})])",MACs,8064.796928,top1_acc,-84.71726948548141 +"OrderedDict([(, {0: 256, 1: 320, 2: 384, 3: 768, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 1611, 14: 3038, 15: 2589, 16: 3024, 17: 2994, 18: 1678, 19: 2318, 20: 2969, 21: 628, 22: 692, 23: 1040})])",MACs,7252.478208,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 512, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 2606, 15: 3072, 16: 2564, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 3072, 22: 3072, 23: 213})])",MACs,8186.104064,top1_acc,-84.73764645950077 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 3026, 16: 3024, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,9131.264256,top1_acc,-84.92103922567499 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 320, 4: 640, 5: 576, 6: 128, 7: 768, 8: 640, 9: 256, 10: 768, 11: 256, 12: 3044, 13: 1611, 14: 3038, 15: 3072, 16: 3072, 17: 2994, 18: 1678, 19: 1544, 20: 2969, 21: 2664, 22: 692, 23: 213})])",MACs,7900.367104,top1_acc,-84.0346408558329 +"OrderedDict([(, {0: 256, 1: 320, 2: 384, 3: 512, 4: 768, 5: 768, 6: 128, 7: 768, 8: 256, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 1611, 14: 3072, 15: 1877, 16: 3072, 17: 2994, 18: 1678, 19: 2985, 20: 2035, 21: 1277, 22: 3072, 23: 213})])",MACs,8054.311168,top1_acc,-84.70708099847172 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 320, 4: 192, 5: 384, 6: 768, 7: 512, 8: 640, 9: 768, 10: 768, 11: 256, 12: 1542, 13: 1611, 14: 3038, 15: 2589, 16: 3024, 17: 3072, 18: 2438, 19: 2985, 20: 2969, 21: 628, 22: 3072, 23: 408})])",MACs,8000.178432,top1_acc,-84.48293428425879 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 512, 4: 640, 5: 384, 6: 576, 7: 512, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 3072, 16: 3072, 17: 2527, 18: 1678, 19: 2985, 20: 1223, 21: 2664, 22: 1988, 23: 3072})])",MACs,8721.9264,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 768, 4: 640, 5: 768, 6: 576, 7: 256, 8: 768, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 3032, 14: 1891, 15: 3072, 16: 2564, 17: 2994, 18: 2438, 19: 3072, 20: 2035, 21: 1277, 22: 1988, 23: 213})])",MACs,8012.761344,top1_acc,-84.66632705043301 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 768, 7: 512, 8: 768, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 2438, 19: 2318, 20: 3072, 21: 3072, 22: 692, 23: 3072})])",MACs,8393.394432,top1_acc,-84.65613856342333 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 320, 4: 768, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 768, 11: 768, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 2318, 20: 2035, 21: 1277, 22: 1988, 23: 1040})])",MACs,7172.589824,top1_acc,-84.20784513499746 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 768, 4: 768, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 3026, 16: 3024, 17: 1790, 18: 1678, 19: 2318, 20: 2969, 21: 3072, 22: 3072, 23: 3072})])",MACs,9072.347392,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 128, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7649.298688,top1_acc,-84.82934284258788 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 768, 4: 640, 5: 576, 6: 576, 7: 256, 8: 768, 9: 768, 10: 768, 11: 768, 12: 1542, 13: 1611, 14: 3038, 15: 2589, 16: 3072, 17: 1790, 18: 1678, 19: 2318, 20: 3072, 21: 3072, 22: 692, 23: 1040})])",MACs,7988.513024,top1_acc,-84.28935303107488 +"OrderedDict([(, {0: 768, 1: 320, 2: 256, 3: 768, 4: 640, 5: 768, 6: 128, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 3072, 21: 3072, 22: 1988, 23: 1040})])",MACs,7984.843008,top1_acc,-84.33010697911361 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 192, 5: 768, 6: 576, 7: 768, 8: 256, 9: 768, 10: 192, 11: 256, 12: 3044, 13: 3032, 14: 1891, 15: 3026, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 408})])",MACs,6799.362304,top1_acc,-84.1874681609781 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 768, 4: 640, 5: 768, 6: 128, 7: 512, 8: 256, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 3026, 16: 3072, 17: 2527, 18: 2438, 19: 3072, 20: 2035, 21: 2664, 22: 3072, 23: 3072})])",MACs,9100.593408,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 256, 12: 3072, 13: 3072, 14: 3072, 15: 2589, 16: 3072, 17: 3072, 18: 3002, 19: 2985, 20: 3072, 21: 3072, 22: 1988, 23: 3072})])",MACs,9935.587584,top1_acc,-84.87009679062659 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 320, 4: 768, 5: 384, 6: 128, 7: 512, 8: 768, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 1877, 16: 3024, 17: 2527, 18: 2438, 19: 2318, 20: 2035, 21: 628, 22: 692, 23: 1040})])",MACs,7459.04768,top1_acc,-84.54406520631686 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 640, 5: 576, 6: 768, 7: 256, 8: 256, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1611, 14: 2606, 15: 3026, 16: 3072, 17: 2994, 18: 3072, 19: 2318, 20: 1223, 21: 1277, 22: 1988, 23: 1040})])",MACs,7657.883904,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 768, 1: 320, 2: 256, 3: 768, 4: 192, 5: 576, 6: 576, 7: 512, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 2589, 16: 3024, 17: 2994, 18: 3002, 19: 1544, 20: 3072, 21: 628, 22: 692, 23: 408})])",MACs,7540.246784,top1_acc,-84.64595007641365 +"OrderedDict([(, {0: 256, 1: 768, 2: 256, 3: 768, 4: 640, 5: 768, 6: 576, 7: 512, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 3072, 14: 3038, 15: 3026, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 3072, 21: 3072, 22: 692, 23: 3072})])",MACs,8984.791296,top1_acc,-84.87009679062659 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 768, 4: 640, 5: 768, 6: 576, 7: 512, 8: 256, 9: 768, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 2985, 20: 2035, 21: 3072, 22: 1988, 23: 3072})])",MACs,8742.89792,top1_acc,-84.71726948548141 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 512, 4: 640, 5: 384, 6: 768, 7: 256, 8: 768, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 3038, 15: 2589, 16: 1825, 17: 2527, 18: 2438, 19: 2318, 20: 2035, 21: 1277, 22: 692, 23: 3072})])",MACs,7554.140416,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 768, 5: 576, 6: 768, 7: 768, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 3072, 19: 3072, 20: 2969, 21: 628, 22: 692, 23: 408})])",MACs,7812.876544,top1_acc,-84.71726948548141 +"OrderedDict([(, {0: 256, 1: 768, 2: 384, 3: 768, 4: 768, 5: 576, 6: 768, 7: 512, 8: 640, 9: 256, 10: 192, 11: 768, 12: 1542, 13: 3032, 14: 3038, 15: 3072, 16: 3072, 17: 2994, 18: 1678, 19: 3072, 20: 2035, 21: 3072, 22: 692, 23: 408})])",MACs,8283.359488,top1_acc,-84.66632705043301 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 512, 4: 768, 5: 384, 6: 768, 7: 768, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 3026, 16: 2564, 17: 2527, 18: 3002, 19: 2318, 20: 3072, 21: 628, 22: 345, 23: 1040})])",MACs,7632.521472,top1_acc,-84.73764645950077 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 2606, 15: 3026, 16: 3024, 17: 1790, 18: 3072, 19: 2985, 20: 3072, 21: 2664, 22: 692, 23: 213})])",MACs,8383.236352,top1_acc,-84.75802343352012 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 192, 5: 576, 6: 768, 7: 512, 8: 768, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 2589, 16: 1825, 17: 2994, 18: 3072, 19: 2318, 20: 2969, 21: 1277, 22: 1988, 23: 213})])",MACs,7720.143104,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 320, 4: 640, 5: 576, 6: 576, 7: 256, 8: 640, 9: 768, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 3038, 15: 2589, 16: 1825, 17: 1790, 18: 2438, 19: 3072, 20: 2969, 21: 3072, 22: 692, 23: 1040})])",MACs,7743.539456,top1_acc,-84.25878757004584 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 512, 4: 640, 5: 576, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 2606, 15: 3072, 16: 3072, 17: 2994, 18: 3002, 19: 1544, 20: 3072, 21: 1277, 22: 692, 23: 1040})])",MACs,8017.74208,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 256, 1: 768, 2: 192, 3: 768, 4: 768, 5: 576, 6: 128, 7: 256, 8: 768, 9: 768, 10: 768, 11: 256, 12: 3044, 13: 3072, 14: 1891, 15: 2589, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 2969, 21: 628, 22: 692, 23: 213})])",MACs,7366.9696,top1_acc,-84.27916454406521 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 768, 4: 768, 5: 576, 6: 128, 7: 768, 8: 640, 9: 256, 10: 768, 11: 768, 12: 2448, 13: 1611, 14: 2606, 15: 3026, 16: 3072, 17: 2527, 18: 3072, 19: 3072, 20: 3072, 21: 1277, 22: 345, 23: 1040})])",MACs,8422.75456,top1_acc,-84.45236882322975 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 768, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 692, 23: 213})])",MACs,7237.20832,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3072, 19: 1544, 20: 1223, 21: 2664, 22: 692, 23: 3072})])",MACs,8709.277952,top1_acc,-85.03311258278146 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 768, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 1611, 14: 3072, 15: 2589, 16: 3072, 17: 3072, 18: 3002, 19: 2985, 20: 2969, 21: 3072, 22: 1988, 23: 3072})])",MACs,9491.777792,top1_acc,-84.66632705043301 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 512, 4: 640, 5: 576, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 3072, 16: 3072, 17: 2527, 18: 3072, 19: 2985, 20: 2969, 21: 2664, 22: 1988, 23: 3072})])",MACs,9639.168256,top1_acc,-84.77840040753948 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 576, 6: 768, 7: 768, 8: 256, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 1611, 14: 2606, 15: 3026, 16: 3072, 17: 2994, 18: 3072, 19: 2318, 20: 3072, 21: 1277, 22: 1988, 23: 1040})])",MACs,8457.619712,top1_acc,-84.69689251146205 +"OrderedDict([(, {0: 768, 1: 320, 2: 256, 3: 768, 4: 640, 5: 768, 6: 128, 7: 768, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 3038, 15: 3026, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 3072, 21: 3072, 22: 1988, 23: 1040})])",MACs,8406.04288,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 640, 9: 768, 10: 768, 11: 256, 12: 1542, 13: 1611, 14: 3038, 15: 2589, 16: 3024, 17: 2527, 18: 2438, 19: 2985, 20: 2969, 21: 628, 22: 3072, 23: 408})])",MACs,8247.44576,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 192, 5: 576, 6: 768, 7: 256, 8: 768, 9: 768, 10: 768, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2527, 18: 2438, 19: 2318, 20: 2969, 21: 3072, 22: 692, 23: 1040})])",MACs,7366.576384,top1_acc,-83.88181355068772 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 512, 4: 640, 5: 576, 6: 768, 7: 256, 8: 768, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 3038, 15: 2589, 16: 1825, 17: 2527, 18: 2438, 19: 1544, 20: 2035, 21: 1277, 22: 1988, 23: 3072})])",MACs,7738.55872,top1_acc,-84.4727457972491 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 768, 8: 768, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 3072, 15: 1877, 16: 3072, 17: 3072, 18: 2438, 19: 2985, 20: 1223, 21: 2664, 22: 692, 23: 1040})])",MACs,7180.716288,top1_acc,-84.28935303107488 +"OrderedDict([(, {0: 768, 1: 320, 2: 192, 3: 768, 4: 192, 5: 576, 6: 576, 7: 512, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 2589, 16: 3024, 17: 2994, 18: 3002, 19: 2318, 20: 3072, 21: 628, 22: 692, 23: 1040})])",MACs,7789.414656,top1_acc,-84.68670402445237 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 128, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 3072, 14: 3072, 15: 1877, 16: 3024, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7747.602688,top1_acc,-84.61538461538461 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 640, 5: 576, 6: 768, 7: 256, 8: 256, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3026, 16: 3072, 17: 2994, 18: 3072, 19: 2985, 20: 3072, 21: 3072, 22: 1988, 23: 1040})])",MACs,9102.428416,top1_acc,-84.55425369332654 +"OrderedDict([(, {0: 768, 1: 320, 2: 256, 3: 320, 4: 640, 5: 576, 6: 576, 7: 768, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 2589, 16: 2564, 17: 2527, 18: 3072, 19: 1544, 20: 3072, 21: 2664, 22: 692, 23: 1040})])",MACs,8083.343616,top1_acc,-84.69689251146205 +"OrderedDict([(, {0: 256, 1: 768, 2: 384, 3: 768, 4: 768, 5: 576, 6: 768, 7: 512, 8: 640, 9: 256, 10: 768, 11: 768, 12: 1542, 13: 3032, 14: 3038, 15: 3072, 16: 3024, 17: 2994, 18: 1678, 19: 3072, 20: 2035, 21: 628, 22: 3072, 23: 408})])",MACs,8506.706176,top1_acc,-84.80896586856852 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 768, 4: 640, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 3032, 14: 3038, 15: 3072, 16: 3072, 17: 2527, 18: 2438, 19: 2985, 20: 1223, 21: 2664, 22: 1988, 23: 3072})])",MACs,9081.587968,top1_acc,-84.95160468670403 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 768, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 3026, 16: 2564, 17: 2527, 18: 3002, 19: 2318, 20: 3072, 21: 3072, 22: 692, 23: 1040})])",MACs,9053.669632,top1_acc,-84.90066225165563 +"OrderedDict([(, {0: 256, 1: 320, 2: 384, 3: 768, 4: 640, 5: 768, 6: 576, 7: 512, 8: 256, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 1611, 14: 3038, 15: 2589, 16: 3024, 17: 2994, 18: 1678, 19: 2318, 20: 3072, 21: 628, 22: 692, 23: 1040})])",MACs,7736.199424,top1_acc,-84.53387671930719 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 3026, 16: 3024, 17: 2527, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8486.783232,top1_acc,-84.80896586856852 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 320, 4: 192, 5: 384, 6: 768, 7: 512, 8: 768, 9: 256, 10: 768, 11: 256, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 3024, 17: 2994, 18: 1678, 19: 2318, 20: 3072, 21: 628, 22: 692, 23: 1040})])",MACs,7696.288,top1_acc,-84.4727457972491 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 408})])",MACs,6895.634688,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 768, 1: 768, 2: 192, 3: 512, 4: 640, 5: 576, 6: 768, 7: 256, 8: 768, 9: 320, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 2606, 15: 3072, 16: 3072, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 1040})])",MACs,7218.006272,top1_acc,-84.31991849210392 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 192, 5: 768, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 1891, 15: 2589, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 408})])",MACs,6378.162432,top1_acc,-84.17727967396841 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 512, 4: 192, 5: 384, 6: 768, 7: 512, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 3026, 16: 2564, 17: 3072, 18: 3002, 19: 2318, 20: 3072, 21: 628, 22: 345, 23: 1040})])",MACs,7385.254144,top1_acc,-84.45236882322975 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 3038, 15: 2589, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 2969, 21: 1277, 22: 692, 23: 1040})])",MACs,6941.31328,top1_acc,-84.36067244014264 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 192, 5: 384, 6: 768, 7: 512, 8: 768, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 2589, 16: 1825, 17: 2994, 18: 3072, 19: 2318, 20: 2969, 21: 1277, 22: 692, 23: 213})])",MACs,7383.550208,top1_acc,-84.65613856342333 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 512, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 2606, 15: 3072, 16: 2564, 17: 1790, 18: 3002, 19: 3072, 20: 2035, 21: 3072, 22: 3072, 23: 213})])",MACs,8563.853568,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 768, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2527, 18: 1678, 19: 1544, 20: 2969, 21: 1277, 22: 692, 23: 408})])",MACs,6315.182336,top1_acc,-84.00407539480386 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 3038, 15: 3026, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,9032.960256,top1_acc,-84.99235863474274 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 256, 12: 3072, 13: 1611, 14: 2606, 15: 2589, 16: 3072, 17: 3072, 18: 3002, 19: 2318, 20: 1223, 21: 1277, 22: 1988, 23: 3072})])",MACs,8491.043072,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 768, 4: 768, 5: 576, 6: 128, 7: 512, 8: 640, 9: 256, 10: 768, 11: 768, 12: 2448, 13: 1611, 14: 2606, 15: 3026, 16: 3072, 17: 2527, 18: 3072, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 3072})])",MACs,8404.207872,top1_acc,-84.37086092715231 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 320, 4: 192, 5: 384, 6: 768, 7: 512, 8: 640, 9: 768, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 3038, 15: 2589, 16: 3072, 17: 3072, 18: 2438, 19: 2985, 20: 2969, 21: 3072, 22: 692, 23: 408})])",MACs,7776.831744,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 512, 4: 640, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 1891, 15: 3072, 16: 2564, 17: 2994, 18: 1678, 19: 3072, 20: 2035, 21: 1277, 22: 1988, 23: 213})])",MACs,7653.099776,top1_acc,-84.63576158940397 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 512, 4: 640, 5: 576, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 3038, 15: 2589, 16: 3072, 17: 1790, 18: 1678, 19: 2318, 20: 3072, 21: 628, 22: 345, 23: 1040})])",MACs,6567.364864,top1_acc,-84.27916454406521 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 2606, 15: 3026, 16: 3024, 17: 1790, 18: 3072, 19: 2985, 20: 2969, 21: 2664, 22: 692, 23: 213})])",MACs,7899.515136,top1_acc,-84.37086092715231 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 320, 4: 768, 5: 576, 6: 768, 7: 768, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 3026, 16: 1825, 17: 3072, 18: 3072, 19: 2318, 20: 2969, 21: 628, 22: 692, 23: 408})])",MACs,7831.750912,top1_acc,-84.81915435557819 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 1891, 15: 3026, 16: 3024, 17: 1790, 18: 2438, 19: 2985, 20: 2035, 21: 2664, 22: 692, 23: 213})])",MACs,8268.548352,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 512, 4: 768, 5: 384, 6: 768, 7: 768, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 2527, 18: 3002, 19: 3072, 20: 3072, 21: 628, 22: 345, 23: 1040})])",MACs,7613.647104,top1_acc,-84.64595007641365 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 768, 6: 576, 7: 512, 8: 256, 9: 768, 10: 192, 11: 256, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 1790, 18: 3072, 19: 1544, 20: 3072, 21: 1277, 22: 345, 23: 408})])",MACs,6914.050304,top1_acc,-84.11614875191034 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 320, 4: 640, 5: 576, 6: 576, 7: 256, 8: 768, 9: 768, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 3038, 15: 2589, 16: 1825, 17: 3072, 18: 2438, 19: 3072, 20: 2969, 21: 3072, 22: 692, 23: 1040})])",MACs,8050.116864,top1_acc,-84.381049414162 +"OrderedDict([(, {0: 256, 1: 768, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 768, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 3072, 15: 1877, 16: 3072, 17: 1790, 18: 2438, 19: 2985, 20: 2035, 21: 2664, 22: 692, 23: 1040})])",MACs,7251.888384,top1_acc,-84.17727967396841 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 640, 5: 768, 6: 768, 7: 256, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 2589, 16: 2564, 17: 2527, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7430.473984,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 768, 1: 320, 2: 192, 3: 768, 4: 768, 5: 576, 6: 576, 7: 512, 8: 768, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 3072, 15: 2589, 16: 3024, 17: 2994, 18: 3002, 19: 3072, 20: 3072, 21: 628, 22: 692, 23: 1040})])",MACs,8401.12768,top1_acc,-84.75802343352012 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 3026, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9522.44864,top1_acc,-85.0127356087621 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 512, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 1877, 16: 3024, 17: 2994, 18: 2438, 19: 2318, 20: 2035, 21: 628, 22: 1988, 23: 1040})])",MACs,8078.297344,top1_acc,-84.72745797249108 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 3038, 15: 3072, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,9232.845056,top1_acc,-84.89047376464595 +"OrderedDict([(, {0: 256, 1: 768, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 1542, 13: 3072, 14: 1891, 15: 1877, 16: 3024, 17: 2527, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7665.682688,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 192, 5: 768, 6: 576, 7: 256, 8: 256, 9: 768, 10: 768, 11: 256, 12: 2448, 13: 3032, 14: 1891, 15: 2589, 16: 1825, 17: 2527, 18: 2438, 19: 1544, 20: 2035, 21: 1277, 22: 692, 23: 408})])",MACs,7000.230144,top1_acc,-84.29954151808457 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 768, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,7250.774272,top1_acc,-84.60519612837494 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 768, 4: 640, 5: 384, 6: 576, 7: 512, 8: 256, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 3032, 14: 3038, 15: 3026, 16: 3072, 17: 2527, 18: 3072, 19: 1544, 20: 1223, 21: 2664, 22: 1988, 23: 408})])",MACs,8281.065728,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 640, 5: 576, 6: 768, 7: 512, 8: 768, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 2589, 16: 1825, 17: 2994, 18: 3072, 19: 2318, 20: 3072, 21: 1277, 22: 692, 23: 1040})])",MACs,7839.025408,top1_acc,-84.79877738155885 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 408})])",MACs,7768.04992,top1_acc,-84.82934284258788 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 192, 5: 768, 6: 576, 7: 768, 8: 256, 9: 768, 10: 192, 11: 256, 12: 3044, 13: 3032, 14: 1891, 15: 2589, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 408})])",MACs,6713.444608,top1_acc,-84.19765664798777 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 320, 4: 640, 5: 768, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 3038, 15: 3026, 16: 3072, 17: 2994, 18: 3002, 19: 2318, 20: 3072, 21: 3072, 22: 692, 23: 3072})])",MACs,8861.649152,top1_acc,-84.74783494651045 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 2318, 20: 2035, 21: 628, 22: 1988, 23: 1040})])",MACs,7349.27488,top1_acc,-84.4218033622007 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 192, 5: 576, 6: 768, 7: 256, 8: 768, 9: 256, 10: 768, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 2318, 20: 2969, 21: 1277, 22: 692, 23: 1040})])",MACs,6575.163648,top1_acc,-84.01426388181356 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 3038, 15: 3026, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 3072, 21: 3072, 22: 345, 23: 1040})])",MACs,9971.435776,top1_acc,-84.91085073866532 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 192, 5: 384, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 256, 12: 3044, 13: 1611, 14: 1891, 15: 2589, 16: 1825, 17: 2527, 18: 3072, 19: 2318, 20: 2969, 21: 1277, 22: 692, 23: 408})])",MACs,7571.11424,top1_acc,-84.29954151808457 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 768, 4: 640, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 3072, 14: 1891, 15: 3072, 16: 3072, 17: 2994, 18: 2438, 19: 3072, 20: 2035, 21: 2664, 22: 1988, 23: 3072})])",MACs,9091.614976,top1_acc,-84.79877738155885 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 3038, 15: 2589, 16: 3024, 17: 3072, 18: 1678, 19: 2318, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,6574.442752,top1_acc,-84.381049414162 +"OrderedDict([(, {0: 768, 1: 320, 2: 256, 3: 320, 4: 192, 5: 384, 6: 768, 7: 512, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 2994, 18: 3072, 19: 1544, 20: 2969, 21: 2664, 22: 692, 23: 3072})])",MACs,7593.986304,top1_acc,-84.24859908303617 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 512, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 2318, 20: 1223, 21: 628, 22: 692, 23: 408})])",MACs,6283.921664,top1_acc,-84.16709118695873 +"OrderedDict([(, {0: 256, 1: 768, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 3072, 15: 1877, 16: 3024, 17: 1790, 18: 2438, 19: 2985, 20: 2035, 21: 1277, 22: 692, 23: 1040})])",MACs,6860.704,top1_acc,-84.21803362200713 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 320, 4: 640, 5: 768, 6: 128, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 1891, 15: 3072, 16: 2564, 17: 2527, 18: 1678, 19: 3072, 20: 2035, 21: 1277, 22: 692, 23: 213})])",MACs,7033.850112,top1_acc,-84.29954151808457 +"OrderedDict([(, {0: 256, 1: 768, 2: 384, 3: 320, 4: 768, 5: 576, 6: 768, 7: 512, 8: 640, 9: 256, 10: 768, 11: 768, 12: 1542, 13: 3032, 14: 3038, 15: 3026, 16: 3024, 17: 2994, 18: 1678, 19: 3072, 20: 2035, 21: 628, 22: 3072, 23: 408})])",MACs,8306.821376,top1_acc,-84.53387671930719 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 320, 4: 768, 5: 576, 6: 576, 7: 768, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 3072, 15: 3026, 16: 3072, 17: 3072, 18: 2438, 19: 2985, 20: 2035, 21: 2664, 22: 692, 23: 1040})])",MACs,8379.566336,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2318, 20: 2969, 21: 1277, 22: 345, 23: 1040})])",MACs,5942.282496,top1_acc,-83.9429444727458 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 320, 4: 768, 5: 576, 6: 128, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7635.732736,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 768, 6: 576, 7: 256, 8: 768, 9: 768, 10: 192, 11: 256, 12: 3044, 13: 3032, 14: 2606, 15: 3072, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 3072, 21: 1277, 22: 345, 23: 3072})])",MACs,7714.572544,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 512, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 3038, 15: 2589, 16: 3072, 17: 1790, 18: 1678, 19: 2318, 20: 2969, 21: 628, 22: 345, 23: 213})])",MACs,6111.889664,top1_acc,-84.05501782985226 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 768, 4: 640, 5: 384, 6: 128, 7: 512, 8: 256, 9: 768, 10: 768, 11: 768, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,7118.457088,top1_acc,-84.30973000509424 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 192, 5: 768, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 1891, 15: 3026, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 408})])",MACs,6464.080128,top1_acc,-84.14671421293937 +"OrderedDict([(, {0: 256, 1: 768, 2: 384, 3: 768, 4: 768, 5: 576, 6: 768, 7: 768, 8: 256, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 1891, 15: 3026, 16: 1825, 17: 3072, 18: 3072, 19: 3072, 20: 2969, 21: 628, 22: 692, 23: 408})])",MACs,7954.893056,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 512, 4: 192, 5: 384, 6: 768, 7: 256, 8: 640, 9: 256, 10: 768, 11: 256, 12: 1542, 13: 2465, 14: 1891, 15: 3026, 16: 1825, 17: 3072, 18: 3002, 19: 2318, 20: 3072, 21: 1277, 22: 345, 23: 1040})])",MACs,7208.569088,top1_acc,-84.41161487519103 +"OrderedDict([(, {0: 256, 1: 768, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 768, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 3072, 15: 1877, 16: 3072, 17: 2527, 18: 2438, 19: 2985, 20: 2035, 21: 2664, 22: 692, 23: 1040})])",MACs,7547.652352,top1_acc,-84.41161487519103 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 3026, 16: 2564, 17: 2527, 18: 3002, 19: 2318, 20: 2035, 21: 1277, 22: 692, 23: 1040})])",MACs,8115.194112,top1_acc,-84.71726948548141 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 2969, 21: 1277, 22: 692, 23: 213})])",MACs,6127.618304,top1_acc,-84.06520631686195 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 512, 4: 640, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3038, 15: 3072, 16: 2564, 17: 2527, 18: 1678, 19: 2985, 20: 1223, 21: 1277, 22: 1988, 23: 213})])",MACs,7643.072768,top1_acc,-84.67651553744268 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 768, 4: 768, 5: 384, 6: 576, 7: 512, 8: 640, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 3072, 20: 2969, 21: 628, 22: 692, 23: 408})])",MACs,7573.670144,top1_acc,-84.49312277126847 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 3026, 16: 3024, 17: 2527, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8759.478528,top1_acc,-84.87009679062659 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 768, 4: 640, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 3032, 14: 3038, 15: 3072, 16: 3072, 17: 2527, 18: 2438, 19: 2985, 20: 1223, 21: 1277, 22: 1988, 23: 3072})])",MACs,8808.892672,top1_acc,-84.82934284258788 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 320, 4: 192, 5: 768, 6: 576, 7: 256, 8: 640, 9: 320, 10: 768, 11: 256, 12: 2448, 13: 3032, 14: 1891, 15: 2589, 16: 1825, 17: 2527, 18: 3072, 19: 1544, 20: 2969, 21: 1277, 22: 692, 23: 408})])",MACs,7117.670656,top1_acc,-84.10596026490066 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,5906.893056,top1_acc,-84.05501782985226 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 3072, 15: 2589, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 408})])",MACs,6855.723264,top1_acc,-84.36067244014264 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3072, 19: 1544, 20: 2035, 21: 2664, 22: 692, 23: 3072})])",MACs,8868.923648,top1_acc,-84.84971981660723 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 640, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 2465, 14: 3038, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 408})])",MACs,7225.936128,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 512, 4: 192, 5: 576, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 2465, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 1678, 19: 2318, 20: 3072, 21: 628, 22: 345, 23: 1040})])",MACs,6726.617344,top1_acc,-84.17727967396841 +"OrderedDict([(, {0: 768, 1: 320, 2: 256, 3: 768, 4: 640, 5: 576, 6: 576, 7: 512, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 3072, 16: 3072, 17: 2994, 18: 3002, 19: 2985, 20: 3072, 21: 628, 22: 1988, 23: 408})])",MACs,8373.60256,top1_acc,-84.75802343352012 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 768, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 2589, 16: 2564, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 692, 23: 213})])",MACs,7649.822976,top1_acc,-84.61538461538461 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 768, 4: 192, 5: 768, 6: 576, 7: 768, 8: 256, 9: 768, 10: 192, 11: 256, 12: 3044, 13: 3032, 14: 1891, 15: 3026, 16: 1825, 17: 2527, 18: 2438, 19: 2985, 20: 2035, 21: 1277, 22: 1988, 23: 3072})])",MACs,8265.206016,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 192, 5: 768, 6: 768, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 1891, 15: 3026, 16: 2564, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 408})])",MACs,6909.266176,top1_acc,-84.21803362200713 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 640, 5: 768, 6: 768, 7: 256, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 3026, 16: 2564, 17: 2527, 18: 1678, 19: 3072, 20: 1223, 21: 2664, 22: 692, 23: 408})])",MACs,8587.643136,top1_acc,-84.83953132959755 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 192, 5: 576, 6: 768, 7: 768, 8: 640, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 3072, 19: 3072, 20: 2969, 21: 628, 22: 692, 23: 408})])",MACs,7198.279936,top1_acc,-84.14671421293937 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 320, 4: 640, 5: 576, 6: 576, 7: 256, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 1611, 14: 1891, 15: 2589, 16: 3024, 17: 2527, 18: 3002, 19: 3072, 20: 2969, 21: 1277, 22: 345, 23: 1040})])",MACs,7915.571456,top1_acc,-84.56444218033621 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 768, 4: 768, 5: 384, 6: 576, 7: 512, 8: 256, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 3038, 15: 1877, 16: 3024, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 692, 23: 213})])",MACs,7848.790272,top1_acc,-84.73764645950077 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 768, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 692, 23: 213})])",MACs,7035.160832,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 192, 5: 768, 6: 768, 7: 256, 8: 768, 9: 256, 10: 768, 11: 256, 12: 2448, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 2527, 18: 1678, 19: 1544, 20: 2969, 21: 1277, 22: 692, 23: 408})])",MACs,6758.14016,top1_acc,-84.20784513499746 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 576, 6: 768, 7: 768, 8: 256, 9: 768, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 3026, 16: 1825, 17: 3072, 18: 2438, 19: 2318, 20: 2035, 21: 628, 22: 692, 23: 408})])",MACs,7714.3104,top1_acc,-84.78858889454915 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 3026, 16: 3024, 17: 2527, 18: 3002, 19: 2318, 20: 2969, 21: 2664, 22: 345, 23: 1040})])",MACs,8794.867968,top1_acc,-84.81915435557819 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 576, 6: 128, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7171.737856,top1_acc,-84.33010697911361 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7608.404224,top1_acc,-84.84971981660723 +"OrderedDict([(, {0: 256, 1: 320, 2: 384, 3: 768, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 2606, 15: 2589, 16: 3024, 17: 2994, 18: 1678, 19: 2318, 20: 2969, 21: 628, 22: 692, 23: 1040})])",MACs,6922.176768,top1_acc,-84.20784513499746 +"OrderedDict([(, {0: 256, 1: 256, 2: 384, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 3038, 15: 2589, 16: 3024, 17: 2527, 18: 1678, 19: 2318, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,6544.754944,top1_acc,-84.2384105960265 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 768, 4: 192, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 3032, 14: 3038, 15: 2589, 16: 3024, 17: 2527, 18: 2438, 19: 1544, 20: 1223, 21: 2664, 22: 692, 23: 3072})])",MACs,8248.232192,top1_acc,-84.56444218033621 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 2969, 21: 1277, 22: 692, 23: 1040})])",MACs,6528.698624,top1_acc,-84.22822210901681 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 3032, 14: 3038, 15: 3026, 16: 3072, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 2664, 22: 692, 23: 408})])",MACs,7674.923264,top1_acc,-84.5236882322975 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 3038, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8587.774208,top1_acc,-84.90066225165563 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8365.279488,top1_acc,-84.92103922567499 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 2318, 20: 2969, 21: 1277, 22: 345, 23: 1040})])",MACs,6556.879104,top1_acc,-84.2384105960265 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 3072, 14: 3038, 15: 3026, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 2035, 21: 2664, 22: 692, 23: 1040})])",MACs,7785.220352,top1_acc,-84.4727457972491 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 640, 5: 384, 6: 128, 7: 256, 8: 768, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 2527, 18: 2438, 19: 2318, 20: 2035, 21: 628, 22: 345, 23: 1040})])",MACs,6861.03168,top1_acc,-84.22822210901681 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 128, 7: 512, 8: 640, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7851.346176,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 768, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 2589, 16: 1825, 17: 2527, 18: 2438, 19: 1544, 20: 2035, 21: 1277, 22: 692, 23: 408})])",MACs,6557.27232,top1_acc,-84.01426388181356 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 320, 4: 768, 5: 576, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 3026, 16: 1825, 17: 3072, 18: 3072, 19: 2318, 20: 2969, 21: 1277, 22: 1988, 23: 408})])",MACs,8432.25728,top1_acc,-84.70708099847172 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 768, 4: 640, 5: 768, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 2589, 16: 2564, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 408})])",MACs,7909.28,top1_acc,-84.61538461538461 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 512, 4: 768, 5: 576, 6: 768, 7: 256, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 3026, 16: 3024, 17: 3072, 18: 3002, 19: 3072, 20: 3072, 21: 1277, 22: 345, 23: 1040})])",MACs,8825.080064,top1_acc,-84.90066225165563 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 692, 23: 408})])",MACs,8068.008192,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 768, 4: 640, 5: 384, 6: 768, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3038, 15: 3072, 16: 3072, 17: 2527, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 692, 23: 3072})])",MACs,8208.386304,top1_acc,-84.74783494651045 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,5719.656704,top1_acc,-84.17727967396841 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 512, 8: 640, 9: 320, 10: 768, 11: 256, 12: 1542, 13: 2465, 14: 1891, 15: 3026, 16: 1825, 17: 2527, 18: 3002, 19: 2318, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,7142.967552,top1_acc,-84.27916454406521 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 192, 5: 768, 6: 128, 7: 256, 8: 256, 9: 768, 10: 768, 11: 256, 12: 2448, 13: 3032, 14: 1891, 15: 2589, 16: 1825, 17: 2527, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6581.52064,top1_acc,-84.27916454406521 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 768, 10: 192, 11: 768, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 408})])",MACs,7507.872,top1_acc,-84.54406520631686 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 3072, 16: 3072, 17: 2527, 18: 3002, 19: 2985, 20: 2035, 21: 2664, 22: 1988, 23: 3072})])",MACs,10041.559296,top1_acc,-84.90066225165563 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 512, 4: 768, 5: 384, 6: 768, 7: 768, 8: 640, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 1891, 15: 3026, 16: 2564, 17: 2994, 18: 3002, 19: 2318, 20: 3072, 21: 628, 22: 345, 23: 1040})])",MACs,7470.84416,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 3026, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,9040.824576,top1_acc,-84.99235863474274 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 768, 5: 576, 6: 768, 7: 256, 8: 768, 9: 320, 10: 768, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 3024, 17: 2994, 18: 3002, 19: 3072, 20: 2969, 21: 1277, 22: 692, 23: 213})])",MACs,7695.567104,top1_acc,-84.78858889454915 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 768, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3032, 14: 3038, 15: 3072, 16: 3072, 17: 2994, 18: 3002, 19: 2985, 20: 1223, 21: 2664, 22: 1988, 23: 3072})])",MACs,9420.605696,top1_acc,-84.9617931737137 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 192, 5: 576, 6: 576, 7: 512, 8: 256, 9: 768, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,6438.783232,top1_acc,-84.09577177789099 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 768, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7690.193152,top1_acc,-84.9617931737137 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 3038, 15: 2589, 16: 1825, 17: 1790, 18: 1678, 19: 2318, 20: 2969, 21: 628, 22: 345, 23: 213})])",MACs,5784.93056,top1_acc,-83.87162506367804 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 3038, 15: 2589, 16: 2564, 17: 1790, 18: 3072, 19: 2318, 20: 2035, 21: 2664, 22: 1988, 23: 1040})])",MACs,8488.749312,top1_acc,-84.49312277126847 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 2589, 16: 2564, 17: 2527, 18: 3002, 19: 1544, 20: 3072, 21: 1277, 22: 345, 23: 408})])",MACs,7697.664256,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 3026, 16: 3072, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8723.826944,top1_acc,-85.00254712175241 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,6501.697792,top1_acc,-84.25878757004584 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 320, 4: 192, 5: 768, 6: 576, 7: 512, 8: 256, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 2465, 14: 3038, 15: 2589, 16: 3024, 17: 3072, 18: 1678, 19: 2318, 20: 1223, 21: 1277, 22: 692, 23: 1040})])",MACs,7220.037888,top1_acc,-84.50331125827815 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 768, 9: 768, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 3072, 18: 3002, 19: 1544, 20: 2969, 21: 1277, 22: 692, 23: 213})])",MACs,6907.627776,top1_acc,-84.41161487519103 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,5979.834624,top1_acc,-84.36067244014264 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 2589, 16: 3072, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,7405.30816,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 128, 7: 512, 8: 640, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2527, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7810.976,top1_acc,-84.69689251146205 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 3038, 15: 3026, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9514.58432,top1_acc,-84.98217014773306 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 320, 4: 192, 5: 384, 6: 576, 7: 512, 8: 768, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 1891, 15: 3026, 16: 1825, 17: 2527, 18: 1678, 19: 1544, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,7191.529728,top1_acc,-84.29954151808457 +"OrderedDict([(, {0: 256, 1: 320, 2: 768, 3: 320, 4: 640, 5: 576, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2527, 18: 2438, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 408})])",MACs,7429.032192,top1_acc,-84.60519612837494 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 320, 10: 768, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 3026, 16: 3024, 17: 2527, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8040.352,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,5825.104128,top1_acc,-84.20784513499746 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 512, 4: 192, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 3072, 17: 1790, 18: 1678, 19: 2318, 20: 2969, 21: 1277, 22: 345, 23: 1040})])",MACs,6269.2416,top1_acc,-84.07539480387163 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 3072})])",MACs,7569.80352,top1_acc,-84.88028527763628 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 640, 9: 256, 10: 768, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 3026, 16: 2564, 17: 2527, 18: 1678, 19: 2318, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,7365.3312,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8674.4128,top1_acc,-84.83953132959755 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 2606, 15: 2589, 16: 1825, 17: 3072, 18: 1678, 19: 3072, 20: 2969, 21: 628, 22: 692, 23: 1040})])",MACs,7335.250176,top1_acc,-84.60519612837494 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 3038, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 1040})])",MACs,7942.179072,top1_acc,-84.64595007641365 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 768, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 2465, 14: 2606, 15: 2589, 16: 2564, 17: 2994, 18: 1678, 19: 3072, 20: 2035, 21: 628, 22: 692, 23: 213})])",MACs,6869.813504,top1_acc,-84.381049414162 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7158.696192,top1_acc,-84.91085073866532 +"OrderedDict([(, {0: 256, 1: 256, 2: 384, 3: 768, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 3072, 16: 3072, 17: 2527, 18: 2438, 19: 2985, 20: 1223, 21: 2664, 22: 1988, 23: 3072})])",MACs,8747.026688,top1_acc,-84.93122771268466 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 1678, 19: 3072, 20: 2035, 21: 1277, 22: 692, 23: 1040})])",MACs,6803.622144,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 576, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 768, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 408})])",MACs,6169.364736,top1_acc,-84.07539480387163 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 640, 5: 576, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 3026, 16: 3024, 17: 2527, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9094.039808,top1_acc,-84.79877738155885 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 768, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,6340.479232,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 768, 4: 768, 5: 384, 6: 576, 7: 512, 8: 640, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 692, 23: 408})])",MACs,7730.03904,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6402.803968,top1_acc,-84.4218033622007 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 3026, 16: 3024, 17: 2527, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8751.614208,top1_acc,-84.85990830361692 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 640, 5: 768, 6: 768, 7: 256, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 2589, 16: 2564, 17: 2527, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 1040})])",MACs,7581.993216,top1_acc,-84.75802343352012 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,6946.752768,top1_acc,-84.39123790117168 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,6076.500224,top1_acc,-84.46255731023943 +"OrderedDict([(, {0: 768, 1: 768, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 2465, 14: 3038, 15: 3026, 16: 1825, 17: 2994, 18: 1678, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8079.6736,top1_acc,-84.61538461538461 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8545.437952,top1_acc,-85.03311258278146 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,6107.433216,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 256, 10: 768, 11: 256, 12: 2448, 13: 3072, 14: 1891, 15: 3026, 16: 3072, 17: 2994, 18: 3002, 19: 2318, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8404.470016,top1_acc,-84.72745797249108 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 640, 5: 384, 6: 576, 7: 512, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 2318, 20: 2969, 21: 628, 22: 345, 23: 213})])",MACs,6727.141632,top1_acc,-84.31991849210392 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 192, 5: 768, 6: 576, 7: 256, 8: 768, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 1611, 14: 3038, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7591.4304,top1_acc,-84.40142638818135 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 256, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 2606, 15: 2589, 16: 2564, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 692, 23: 213})])",MACs,7572.818176,top1_acc,-84.68670402445237 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 1825, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9015.85536,top1_acc,-84.81915435557819 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 3038, 15: 3026, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8842.119424,top1_acc,-84.91085073866532 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 2438, 19: 1544, 20: 2969, 21: 628, 22: 345, 23: 213})])",MACs,6155.340032,top1_acc,-84.20784513499746 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 3038, 15: 2589, 16: 1825, 17: 1790, 18: 3002, 19: 2318, 20: 2969, 21: 628, 22: 345, 23: 1040})])",MACs,7593.658624,top1_acc,-84.4727457972491 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 3072, 19: 1544, 20: 1223, 21: 2664, 22: 692, 23: 3072})])",MACs,8219.199744,top1_acc,-84.73764645950077 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 2606, 15: 2589, 16: 2564, 17: 2527, 18: 1678, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7680.624896,top1_acc,-84.68670402445237 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6568.544512,top1_acc,-84.31991849210392 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 768, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 1891, 15: 2589, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 408})])",MACs,6021.318912,top1_acc,-84.15690269994906 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 3072, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 408})])",MACs,7870.089472,top1_acc,-84.71726948548141 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 640, 5: 768, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 3032, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 692, 23: 213})])",MACs,7077.497088,top1_acc,-84.61538461538461 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 1040})])",MACs,5779.294464,top1_acc,-83.98369842078452 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 192, 5: 768, 6: 768, 7: 256, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 2969, 21: 1277, 22: 345, 23: 1040})])",MACs,7060.26112,top1_acc,-84.1874681609781 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 192, 5: 768, 6: 768, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 3072})])",MACs,6627.592448,top1_acc,-84.15690269994906 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2318, 20: 2969, 21: 1277, 22: 345, 23: 1040})])",MACs,6938.626304,top1_acc,-84.39123790117168 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 640, 5: 384, 6: 768, 7: 768, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 3072, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,7195.26528,top1_acc,-84.4727457972491 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 768, 5: 768, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 2606, 15: 3026, 16: 3072, 17: 2994, 18: 1678, 19: 3072, 20: 2969, 21: 628, 22: 692, 23: 1040})])",MACs,7841.843456,top1_acc,-84.60519612837494 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 192, 5: 768, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 2318, 20: 1223, 21: 628, 22: 692, 23: 408})])",MACs,6474.762496,top1_acc,-84.0855832908813 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 768, 9: 768, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 2035, 21: 1277, 22: 692, 23: 213})])",MACs,6471.944448,top1_acc,-84.20784513499746 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 640, 9: 256, 10: 768, 11: 256, 12: 1542, 13: 3072, 14: 1891, 15: 3026, 16: 3072, 17: 2994, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,6915.09888,top1_acc,-84.2384105960265 +"OrderedDict([(, {0: 256, 1: 320, 2: 768, 3: 768, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 692, 23: 213})])",MACs,7525.23904,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 512, 8: 640, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 408})])",MACs,6645.483776,top1_acc,-84.50331125827815 +"OrderedDict([(, {0: 768, 1: 320, 2: 192, 3: 320, 4: 640, 5: 768, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 2606, 15: 2589, 16: 2564, 17: 2994, 18: 3072, 19: 1544, 20: 1223, 21: 2664, 22: 692, 23: 3072})])",MACs,8291.68256,top1_acc,-84.61538461538461 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 3072, 17: 1790, 18: 1678, 19: 2318, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,5922.031872,top1_acc,-84.1874681609781 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,5747.050752,top1_acc,-83.95313295975548 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 3038, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 408})])",MACs,7313.23008,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 512, 4: 192, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 2969, 21: 1277, 22: 345, 23: 1040})])",MACs,6172.313856,top1_acc,-84.04482934284259 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,5879.499008,top1_acc,-84.1365257259297 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 2589, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 2035, 21: 1277, 22: 1988, 23: 408})])",MACs,7570.655488,top1_acc,-84.65613856342333 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 512, 8: 256, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 2465, 14: 3038, 15: 3026, 16: 3024, 17: 3072, 18: 3002, 19: 2318, 20: 2035, 21: 1277, 22: 692, 23: 1040})])",MACs,8434.747648,top1_acc,-84.68670402445237 +"OrderedDict([(, {0: 256, 1: 256, 2: 384, 3: 768, 4: 192, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 768, 11: 256, 12: 2448, 13: 3032, 14: 1891, 15: 3072, 16: 3072, 17: 2527, 18: 2438, 19: 1544, 20: 1223, 21: 2664, 22: 345, 23: 3072})])",MACs,7554.533632,top1_acc,-84.5236882322975 +"OrderedDict([(, {0: 256, 1: 768, 2: 192, 3: 320, 4: 192, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,7818.250496,top1_acc,-84.4218033622007 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 3026, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 692, 23: 1040})])",MACs,9590.671616,top1_acc,-84.9617931737137 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 640, 5: 384, 6: 768, 7: 768, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 2589, 16: 3072, 17: 2994, 18: 1678, 19: 2318, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,7487.424768,top1_acc,-84.60519612837494 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 2606, 15: 2589, 16: 3072, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,9012.447488,top1_acc,-84.89047376464595 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 192, 5: 768, 6: 768, 7: 512, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 628, 22: 692, 23: 213})])",MACs,6605.244672,top1_acc,-84.1365257259297 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 640, 5: 768, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 692, 23: 213})])",MACs,6633.883904,top1_acc,-84.45236882322975 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7526.615296,top1_acc,-84.74783494651045 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9436.530944,top1_acc,-85.14518593988792 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 3072, 15: 2589, 16: 3024, 17: 3072, 18: 1678, 19: 2318, 20: 2035, 21: 1277, 22: 692, 23: 1040})])",MACs,6922.897664,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 256, 1: 256, 2: 384, 3: 768, 4: 768, 5: 384, 6: 576, 7: 512, 8: 256, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7945.65248,top1_acc,-84.72745797249108 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 2318, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8742.963456,top1_acc,-84.79877738155885 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 384, 6: 768, 7: 512, 8: 640, 9: 768, 10: 192, 11: 256, 12: 2448, 13: 3072, 14: 2606, 15: 2589, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 692, 23: 213})])",MACs,6883.707136,top1_acc,-84.24859908303617 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7017.531648,top1_acc,-84.82934284258788 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,5815.470336,top1_acc,-84.00407539480386 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 3026, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8281.786624,top1_acc,-84.72745797249108 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 3072})])",MACs,8265.992448,top1_acc,-84.85990830361692 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6334.580992,top1_acc,-84.35048395313297 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 2969, 21: 628, 22: 345, 23: 213})])",MACs,5492.771072,top1_acc,-83.88181355068772 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7898.269952,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 3072})])",MACs,7041.059072,top1_acc,-84.60519612837494 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 3038, 15: 1877, 16: 1825, 17: 3072, 18: 3002, 19: 1544, 20: 2969, 21: 1277, 22: 692, 23: 213})])",MACs,7351.24096,top1_acc,-84.39123790117168 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7240.48512,top1_acc,-84.70708099847172 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 640, 5: 384, 6: 768, 7: 768, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 2589, 16: 3072, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,7335.250176,top1_acc,-84.49312277126847 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3038, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5758.978304,top1_acc,-84.26897605705553 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6866.27456,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 2589, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 2969, 21: 628, 22: 345, 23: 213})])",MACs,5407.246592,top1_acc,-83.88181355068772 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 640, 5: 768, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3038, 15: 1877, 16: 2564, 17: 1790, 18: 3072, 19: 1544, 20: 1223, 21: 2664, 22: 345, 23: 3072})])",MACs,7902.07104,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 640, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 408})])",MACs,7318.14528,top1_acc,-84.5236882322975 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 640, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 408})])",MACs,6827.215104,top1_acc,-84.381049414162 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 3038, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7914.391808,top1_acc,-84.82934284258788 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6462.507264,top1_acc,-84.64595007641365 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3072, 19: 2318, 20: 2969, 21: 2664, 22: 692, 23: 3072})])",MACs,9204.730112,top1_acc,-84.79877738155885 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 3026, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 3072})])",MACs,9921.956096,top1_acc,-84.95160468670403 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7299.533056,top1_acc,-84.66632705043301 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 768, 9: 768, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 3072, 17: 3072, 18: 2438, 19: 1544, 20: 2969, 21: 628, 22: 345, 23: 1040})])",MACs,6781.208832,top1_acc,-84.26897605705553 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 3038, 15: 2589, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5289.4784,top1_acc,-84.05501782985226 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,7170.296064,top1_acc,-84.82934284258788 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,6152.390912,top1_acc,-84.37086092715231 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2318, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,5296.163072,top1_acc,-84.02445236882323 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 768, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 692, 23: 213})])",MACs,7162.759424,top1_acc,-84.60519612837494 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 1040})])",MACs,5697.505536,top1_acc,-84.0855832908813 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 2438, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6803.097856,top1_acc,-84.77840040753948 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6721.308928,top1_acc,-84.68670402445237 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 768, 9: 768, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 1040})])",MACs,6757.615872,top1_acc,-84.41161487519103 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 640, 5: 768, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7812.94208,top1_acc,-84.94141619969434 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 2589, 16: 1825, 17: 3072, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7299.008768,top1_acc,-84.65613856342333 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 408})])",MACs,7444.564224,top1_acc,-84.55425369332654 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 640, 9: 320, 10: 768, 11: 256, 12: 3072, 13: 3072, 14: 3038, 15: 3026, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 2664, 22: 345, 23: 213})])",MACs,8206.15808,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,7421.167872,top1_acc,-84.91085073866532 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 3072, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 2318, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,5792.336128,top1_acc,-84.15690269994906 +"OrderedDict([(, {0: 256, 1: 256, 2: 384, 3: 768, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 692, 23: 213})])",MACs,6819.875072,top1_acc,-84.46255731023943 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,6172.969216,top1_acc,-84.43199184921039 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 256, 12: 1542, 13: 1611, 14: 3038, 15: 2589, 16: 1825, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,6431.508736,top1_acc,-84.22822210901681 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7114.852608,top1_acc,-84.60519612837494 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 640, 5: 384, 6: 576, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7983.925504,top1_acc,-84.83953132959755 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 3072, 15: 3026, 16: 3072, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8430.160128,top1_acc,-84.49312277126847 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,7633.111296,top1_acc,-84.88028527763628 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 768, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,6215.567616,top1_acc,-84.2384105960265 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 768, 9: 768, 10: 192, 11: 256, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 2969, 21: 1277, 22: 692, 23: 3072})])",MACs,7756.122368,top1_acc,-84.53387671930719 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,5143.98848,top1_acc,-83.95313295975548 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 768, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 3072})])",MACs,8061.454592,top1_acc,-84.80896586856852 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 768, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 768, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 3026, 16: 1825, 17: 1790, 18: 3072, 19: 3072, 20: 2969, 21: 628, 22: 345, 23: 213})])",MACs,6667.438336,top1_acc,-84.28935303107488 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6891.112704,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7778.797824,top1_acc,-84.55425369332654 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6907.824384,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,5483.661568,top1_acc,-84.10596026490066 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 3032, 14: 1891, 15: 2589, 16: 2564, 17: 1790, 18: 1678, 19: 1544, 20: 2969, 21: 628, 22: 345, 23: 213})])",MACs,5750.130944,top1_acc,-83.85124808965868 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5881.26848,top1_acc,-84.21803362200713 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 768, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 1790, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,7403.407616,top1_acc,-84.66632705043301 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 576, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 3072, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6318.655744,top1_acc,-84.05501782985226 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5820.254464,top1_acc,-84.37086092715231 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7983.859968,top1_acc,-84.95160468670403 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 628, 22: 692, 23: 1040})])",MACs,7902.464256,top1_acc,-84.85990830361692 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 3002, 19: 3072, 20: 2969, 21: 1277, 22: 692, 23: 213})])",MACs,7566.723328,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 768, 1: 768, 2: 192, 3: 320, 4: 640, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 692, 23: 1040})])",MACs,8497.268992,top1_acc,-84.94141619969434 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5675.48544,top1_acc,-84.12633723892003 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 640, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 2465, 14: 3038, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 2664, 22: 345, 23: 408})])",MACs,7584.745728,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 3072})])",MACs,7528.712448,top1_acc,-84.63576158940397 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6253.119744,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 3072, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,6844.713216,top1_acc,-84.63576158940397 +"OrderedDict([(, {0: 256, 1: 320, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3038, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5968.365824,top1_acc,-84.35048395313297 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 3072})])",MACs,8155.891968,top1_acc,-84.77840040753948 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 640, 5: 768, 6: 576, 7: 512, 8: 256, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6500.976896,top1_acc,-84.54406520631686 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,5993.793792,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 320, 4: 192, 5: 384, 6: 768, 7: 768, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 3072, 14: 1891, 15: 2589, 16: 3072, 17: 1790, 18: 3002, 19: 1544, 20: 2969, 21: 628, 22: 345, 23: 213})])",MACs,7176.849664,top1_acc,-84.48293428425879 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,5958.011136,top1_acc,-84.381049414162 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,6027.675904,top1_acc,-84.39123790117168 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,7417.235712,top1_acc,-84.4218033622007 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 768, 5: 576, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8627.22688,top1_acc,-85.0127356087621 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,6300.567808,top1_acc,-84.4727457972491 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 768, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6722.488576,top1_acc,-84.27916454406521 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,6223.03872,top1_acc,-84.26897605705553 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,6799.42784,top1_acc,-84.80896586856852 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 640, 5: 384, 6: 576, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 1825, 17: 3072, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7432.83328,top1_acc,-84.48293428425879 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 1040})])",MACs,7830.505728,top1_acc,-84.91085073866532 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 768, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2318, 20: 2035, 21: 1277, 22: 345, 23: 408})])",MACs,6568.544512,top1_acc,-84.48293428425879 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 320, 4: 192, 5: 768, 6: 768, 7: 768, 8: 640, 9: 256, 10: 768, 11: 768, 12: 1542, 13: 3072, 14: 3038, 15: 2589, 16: 1825, 17: 2994, 18: 3072, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8255.506688,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 3026, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 692, 23: 1040})])",MACs,8936.360192,top1_acc,-84.79877738155885 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 640, 5: 768, 6: 768, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 692, 23: 1040})])",MACs,7303.203072,top1_acc,-84.69689251146205 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5612.701952,top1_acc,-84.27916454406521 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 768, 9: 320, 10: 768, 11: 768, 12: 1542, 13: 1611, 14: 3038, 15: 2589, 16: 1825, 17: 2994, 18: 1678, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,7666.927872,top1_acc,-84.54406520631686 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2318, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,5445.585152,top1_acc,-83.96332144676516 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5904.271616,top1_acc,-84.25878757004584 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 408})])",MACs,6072.96128,top1_acc,-84.16709118695873 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7902.07104,top1_acc,-84.95160468670403 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 1040})])",MACs,6133.713152,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,4802.21824,top1_acc,-83.96332144676516 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6038.358272,top1_acc,-84.41161487519103 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6057.363712,top1_acc,-84.29954151808457 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 640, 5: 768, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 408})])",MACs,7152.732416,top1_acc,-84.65613856342333 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 192, 5: 576, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6417.811712,top1_acc,-84.30973000509424 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 1891, 15: 2589, 16: 3072, 17: 1790, 18: 1678, 19: 1544, 20: 2969, 21: 628, 22: 345, 23: 213})])",MACs,6602.033408,top1_acc,-84.1874681609781 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6926.502144,top1_acc,-84.74783494651045 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,7721.584896,top1_acc,-84.97198166072339 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6871.779584,top1_acc,-84.75802343352012 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5265.950976,top1_acc,-84.16709118695873 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 512, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,5926.553856,top1_acc,-84.04482934284259 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6694.701312,top1_acc,-84.56444218033621 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 1040})])",MACs,5397.088512,top1_acc,-83.87162506367804 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 2438, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6797.592832,top1_acc,-84.78858889454915 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 576, 6: 576, 7: 768, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 408})])",MACs,7861.897472,top1_acc,-84.82934284258788 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 640, 5: 768, 6: 576, 7: 512, 8: 256, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 2035, 21: 1277, 22: 692, 23: 1040})])",MACs,8006.404352,top1_acc,-84.87009679062659 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3038, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6322.784512,top1_acc,-84.37086092715231 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 408})])",MACs,9121.433856,top1_acc,-84.98217014773306 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,7848.724736,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5066.131712,top1_acc,-84.04482934284259 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 2438, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,7130.253568,top1_acc,-84.70708099847172 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 2664, 22: 345, 23: 3072})])",MACs,7530.48192,top1_acc,-84.21803362200713 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 2606, 15: 2589, 16: 2564, 17: 3072, 18: 2438, 19: 3072, 20: 1223, 21: 2664, 22: 692, 23: 3072})])",MACs,8406.501632,top1_acc,-84.80896586856852 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 192, 5: 768, 6: 768, 7: 512, 8: 256, 9: 768, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,7026.116864,top1_acc,-84.56444218033621 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,6622.218496,top1_acc,-84.4218033622007 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 768, 6: 576, 7: 512, 8: 256, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6555.502848,top1_acc,-84.50331125827815 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5625.3504,top1_acc,-84.10596026490066 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 2589, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,5223.61472,top1_acc,-84.01426388181356 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7040.010496,top1_acc,-84.37086092715231 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,5736.7616,top1_acc,-84.10596026490066 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 576, 6: 768, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,8005.29024,top1_acc,-84.77840040753948 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 768, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 692, 23: 213})])",MACs,7499.811072,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,6772.55808,top1_acc,-84.46255731023943 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6135.351552,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 640, 5: 768, 6: 768, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 3038, 15: 2589, 16: 1825, 17: 2994, 18: 3072, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6468.274432,top1_acc,-84.33010697911361 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 3072, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,7105.874176,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 3072, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,6220.679424,top1_acc,-84.40142638818135 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5437.327616,top1_acc,-84.24859908303617 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2318, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,5241.63712,top1_acc,-83.91237901171677 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6335.301888,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5209.85216,top1_acc,-84.21803362200713 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 768, 7: 768, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,8331.790592,top1_acc,-84.83953132959755 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6748.571904,top1_acc,-84.65613856342333 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5978.851584,top1_acc,-84.2384105960265 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 320, 4: 768, 5: 576, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 3038, 15: 2589, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 2664, 22: 692, 23: 3072})])",MACs,8506.64064,top1_acc,-84.77840040753948 +"OrderedDict([(, {0: 256, 1: 320, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3038, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6432.360704,top1_acc,-84.54406520631686 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 256, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 408})])",MACs,8794.933504,top1_acc,-84.93122771268466 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6225.856768,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,5626.464512,top1_acc,-84.25878757004584 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 640, 5: 768, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3072, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7083.85408,top1_acc,-84.77840040753948 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3072, 19: 2318, 20: 1223, 21: 2664, 22: 692, 23: 3072})])",MACs,8861.452544,top1_acc,-84.9617931737137 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6785.99296,top1_acc,-84.80896586856852 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 2318, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5764.876544,top1_acc,-84.35048395313297 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5333.584128,top1_acc,-83.95313295975548 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,6232.934656,top1_acc,-84.40142638818135 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 768, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,5610.670336,top1_acc,-84.00407539480386 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7023.036672,top1_acc,-84.82934284258788 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 768, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6526.011648,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7379.224832,top1_acc,-84.87009679062659 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5252.057344,top1_acc,-84.28935303107488 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 1790, 18: 3002, 19: 1544, 20: 2035, 21: 2664, 22: 345, 23: 213})])",MACs,8736.803072,top1_acc,-84.74783494651045 +"OrderedDict([(, {0: 256, 1: 320, 2: 384, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,7054.821632,top1_acc,-84.61538461538461 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,7203.064064,top1_acc,-84.82934284258788 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5547.624704,top1_acc,-83.92256749872644 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3032, 14: 2606, 15: 3026, 16: 2564, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 692, 23: 1040})])",MACs,8764.459264,top1_acc,-84.98217014773306 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 768, 4: 768, 5: 576, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 3026, 16: 1825, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8751.614208,top1_acc,-84.99235863474274 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9451.866368,top1_acc,-85.02292409577178 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5953.161472,top1_acc,-84.39123790117168 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,7423.068416,top1_acc,-84.77840040753948 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5237.115136,top1_acc,-84.17727967396841 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 640, 5: 768, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6514.215168,top1_acc,-84.4218033622007 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,7465.404672,top1_acc,-84.87009679062659 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,6023.088384,top1_acc,-84.10596026490066 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 768, 5: 576, 6: 576, 7: 512, 8: 256, 9: 256, 10: 768, 11: 768, 12: 2448, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 3072, 18: 3002, 19: 2318, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,7953.84448,top1_acc,-84.68670402445237 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6129.846528,top1_acc,-84.56444218033621 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6430.13248,top1_acc,-84.29954151808457 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 640, 5: 768, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7592.41344,top1_acc,-84.68670402445237 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 768, 6: 768, 7: 512, 8: 640, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 1277, 22: 692, 23: 213})])",MACs,6613.240064,top1_acc,-84.16709118695873 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,5765.859584,top1_acc,-84.24859908303617 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 384, 6: 768, 7: 512, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,6635.129088,top1_acc,-84.43199184921039 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6715.803904,top1_acc,-84.66632705043301 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5482.48192,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6566.971648,top1_acc,-84.63576158940397 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,5833.623808,top1_acc,-84.28935303107488 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8530.102528,top1_acc,-85.04330106979113 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5248.321792,top1_acc,-84.2384105960265 +"OrderedDict([(, {0: 256, 1: 320, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5715.593472,top1_acc,-84.41161487519103 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,5860.821248,top1_acc,-84.46255731023943 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6015.158528,top1_acc,-84.19765664798777 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,6138.431744,top1_acc,-84.21803362200713 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 768, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 2318, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6146.623744,top1_acc,-84.27916454406521 +"OrderedDict([(, {0: 768, 1: 320, 2: 256, 3: 320, 4: 640, 5: 768, 6: 768, 7: 512, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3072, 19: 1544, 20: 1223, 21: 2664, 22: 692, 23: 3072})])",MACs,8208.255232,top1_acc,-84.70708099847172 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6457.98528,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,6339.561728,top1_acc,-84.46255731023943 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6636.374272,top1_acc,-84.64595007641365 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,5988.74752,top1_acc,-84.40142638818135 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 692, 23: 1040})])",MACs,8613.660928,top1_acc,-85.0127356087621 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 692, 23: 1040})])",MACs,9525.594368,top1_acc,-85.00254712175241 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6585.321728,top1_acc,-84.4218033622007 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7274.694912,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,6902.64704,top1_acc,-84.33010697911361 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 2589, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5309.335808,top1_acc,-84.28935303107488 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,7020.873984,top1_acc,-84.70708099847172 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,6664.620288,top1_acc,-84.39123790117168 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,5544.74112,top1_acc,-84.20784513499746 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 768, 10: 192, 11: 256, 12: 3072, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,6199.183616,top1_acc,-84.33010697911361 +"OrderedDict([(, {0: 768, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7181.109504,top1_acc,-84.81915435557819 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9332.984064,top1_acc,-85.10443199184921 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5892.73728,top1_acc,-84.31991849210392 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 192, 5: 768, 6: 768, 7: 512, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6206.392576,top1_acc,-84.10596026490066 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 192, 5: 384, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6642.272512,top1_acc,-84.39123790117168 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 2438, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6729.369856,top1_acc,-84.73764645950077 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6696.929536,top1_acc,-84.75802343352012 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 768, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 3032, 14: 3038, 15: 3026, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7181.895936,top1_acc,-84.54406520631686 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,5635.049728,top1_acc,-84.21803362200713 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,5621.156096,top1_acc,-84.37086092715231 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,5396.760832,top1_acc,-84.1365257259297 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,7558.99008,top1_acc,-84.94141619969434 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6169.561344,top1_acc,-84.29954151808457 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5133.633792,top1_acc,-84.0346408558329 +"OrderedDict([(, {0: 256, 1: 320, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5592.91008,top1_acc,-84.21803362200713 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 2438, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6634.014976,top1_acc,-84.61538461538461 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,7825.131776,top1_acc,-84.90066225165563 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5842.864384,top1_acc,-84.27916454406521 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5752.031488,top1_acc,-84.21803362200713 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5311.498496,top1_acc,-84.36067244014264 +"OrderedDict([(, {0: 768, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 3038, 15: 1877, 16: 2564, 17: 3072, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6952.716544,top1_acc,-84.72745797249108 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5367.335168,top1_acc,-84.06520631686195 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5315.758336,top1_acc,-84.26897605705553 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,5583.997184,top1_acc,-83.9429444727458 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 3072, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,8298.498304,top1_acc,-84.92103922567499 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6298.667264,top1_acc,-84.381049414162 +"OrderedDict([(, {0: 256, 1: 320, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5275.584768,top1_acc,-84.2384105960265 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 768, 4: 640, 5: 768, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 692, 23: 408})])",MACs,8059.881728,top1_acc,-84.87009679062659 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 768, 6: 768, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6703.024384,top1_acc,-84.55425369332654 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7214.991616,top1_acc,-84.84971981660723 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 2564, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 692, 23: 408})])",MACs,8007.649536,top1_acc,-84.73764645950077 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7597.32864,top1_acc,-84.95160468670403 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8824.16256,top1_acc,-84.91085073866532 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 768, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3072, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8293.779712,top1_acc,-84.90066225165563 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7313.099008,top1_acc,-84.77840040753948 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6355.355904,top1_acc,-84.54406520631686 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,6575.29472,top1_acc,-84.54406520631686 +"OrderedDict([(, {0: 256, 1: 256, 2: 384, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5215.42272,top1_acc,-84.25878757004584 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 768, 5: 384, 6: 768, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,6485.313792,top1_acc,-84.61538461538461 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 768, 5: 768, 6: 576, 7: 512, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 2664, 22: 345, 23: 1040})])",MACs,7463.897344,top1_acc,-84.41161487519103 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7384.074496,top1_acc,-84.78858889454915 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 2318, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5728.24192,top1_acc,-84.30973000509424 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 1040})])",MACs,7429.425408,top1_acc,-84.88028527763628 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 3032, 14: 3072, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7782.664448,top1_acc,-84.75802343352012 +"OrderedDict([(, {0: 256, 1: 320, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 512, 8: 256, 9: 256, 10: 768, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 3026, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6453.987584,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 256, 1: 256, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 2589, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5432.936704,top1_acc,-84.2384105960265 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5489.166592,top1_acc,-84.30973000509424 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5896.931584,top1_acc,-84.1365257259297 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 768, 5: 576, 6: 576, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,7555.320064,top1_acc,-84.79877738155885 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6348.86784,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,8230.4064,top1_acc,-84.85990830361692 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7268.403456,top1_acc,-84.80896586856852 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9282.128128,top1_acc,-85.00254712175241 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5256.972544,top1_acc,-84.381049414162 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 768, 6: 768, 7: 256, 8: 640, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,6922.373376,top1_acc,-84.54406520631686 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 2589, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5227.54688,top1_acc,-84.37086092715231 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5710.809344,top1_acc,-84.30973000509424 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 256, 8: 768, 9: 256, 10: 768, 11: 768, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7857.83424,top1_acc,-84.71726948548141 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7676.692736,top1_acc,-84.92103922567499 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5170.268416,top1_acc,-84.06520631686195 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6454.249728,top1_acc,-84.70708099847172 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9033.091328,top1_acc,-84.87009679062659 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 768, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7791.708416,top1_acc,-84.67651553744268 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,4678.617344,top1_acc,-83.90219052470708 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6314.920192,top1_acc,-84.77840040753948 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 3038, 15: 1877, 16: 2564, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5634.459904,top1_acc,-84.30973000509424 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,6592.923904,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 768, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6951.995648,top1_acc,-84.69689251146205 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 3032, 14: 1891, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7713.458432,top1_acc,-84.51349974528782 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7970.294016,top1_acc,-85.00254712175241 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6566.971648,top1_acc,-84.63576158940397 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 768, 4: 192, 5: 384, 6: 576, 7: 512, 8: 768, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 3072, 18: 3002, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,6735.137024,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 3038, 15: 1877, 16: 3072, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6199.838976,top1_acc,-84.40142638818135 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8911.784192,top1_acc,-85.13499745287825 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6400.444672,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6057.625856,top1_acc,-84.26897605705553 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5373.430016,top1_acc,-84.12633723892003 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5545.134336,top1_acc,-84.1874681609781 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,6793.005312,top1_acc,-84.40142638818135 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 768, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,5787.87968,top1_acc,-83.9429444727458 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5595.8592,top1_acc,-84.26897605705553 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5765.531904,top1_acc,-84.31991849210392 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 3072, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6340.741376,top1_acc,-84.61538461538461 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 768, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 3026, 16: 1825, 17: 2994, 18: 2438, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7900.039424,top1_acc,-84.71726948548141 +"OrderedDict([(, {0: 256, 1: 256, 2: 384, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,6352.603392,top1_acc,-84.5236882322975 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5552.93312,top1_acc,-84.41161487519103 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6533.941504,top1_acc,-84.65613856342333 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 768, 11: 256, 12: 2448, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,7020.153088,top1_acc,-84.68670402445237 +"OrderedDict([(, {0: 256, 1: 768, 2: 768, 3: 320, 4: 640, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 256, 12: 3044, 13: 3072, 14: 2606, 15: 2589, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8452.114688,top1_acc,-84.78858889454915 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8951.3024,top1_acc,-85.05348955680081 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 512, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,5424.81024,top1_acc,-83.90219052470708 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 640, 5: 768, 6: 768, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,6834.227456,top1_acc,-84.56444218033621 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6560.614656,top1_acc,-84.72745797249108 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6361.64736,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 768, 7: 256, 8: 256, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7097.813248,top1_acc,-84.82934284258788 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 256, 8: 256, 9: 320, 10: 768, 11: 768, 12: 1542, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 2664, 22: 345, 23: 1040})])",MACs,8327.268608,top1_acc,-84.75802343352012 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6427.248896,top1_acc,-84.49312277126847 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5534.58304,top1_acc,-84.36067244014264 +"OrderedDict([(, {0: 256, 1: 256, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5615.716608,top1_acc,-84.30973000509424 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 512, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6360.992,top1_acc,-84.37086092715231 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5885.856,top1_acc,-84.2384105960265 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 256, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7916.16128,top1_acc,-84.98217014773306 +"OrderedDict([(, {0: 768, 1: 320, 2: 192, 3: 320, 4: 768, 5: 768, 6: 576, 7: 512, 8: 256, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 3032, 14: 1891, 15: 3026, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7653.755136,top1_acc,-84.73764645950077 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6916.475136,top1_acc,-84.70708099847172 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 320, 4: 768, 5: 384, 6: 768, 7: 256, 8: 640, 9: 320, 10: 768, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 2664, 22: 345, 23: 213})])",MACs,7532.185856,top1_acc,-84.77840040753948 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 768, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7144.605952,top1_acc,-84.72745797249108 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 768, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,6865.094912,top1_acc,-84.36067244014264 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 408})])",MACs,6359.68128,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,8358.594816,top1_acc,-84.78858889454915 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 3026, 16: 3072, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9052.55552,top1_acc,-84.99235863474274 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 512, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 408})])",MACs,5827.594496,top1_acc,-83.97350993377484 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5375.068416,top1_acc,-84.11614875191034 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8720.94336,top1_acc,-84.95160468670403 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 768, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 2589, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6896.617728,top1_acc,-84.4727457972491 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,7913.408768,top1_acc,-85.04330106979113 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 408})])",MACs,8863.48416,top1_acc,-84.94141619969434 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 2985, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6418.66368,top1_acc,-84.51349974528782 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 320, 4: 640, 5: 384, 6: 768, 7: 768, 8: 768, 9: 256, 10: 768, 11: 256, 12: 2448, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7045.777664,top1_acc,-84.56444218033621 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5839.522048,top1_acc,-84.49312277126847 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5325.19552,top1_acc,-84.19765664798777 +"OrderedDict([(, {0: 768, 1: 320, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 2438, 19: 2985, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,7243.172096,top1_acc,-84.78858889454915 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7131.433216,top1_acc,-84.74783494651045 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 512, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,6051.596544,top1_acc,-84.28935303107488 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,8518.961408,top1_acc,-84.88028527763628 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 2589, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8444.184832,top1_acc,-84.99235863474274 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,6329.075968,top1_acc,-84.56444218033621 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,5287.971072,top1_acc,-84.1874681609781 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,5885.659392,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 256, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8751.286528,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,7615.875328,top1_acc,-84.87009679062659 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,8475.117824,top1_acc,-85.02292409577178 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6413.617408,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 768, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6030.0352,top1_acc,-84.36067244014264 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,5713.889536,top1_acc,-84.39123790117168 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5069.015296,top1_acc,-83.93275598573612 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 408})])",MACs,6565.857536,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5160.896768,top1_acc,-84.05501782985226 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 768, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,7730.956544,top1_acc,-84.71726948548141 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 408})])",MACs,8334.412032,top1_acc,-84.9617931737137 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6653.020416,top1_acc,-84.36067244014264 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,7941.589248,top1_acc,-84.94141619969434 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5307.894016,top1_acc,-84.20784513499746 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8916.109568,top1_acc,-84.88028527763628 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6668.552448,top1_acc,-84.71726948548141 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 512, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,5156.702464,top1_acc,-83.92256749872644 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 576, 7: 256, 8: 768, 9: 768, 10: 192, 11: 256, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,7830.374656,top1_acc,-84.65613856342333 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 2664, 22: 345, 23: 408})])",MACs,8529.185024,top1_acc,-84.94141619969434 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 512, 8: 256, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 1040})])",MACs,7157.90976,top1_acc,-84.41161487519103 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8809.41696,top1_acc,-84.90066225165563 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5497.030912,top1_acc,-84.2384105960265 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5427.955968,top1_acc,-84.12633723892003 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6524.50432,top1_acc,-84.60519612837494 +"OrderedDict([(, {0: 768, 1: 768, 2: 192, 3: 320, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 256, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8487.30752,top1_acc,-84.72745797249108 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5179.902208,top1_acc,-83.86143657666837 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8256.94848,top1_acc,-84.66632705043301 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 692, 23: 1040})])",MACs,9525.594368,top1_acc,-85.00254712175241 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 256, 9: 320, 10: 768, 11: 768, 12: 1542, 13: 1611, 14: 3038, 15: 1877, 16: 3072, 17: 1790, 18: 1678, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,7180.978432,top1_acc,-84.28935303107488 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 768, 5: 768, 6: 768, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 2985, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,7491.619072,top1_acc,-84.75802343352012 +"OrderedDict([(, {0: 256, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6519.130368,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5498.734848,top1_acc,-84.22822210901681 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 2664, 22: 692, 23: 408})])",MACs,8197.769472,top1_acc,-85.09424350483953 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,8183.941376,top1_acc,-84.9617931737137 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 692, 23: 1040})])",MACs,8345.159936,top1_acc,-84.80896586856852 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,6286.805248,top1_acc,-84.17727967396841 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6096.816384,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 768, 11: 256, 12: 1542, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,5588.97792,top1_acc,-83.83087111563933 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6422.59584,top1_acc,-84.55425369332654 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5334.829312,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6024.46464,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5647.894784,top1_acc,-84.26897605705553 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7047.80928,top1_acc,-84.81915435557819 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,8076.003584,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6933.973248,top1_acc,-84.84971981660723 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 2589, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6448.941312,top1_acc,-84.39123790117168 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 640, 5: 384, 6: 576, 7: 768, 8: 256, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6736.709888,top1_acc,-84.5236882322975 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6631.131392,top1_acc,-84.5236882322975 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6201.608448,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 768, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8152.74624,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,8204.585216,top1_acc,-85.1146204788589 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 3026, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,7987.792128,top1_acc,-84.88028527763628 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 2664, 22: 345, 23: 213})])",MACs,8386.840832,top1_acc,-84.71726948548141 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5351.7376,top1_acc,-84.17727967396841 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 3038, 15: 2589, 16: 3072, 17: 3072, 18: 3002, 19: 3072, 20: 1223, 21: 2664, 22: 345, 23: 1040})])",MACs,8056.277248,top1_acc,-84.60519612837494 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8978.565376,top1_acc,-84.98217014773306 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6953.568512,top1_acc,-84.68670402445237 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,6995.773696,top1_acc,-84.66632705043301 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6128.601344,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8884.521216,top1_acc,-85.02292409577178 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6342.183168,top1_acc,-84.71726948548141 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5692.328192,top1_acc,-84.4218033622007 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5126.62144,top1_acc,-83.99388690779419 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 576, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 3072, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9048.426752,top1_acc,-84.98217014773306 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6192.761088,top1_acc,-84.50331125827815 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 692, 23: 1040})])",MACs,8984.856832,top1_acc,-84.97198166072339 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,5973.01888,top1_acc,-84.4727457972491 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 1542, 13: 1611, 14: 1891, 15: 2589, 16: 1825, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5697.702144,top1_acc,-84.26897605705553 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3072, 13: 1611, 14: 3038, 15: 2589, 16: 1825, 17: 2994, 18: 1678, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8349.419776,top1_acc,-84.56444218033621 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 1678, 19: 2985, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,6582.634752,top1_acc,-84.55425369332654 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,9247.918336,top1_acc,-85.12480896586857 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5633.804544,top1_acc,-84.29954151808457 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 3038, 15: 1877, 16: 2564, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5573.24928,top1_acc,-84.36067244014264 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9107.474688,top1_acc,-85.05348955680081 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 768, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6272.059648,top1_acc,-84.0855832908813 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5375.265024,top1_acc,-83.97350993377484 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6138.235136,top1_acc,-84.4727457972491 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5152.246016,top1_acc,-83.90219052470708 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,6920.407296,top1_acc,-84.63576158940397 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,4951.64032,top1_acc,-83.97350993377484 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,7872.841984,top1_acc,-84.9617931737137 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5124.917504,top1_acc,-84.26897605705553 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 256, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 2664, 22: 692, 23: 408})])",MACs,7727.614208,top1_acc,-84.90066225165563 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 768, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 3072, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6153.832704,top1_acc,-84.41161487519103 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5514.856704,top1_acc,-84.39123790117168 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,7868.451072,top1_acc,-84.83953132959755 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5741.742336,top1_acc,-84.31991849210392 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,5497.424128,top1_acc,-84.07539480387163 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,8127.580416,top1_acc,-84.82934284258788 +"OrderedDict([(, {0: 256, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 256, 8: 256, 9: 320, 10: 768, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6443.56736,top1_acc,-84.50331125827815 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5533.27232,top1_acc,-84.0855832908813 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,8395.426048,top1_acc,-84.97198166072339 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7423.396096,top1_acc,-84.9617931737137 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,8480.622848,top1_acc,-84.99235863474274 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 640, 5: 768, 6: 576, 7: 256, 8: 256, 9: 256, 10: 768, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,6005.590272,top1_acc,-84.16709118695873 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9245.690112,top1_acc,-84.99235863474274 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 768, 7: 512, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,5975.116032,top1_acc,-84.35048395313297 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,7415.662848,top1_acc,-84.93122771268466 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 2664, 22: 345, 23: 213})])",MACs,8461.027584,top1_acc,-84.80896586856852 +"OrderedDict([(, {0: 256, 1: 768, 2: 768, 3: 320, 4: 640, 5: 384, 6: 768, 7: 768, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 3072, 17: 2994, 18: 1678, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,6706.432256,top1_acc,-84.43199184921039 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 768, 5: 768, 6: 768, 7: 256, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 2664, 22: 692, 23: 1040})])",MACs,8590.919936,top1_acc,-84.87009679062659 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5369.694464,top1_acc,-84.07539480387163 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 1040})])",MACs,8936.360192,top1_acc,-85.12480896586857 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,5104.470272,top1_acc,-84.02445236882323 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6076.23808,top1_acc,-84.53387671930719 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,8962.246912,top1_acc,-84.98217014773306 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,7862.159616,top1_acc,-85.00254712175241 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7962.888448,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 768, 4: 768, 5: 384, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7366.9696,top1_acc,-84.84971981660723 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 3038, 15: 1877, 16: 2564, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6669.142272,top1_acc,-84.2384105960265 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,4968.67968,top1_acc,-83.83087111563933 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 768, 6: 768, 7: 768, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6121.13024,top1_acc,-84.15690269994906 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 692, 23: 1040})])",MACs,8443.267328,top1_acc,-84.85990830361692 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 1611, 14: 3038, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6999.31264,top1_acc,-84.33010697911361 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 320, 4: 640, 5: 576, 6: 768, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7136.348416,top1_acc,-84.5746306673459 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5406.918912,top1_acc,-84.09577177789099 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 256, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,7990.741248,top1_acc,-84.91085073866532 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 768, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6999.116032,top1_acc,-84.50331125827815 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 2664, 22: 692, 23: 1040})])",MACs,7921.338624,top1_acc,-84.78858889454915 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6460.213504,top1_acc,-84.66632705043301 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 3026, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8760.789248,top1_acc,-84.88028527763628 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,5720.246528,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 2985, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,6747.457792,top1_acc,-84.69689251146205 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 3072, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8703.510784,top1_acc,-84.79877738155885 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,5558.241536,top1_acc,-84.22822210901681 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6442.518784,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 768, 11: 256, 12: 1542, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6470.895872,top1_acc,-84.41161487519103 +"OrderedDict([(, {0: 768, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 2589, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 2664, 22: 345, 23: 408})])",MACs,7525.56672,top1_acc,-84.70708099847172 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 2606, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 2985, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8276.740352,top1_acc,-84.84971981660723 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6246.172928,top1_acc,-84.66632705043301 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,7380.797696,top1_acc,-84.85990830361692 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 640, 5: 768, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7101.614336,top1_acc,-84.49312277126847 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 640, 5: 576, 6: 768, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6814.8288,top1_acc,-84.56444218033621 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 1891, 15: 2589, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5713.692928,top1_acc,-84.35048395313297 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5310.318848,top1_acc,-84.25878757004584 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6899.828992,top1_acc,-84.87009679062659 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 1542, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5856.03712,top1_acc,-84.4218033622007 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,6115.297536,top1_acc,-84.05501782985226 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6027.151616,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,7357.860096,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,6556.485888,top1_acc,-84.56444218033621 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,6112.413952,top1_acc,-84.49312277126847 +"OrderedDict([(, {0: 256, 1: 320, 2: 768, 3: 320, 4: 192, 5: 768, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6636.636416,top1_acc,-84.4218033622007 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 768, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 408})])",MACs,6540.167424,top1_acc,-84.67651553744268 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6359.877888,top1_acc,-84.68670402445237 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 768, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6761.941248,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 768, 9: 256, 10: 768, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 3072})])",MACs,6892.685568,top1_acc,-84.21803362200713 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,9254.799616,top1_acc,-84.98217014773306 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 256, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 2589, 16: 3072, 17: 1790, 18: 3002, 19: 2985, 20: 1223, 21: 2664, 22: 345, 23: 213})])",MACs,7565.674752,top1_acc,-84.68670402445237 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7051.348224,top1_acc,-84.74783494651045 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,8153.663744,top1_acc,-84.91085073866532 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 768, 4: 192, 5: 384, 6: 576, 7: 512, 8: 256, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6195.5136,top1_acc,-84.24859908303617 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9336.65408,top1_acc,-85.05348955680081 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 2606, 15: 2589, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5122.754816,top1_acc,-83.98369842078452 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 3072, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5778.04928,top1_acc,-84.14671421293937 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 256, 9: 256, 10: 192, 11: 768, 12: 1542, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 1040})])",MACs,6053.62816,top1_acc,-84.27916454406521 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 2664, 22: 345, 23: 213})])",MACs,7682.066688,top1_acc,-84.92103922567499 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5962.53312,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6976.37504,top1_acc,-84.75802343352012 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7106.857216,top1_acc,-84.39123790117168 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 1040})])",MACs,8593.344768,top1_acc,-84.85990830361692 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 1040})])",MACs,8213.03936,top1_acc,-84.70708099847172 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6224.808192,top1_acc,-84.5236882322975 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 768, 7: 256, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,7741.114624,top1_acc,-84.89047376464595 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7820.740864,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 1040})])",MACs,9036.237056,top1_acc,-84.97198166072339 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5229.709568,top1_acc,-84.28935303107488 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 2606, 15: 2589, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6164.842752,top1_acc,-84.48293428425879 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 768, 8: 256, 9: 256, 10: 768, 11: 768, 12: 2448, 13: 1611, 14: 2606, 15: 2589, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,6732.187904,top1_acc,-84.4218033622007 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5454.760192,top1_acc,-84.39123790117168 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5377.62432,top1_acc,-84.17727967396841 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 192, 5: 768, 6: 768, 7: 256, 8: 768, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 3072, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7329.089792,top1_acc,-84.64595007641365 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5839.063296,top1_acc,-84.28935303107488 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7771.98208,top1_acc,-84.83953132959755 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6096.816384,top1_acc,-84.5236882322975 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 692, 23: 1040})])",MACs,8950.057216,top1_acc,-85.05348955680081 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,4923.984128,top1_acc,-84.09577177789099 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 576, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,8313.63712,top1_acc,-84.90066225165563 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 1542, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5214.046464,top1_acc,-83.84105960264901 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7899.711744,top1_acc,-85.13499745287825 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6244.141312,top1_acc,-84.48293428425879 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5948.705024,top1_acc,-84.19765664798777 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,4942.79296,top1_acc,-84.09577177789099 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6396.70912,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6791.432448,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 320, 4: 640, 5: 768, 6: 768, 7: 256, 8: 768, 9: 320, 10: 768, 11: 256, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 2664, 22: 692, 23: 213})])",MACs,7694.846208,top1_acc,-84.65613856342333 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6977.423616,top1_acc,-84.78858889454915 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 3026, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7619.348736,top1_acc,-84.51349974528782 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5520.230656,top1_acc,-84.4218033622007 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5596.645632,top1_acc,-84.43199184921039 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6097.733888,top1_acc,-84.21803362200713 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 1040})])",MACs,8367.180032,top1_acc,-84.94141619969434 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,7030.44224,top1_acc,-84.77840040753948 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5843.192064,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6161.631488,top1_acc,-84.50331125827815 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,4984.342784,top1_acc,-84.12633723892003 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5498.407168,top1_acc,-84.28935303107488 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 256, 8: 256, 9: 320, 10: 768, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 2664, 22: 345, 23: 213})])",MACs,7136.807168,top1_acc,-84.83953132959755 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 1040})])",MACs,7461.931264,top1_acc,-84.73764645950077 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 408})])",MACs,7856.261376,top1_acc,-85.07386653082017 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 768, 4: 768, 5: 768, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6216.419584,top1_acc,-84.33010697911361 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5549.00096,top1_acc,-84.27916454406521 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5880.744192,top1_acc,-84.41161487519103 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 512, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 692, 23: 1040})])",MACs,6853.560576,top1_acc,-84.65613856342333 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,8749.189376,top1_acc,-84.94141619969434 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 576, 6: 768, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 3072, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5338.368256,top1_acc,-84.00407539480386 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 256, 12: 1542, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6980.503808,top1_acc,-84.54406520631686 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 768, 6: 576, 7: 256, 8: 256, 9: 320, 10: 768, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6093.867264,top1_acc,-84.16709118695873 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,7848.528128,top1_acc,-84.78858889454915 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 2589, 16: 2564, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7039.813888,top1_acc,-84.75802343352012 +"OrderedDict([(, {0: 384, 1: 320, 2: 384, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,6607.341824,top1_acc,-84.381049414162 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8502.839552,top1_acc,-84.9617931737137 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 768, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 2589, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5582.358784,top1_acc,-84.381049414162 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 256, 10: 192, 11: 768, 12: 1542, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6484.461824,top1_acc,-84.48293428425879 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5870.913792,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5087.561984,top1_acc,-84.09577177789099 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 192, 5: 384, 6: 768, 7: 512, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6320.949504,top1_acc,-84.37086092715231 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 768, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5533.862144,top1_acc,-84.16709118695873 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 192, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8805.81248,top1_acc,-84.94141619969434 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,4856.744192,top1_acc,-84.06520631686195 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,4946.790656,top1_acc,-83.97350993377484 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3072, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5667.358976,top1_acc,-84.27916454406521 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,5643.962624,top1_acc,-84.00407539480386 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 2589, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6657.411328,top1_acc,-84.63576158940397 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 692, 23: 1040})])",MACs,9504.75392,top1_acc,-85.04330106979113 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6548.621568,top1_acc,-84.5236882322975 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7881.230592,top1_acc,-84.63576158940397 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5226.105088,top1_acc,-84.06520631686195 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 192, 5: 384, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 3032, 14: 1891, 15: 3026, 16: 1825, 17: 1790, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,7654.934784,top1_acc,-84.48293428425879 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6320.425216,top1_acc,-84.75802343352012 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6712.26496,top1_acc,-84.78858889454915 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,7458.195712,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 192, 5: 768, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5851.842816,top1_acc,-84.06520631686195 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6591.875328,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5944.248576,top1_acc,-84.56444218033621 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 256, 8: 768, 9: 256, 10: 768, 11: 768, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6469.847296,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,7653.36192,top1_acc,-84.91085073866532 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5999.692032,top1_acc,-84.27916454406521 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 768, 4: 192, 5: 768, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 1040})])",MACs,5973.34656,top1_acc,-84.14671421293937 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5813.504256,top1_acc,-84.39123790117168 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 768, 4: 768, 5: 768, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,6241.192192,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5861.28,top1_acc,-84.37086092715231 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6388.648192,top1_acc,-84.67651553744268 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6770.854144,top1_acc,-84.64595007641365 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6250.170624,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6209.734912,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,4929.816832,top1_acc,-83.99388690779419 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 2994, 18: 2438, 19: 3072, 20: 2035, 21: 628, 22: 692, 23: 1040})])",MACs,8010.926336,top1_acc,-84.70708099847172 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,5854.529792,top1_acc,-84.20784513499746 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7063.406848,top1_acc,-84.78858889454915 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 1542, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5221.97632,top1_acc,-84.10596026490066 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 408})])",MACs,6178.998528,top1_acc,-84.28935303107488 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,8136.36224,top1_acc,-85.08405501782985 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,4997.318912,top1_acc,-84.12633723892003 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 768, 6: 576, 7: 512, 8: 768, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 3072, 18: 3002, 19: 2985, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7686.850816,top1_acc,-84.72745797249108 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,6417.877248,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 408})])",MACs,7692.68352,top1_acc,-84.99235863474274 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5702.813952,top1_acc,-84.37086092715231 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 768, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 2465, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6511.659264,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 768, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6660.688128,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5523.507456,top1_acc,-84.5236882322975 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6034.491648,top1_acc,-84.59500764136526 +"OrderedDict([(, {0: 768, 1: 768, 2: 192, 3: 320, 4: 192, 5: 768, 6: 576, 7: 256, 8: 768, 9: 256, 10: 768, 11: 768, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 3072, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 2664, 22: 345, 23: 213})])",MACs,6965.758208,top1_acc,-84.19765664798777 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 408})])",MACs,6766.397696,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 408})])",MACs,6783.502592,top1_acc,-84.74783494651045 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5475.076352,top1_acc,-84.35048395313297 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6124.07936,top1_acc,-84.5236882322975 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 408})])",MACs,5098.637568,top1_acc,-84.05501782985226 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 768, 8: 768, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6682.380544,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7092.504832,top1_acc,-84.94141619969434 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 768, 11: 768, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6742.608128,top1_acc,-84.61538461538461 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5561.190656,top1_acc,-84.381049414162 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3038, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,8124.23808,top1_acc,-84.90066225165563 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5454.760192,top1_acc,-84.12633723892003 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6156.84736,top1_acc,-84.50331125827815 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 1825, 17: 1790, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,7400.589568,top1_acc,-84.70708099847172 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 768, 8: 256, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7322.994944,top1_acc,-84.92103922567499 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 768, 6: 576, 7: 768, 8: 256, 9: 256, 10: 768, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6070.077696,top1_acc,-84.0855832908813 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5427.497216,top1_acc,-84.2384105960265 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 576, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6513.953024,top1_acc,-84.20784513499746 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 256, 8: 256, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7463.504128,top1_acc,-84.84971981660723 +"OrderedDict([(, {0: 256, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5542.11968,top1_acc,-84.25878757004584 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 512, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 408})])",MACs,6741.297408,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7590.578432,top1_acc,-84.9617931737137 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5988.944128,top1_acc,-84.46255731023943 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8965.654784,top1_acc,-84.95160468670403 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 1542, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5620.566272,top1_acc,-84.43199184921039 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 768, 11: 256, 12: 3044, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7127.238912,top1_acc,-84.78858889454915 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5091.88736,top1_acc,-84.28935303107488 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 408})])",MACs,7996.836096,top1_acc,-84.99235863474274 +"OrderedDict([(, {0: 768, 1: 320, 2: 256, 3: 320, 4: 768, 5: 576, 6: 576, 7: 512, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 408})])",MACs,6768.756992,top1_acc,-84.68670402445237 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5651.106048,top1_acc,-84.55425369332654 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 3072, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6967.85536,top1_acc,-84.71726948548141 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 1544, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8555.46496,top1_acc,-84.81915435557819 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5183.375616,top1_acc,-84.00407539480386 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7119.24352,top1_acc,-84.72745797249108 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6561.925376,top1_acc,-84.67651553744268 +"OrderedDict([(, {0: 768, 1: 768, 2: 192, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 2664, 22: 345, 23: 1040})])",MACs,8004.176128,top1_acc,-84.65613856342333 +"OrderedDict([(, {0: 256, 1: 256, 2: 768, 3: 320, 4: 192, 5: 768, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5771.299072,top1_acc,-84.2384105960265 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 192, 5: 384, 6: 768, 7: 256, 8: 768, 9: 320, 10: 768, 11: 768, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,6110.97216,top1_acc,-84.07539480387163 +"OrderedDict([(, {0: 768, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,7363.102976,top1_acc,-84.69689251146205 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,4819.192064,top1_acc,-83.92256749872644 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5024.581888,top1_acc,-84.07539480387163 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 2985, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7075.399936,top1_acc,-84.95160468670403 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,8722.123008,top1_acc,-84.89047376464595 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5668.27648,top1_acc,-84.34029546612328 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5151.983872,top1_acc,-84.06520631686195 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6638.930176,top1_acc,-84.70708099847172 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6369.446144,top1_acc,-84.84971981660723 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6895.372544,top1_acc,-84.60519612837494 +"OrderedDict([(, {0: 256, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,6619.334912,top1_acc,-84.54406520631686 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 768, 5: 384, 6: 576, 7: 256, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,7331.25248,top1_acc,-84.61538461538461 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7151.290624,top1_acc,-84.84971981660723 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5698.947328,top1_acc,-84.53387671930719 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5843.650816,top1_acc,-84.33010697911361 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7440.500992,top1_acc,-85.00254712175241 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,8614.11968,top1_acc,-84.9617931737137 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5359.9296,top1_acc,-84.29954151808457 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 408})])",MACs,5741.152512,top1_acc,-84.4218033622007 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 2448, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 408})])",MACs,7397.44384,top1_acc,-84.75802343352012 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5792.270592,top1_acc,-84.48293428425879 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6927.091968,top1_acc,-84.79877738155885 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 256, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6006.704384,top1_acc,-84.24859908303617 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 768, 8: 256, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7040.010496,top1_acc,-84.67651553744268 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 192, 5: 768, 6: 576, 7: 512, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 3026, 16: 1825, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 1040})])",MACs,6564.874496,top1_acc,-84.46255731023943 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 576, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,4938.53312,top1_acc,-83.73917473255221 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5100.669184,top1_acc,-84.11614875191034 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 640, 5: 768, 6: 768, 7: 768, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,7351.306496,top1_acc,-84.61538461538461 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6646.663424,top1_acc,-84.5236882322975 +"OrderedDict([(, {0: 768, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6899.828992,top1_acc,-84.73764645950077 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 2589, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5533.27232,top1_acc,-84.43199184921039 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 408})])",MACs,8047.102208,top1_acc,-84.94141619969434 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5974.65728,top1_acc,-84.17727967396841 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 3002, 19: 2985, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7173.703936,top1_acc,-84.75802343352012 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5183.899904,top1_acc,-84.35048395313297 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5443.16032,top1_acc,-83.98369842078452 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6034.491648,top1_acc,-84.40142638818135 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,4624.091392,top1_acc,-83.82068262862965 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 1040})])",MACs,9082.112256,top1_acc,-84.97198166072339 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 408})])",MACs,7608.535296,top1_acc,-84.77840040753948 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6282.217728,top1_acc,-84.55425369332654 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 2589, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5675.354368,top1_acc,-84.50331125827815 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,7886.145792,top1_acc,-85.13499745287825 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 1678, 19: 3072, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6491.40864,top1_acc,-84.53387671930719 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 2664, 22: 345, 23: 1040})])",MACs,8025.868544,top1_acc,-84.89047376464595 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 2606, 15: 1877, 16: 2564, 17: 1790, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5428.480256,top1_acc,-83.95313295975548 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7327.189248,top1_acc,-85.0636780438105 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5960.698112,top1_acc,-84.56444218033621 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5762.713856,top1_acc,-84.37086092715231 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 768, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5005.773056,top1_acc,-83.75955170657157 +"OrderedDict([(, {0: 384, 1: 320, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5644.749056,top1_acc,-84.16709118695873 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 1277, 22: 692, 23: 213})])",MACs,8259.111168,top1_acc,-85.04330106979113 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6080.49792,top1_acc,-84.51349974528782 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5791.680768,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5556.86528,top1_acc,-84.31991849210392 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8939.047168,top1_acc,-84.97198166072339 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5585.438976,top1_acc,-84.17727967396841 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 213})])",MACs,9001.240832,top1_acc,-84.97198166072339 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6290.5408,top1_acc,-84.78858889454915 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 768, 7: 256, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3032, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 2985, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,7647.922432,top1_acc,-84.98217014773306 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,4791.994624,top1_acc,-83.8920020376974 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5869.209856,top1_acc,-84.50331125827815 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7058.819328,top1_acc,-84.87009679062659 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 2985, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6427.969792,top1_acc,-84.43199184921039 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7845.185792,top1_acc,-85.02292409577178 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5364.8448,top1_acc,-84.35048395313297 +"OrderedDict([(, {0: 768, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 256, 12: 2448, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6409.750784,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 640, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 2589, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6133.844224,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 256, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6693.783808,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3032, 14: 2606, 15: 3026, 16: 1825, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 1277, 22: 345, 23: 1040})])",MACs,8917.289216,top1_acc,-85.13499745287825 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5921.376512,top1_acc,-84.67651553744268 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5206.706432,top1_acc,-84.19765664798777 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5768.87424,top1_acc,-84.36067244014264 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 640, 5: 384, 6: 768, 7: 768, 8: 640, 9: 256, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,7534.545152,top1_acc,-84.77840040753948 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6028.986624,top1_acc,-84.60519612837494 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,4869.458176,top1_acc,-84.06520631686195 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5229.709568,top1_acc,-84.28935303107488 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5428.676864,top1_acc,-84.29954151808457 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 256, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 1877, 16: 3072, 17: 2994, 18: 3002, 19: 2985, 20: 1223, 21: 2664, 22: 345, 23: 1040})])",MACs,8656.324864,top1_acc,-84.76821192052981 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5533.92768,top1_acc,-84.48293428425879 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 640, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 2606, 15: 2589, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 628, 22: 345, 23: 213})])",MACs,8203.602176,top1_acc,-85.09424350483953 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5410.982144,top1_acc,-84.16709118695873 +"OrderedDict([(, {0: 256, 1: 320, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5561.846016,top1_acc,-84.48293428425879 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5791.680768,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6179.850496,top1_acc,-84.56444218033621 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 384, 6: 576, 7: 768, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 1611, 14: 1891, 15: 2589, 16: 1825, 17: 2994, 18: 3002, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6889.081088,top1_acc,-84.6255731023943 +"OrderedDict([(, {0: 384, 1: 320, 2: 768, 3: 320, 4: 768, 5: 576, 6: 576, 7: 768, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7576.815872,top1_acc,-84.79877738155885 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6065.293568,top1_acc,-84.66632705043301 +"OrderedDict([(, {0: 384, 1: 768, 2: 192, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 768, 11: 256, 12: 3044, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 213})])",MACs,7090.669824,top1_acc,-84.44218033622008 +"OrderedDict([(, {0: 256, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,4842.1952,top1_acc,-83.95313295975548 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 3044, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5359.9296,top1_acc,-84.29954151808457 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 1542, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5419.174144,top1_acc,-84.1874681609781 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 2448, 13: 3032, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5530.913024,top1_acc,-84.12633723892003 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3044, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6056.446208,top1_acc,-84.46255731023943 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 768, 6: 768, 7: 256, 8: 640, 9: 256, 10: 768, 11: 256, 12: 2448, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 1790, 18: 1678, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6489.377024,top1_acc,-84.36067244014264 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6809.192704,top1_acc,-84.73764645950077 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 2985, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6225.529088,top1_acc,-84.58481915435557 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 320, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 192, 11: 768, 12: 1542, 13: 2465, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,7437.74848,top1_acc,-84.48293428425879 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5742.594304,top1_acc,-84.43199184921039 +"OrderedDict([(, {0: 768, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 1891, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,5147.92064,top1_acc,-84.33010697911361 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 768, 6: 576, 7: 256, 8: 768, 9: 256, 10: 192, 11: 256, 12: 2448, 13: 1611, 14: 2606, 15: 1877, 16: 1825, 17: 1790, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 1040})])",MACs,5786.962176,top1_acc,-84.04482934284259 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 320, 4: 768, 5: 576, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 3044, 13: 3032, 14: 2606, 15: 1877, 16: 2564, 17: 2994, 18: 2438, 19: 1544, 20: 1223, 21: 1277, 22: 345, 23: 213})])",MACs,6816.270592,top1_acc,-84.53387671930719 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 192, 5: 384, 6: 576, 7: 256, 8: 640, 9: 320, 10: 192, 11: 768, 12: 2448, 13: 3072, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 1678, 19: 1544, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,5789.649152,top1_acc,-84.14671421293937 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 384, 6: 576, 7: 256, 8: 256, 9: 256, 10: 192, 11: 768, 12: 3072, 13: 2465, 14: 1891, 15: 1877, 16: 1825, 17: 2994, 18: 2438, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,6351.882496,top1_acc,-84.66632705043301 +"OrderedDict([(, {0: 384, 1: 320, 2: 256, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 692, 23: 213})])",MACs,7668.041984,top1_acc,-84.90066225165563 +"OrderedDict([(, {0: 384, 1: 256, 2: 192, 3: 320, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 192, 11: 256, 12: 3072, 13: 3072, 14: 1891, 15: 1877, 16: 2564, 17: 2994, 18: 3002, 19: 3072, 20: 1223, 21: 628, 22: 345, 23: 213})])",MACs,7081.822464,top1_acc,-84.71726948548141 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 320, 4: 192, 5: 384, 6: 768, 7: 768, 8: 256, 9: 320, 10: 768, 11: 768, 12: 3044, 13: 3072, 14: 3038, 15: 2589, 16: 3072, 17: 2994, 18: 3002, 19: 3072, 20: 2035, 21: 2664, 22: 345, 23: 213})])",MACs,8646.88768,top1_acc,-84.89047376464595 +"OrderedDict([(, {0: 256, 1: 320, 2: 256, 3: 320, 4: 640, 5: 384, 6: 576, 7: 256, 8: 256, 9: 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b/eftnas-s1-bert-base-mrpc/EFTNAS_S1_subnet.pth new file mode 100644 index 0000000000000000000000000000000000000000..556b1cc93e56aee63ccc0dde43a8360b9de25c54 --- /dev/null +++ b/eftnas-s1-bert-base-mrpc/EFTNAS_S1_subnet.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e62eaed5e9d73252a7167cfc5608d729fef39615c15ccb0f9b170a2fe8899f2b +size 961 diff --git a/eftnas-s1-bert-base-mrpc/README.md b/eftnas-s1-bert-base-mrpc/README.md new file mode 100644 index 0000000000000000000000000000000000000000..4872ed2e9a3e42a3be81e2ba01da56654243c770 --- /dev/null +++ b/eftnas-s1-bert-base-mrpc/README.md @@ -0,0 +1,122 @@ +--- +language: +- en +license: apache-2.0 +tags: +- generated_from_trainer +datasets: +- glue +metrics: +- accuracy +- f1 +model-index: +- name: tryv3_20epochs + results: + - task: + name: Text Classification + type: text-classification + dataset: + name: GLUE MRPC + type: glue + config: mrpc + split: validation + args: mrpc + metrics: + - name: Accuracy + type: accuracy + value: 0.8259803921568627 + - name: F1 + type: f1 + value: 0.880672268907563 +--- + + + +# tryv3_20epochs + +This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE MRPC dataset. +It achieves the following results on the evaluation set: +- Loss: 0.8979 +- Accuracy: 0.8260 +- F1: 0.8807 +- Combined Score: 0.8533 + +## Model description + +More information needed + +## Intended uses & limitations + +More information needed + +## Training and evaluation data + +More information needed + +## Training procedure + +### Training hyperparameters + +The following hyperparameters were used during training: +- learning_rate: 2e-05 +- train_batch_size: 32 +- eval_batch_size: 128 +- seed: 42 +- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 +- lr_scheduler_type: linear +- num_epochs: 30 +- mixed_precision_training: Native AMP + +### Training results + +| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score | | +|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| +| No log | 1.0 | 115 | 0.4635 | 0.8235 | 0.8746 | 0.8490 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| No log | 1.0 | 115 | 0.4038 | 0.8358 | 0.8835 | 0.8596 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| No log | 2.0 | 230 | 0.4734 | 0.8235 | 0.875 | 0.8493 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| No log | 2.0 | 230 | 0.3589 | 0.8480 | 0.8946 | 0.8713 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| No log | 3.0 | 345 | 0.9022 | 0.8039 | 0.8680 | 0.8360 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| No log | 3.0 | 345 | 0.6409 | 0.8505 | 0.8982 | 0.8743 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| No log | 4.0 | 460 | 0.7340 | 0.8407 | 0.8885 | 0.8646 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| No log | 4.0 | 460 | 0.6669 | 0.8578 | 0.9017 | 0.8798 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.6907 | 5.0 | 575 | 0.8398 | 0.8235 | 0.8788 | 0.8512 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.6907 | 5.0 | 575 | 0.6096 | 0.8799 | 0.9154 | 0.8976 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.6907 | 6.0 | 690 | 1.0233 | 0.8186 | 0.8733 | 0.8460 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.6907 | 6.0 | 690 | 0.8278 | 0.8407 | 0.8885 | 0.8646 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.6907 | 7.0 | 805 | 0.9062 | 0.8137 | 0.8628 | 0.8383 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.6907 | 7.0 | 805 | 0.6970 | 0.8456 | 0.8885 | 0.8670 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.6907 | 8.0 | 920 | 0.9299 | 0.8235 | 0.8763 | 0.8499 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.6907 | 8.0 | 920 | 0.7926 | 0.8456 | 0.8945 | 0.8700 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0889 | 9.0 | 1035 | 0.9827 | 0.8211 | 0.8765 | 0.8488 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.0889 | 9.0 | 1035 | 0.7439 | 0.8529 | 0.8980 | 0.8755 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0889 | 10.0 | 1150 | 0.8922 | 0.8284 | 0.8810 | 0.8547 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.0889 | 10.0 | 1150 | 0.6456 | 0.8603 | 0.9012 | 0.8808 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0889 | 11.0 | 1265 | 0.9563 | 0.8211 | 0.8773 | 0.8492 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.0889 | 11.0 | 1265 | 0.6870 | 0.8554 | 0.8998 | 0.8776 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0889 | 12.0 | 1380 | 0.9069 | 0.8260 | 0.8790 | 0.8525 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.0889 | 12.0 | 1380 | 0.5972 | 0.8676 | 0.9056 | 0.8866 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0889 | 13.0 | 1495 | 0.9532 | 0.8235 | 0.8796 | 0.8516 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.0889 | 13.0 | 1495 | 0.6416 | 0.8652 | 0.9047 | 0.8849 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0339 | 14.0 | 1610 | 0.9255 | 0.8260 | 0.8786 | 0.8523 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.0339 | 14.0 | 1610 | 0.7535 | 0.8578 | 0.9014 | 0.8796 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0339 | 15.0 | 1725 | 0.9056 | 0.8211 | 0.8748 | 0.8479 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.0339 | 15.0 | 1725 | 0.6562 | 0.8603 | 0.9002 | 0.8802 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0339 | 16.0 | 1840 | 0.9582 | 0.8088 | 0.8704 | 0.8396 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.0339 | 16.0 | 1840 | 0.7180 | 0.8554 | 0.8995 | 0.8774 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0339 | 17.0 | 1955 | 0.9102 | 0.8309 | 0.8829 | 0.8569 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.0339 | 17.0 | 1955 | 0.6792 | 0.8627 | 0.9038 | 0.8833 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0195 | 18.0 | 2070 | 0.8795 | 0.8284 | 0.8810 | 0.8547 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.0195 | 18.0 | 2070 | 0.6670 | 0.8652 | 0.9050 | 0.8851 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0195 | 19.0 | 2185 | 0.9087 | 0.8235 | 0.8784 | 0.8510 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.0195 | 19.0 | 2185 | 0.6763 | 0.8627 | 0.9038 | 0.8833 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0195 | 20.0 | 2300 | 0.9082 | 0.8235 | 0.8784 | 0.8510 | OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 192, 11: 192, 12: 995, 13: 930, 14: 928, 15: 931, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})]) | +| 0.0195 | 20.0 | 2300 | 0.6762 | 0.8627 | 0.9038 | 0.8833 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | + + +### Framework versions + +- Transformers 4.29.1 +- Pytorch 1.12.1 +- Datasets 2.13.1 +- Tokenizers 0.13.3 diff --git a/eftnas-s1-bert-base-mrpc/all_results.json b/eftnas-s1-bert-base-mrpc/all_results.json new file mode 100644 index 0000000000000000000000000000000000000000..0e5e49fcf28fba0a67f98a757a2cca41457565d2 --- /dev/null +++ b/eftnas-s1-bert-base-mrpc/all_results.json @@ -0,0 +1,16 @@ +{ + "epoch": 20.0, + "eval_accuracy": 0.8259803921568627, + "eval_combined_score": 0.8533263305322129, + "eval_f1": 0.880672268907563, + "eval_loss": 0.8979202508926392, + "eval_runtime": 0.3875, + "eval_samples": 408, + "eval_samples_per_second": 1053.006, + "eval_steps_per_second": 10.324, + "train_loss": 0.18312535887179168, + "train_runtime": 4630.0259, + "train_samples": 3668, + "train_samples_per_second": 15.844, + "train_steps_per_second": 0.497 +} \ No newline at end of file diff --git a/eftnas-s1-bert-base-mrpc/cache_MACs.csv b/eftnas-s1-bert-base-mrpc/cache_MACs.csv new file mode 100644 index 0000000000000000000000000000000000000000..59493e913caf17814feec5171bdbb97ffa732a4a --- /dev/null +++ b/eftnas-s1-bert-base-mrpc/cache_MACs.csv @@ -0,0 +1,959 @@ +"(0, 0, 0, 0, 0, 2, 0, 2, 2, 1, 3, 0, 4, 4, 3, 1, 1, 2, 0, 0, 0, 2, 2, 1)",8334.4768 +"(0, 1, 0, 0, 0, 0, 1, 3, 0, 2, 2, 3, 2, 0, 0, 1, 0, 3, 0, 4, 4, 4, 1, 3)",7681.08288 +"(0, 1, 0, 0, 0, 1, 2, 2, 0, 1, 4, 2, 3, 3, 2, 1, 0, 2, 2, 4, 2, 2, 0, 0)",8193.639936 +"(0, 0, 0, 0, 0, 1, 0, 3, 0, 1, 3, 1, 3, 4, 4, 0, 2, 3, 3, 3, 1, 1, 2, 4)",7180.649984 +"(0, 1, 0, 0, 0, 2, 0, 3, 1, 3, 3, 2, 1, 4, 3, 3, 4, 0, 1, 2, 0, 4, 3, 3)",7033.456128 +"(0, 1, 0, 0, 0, 0, 2, 3, 2, 1, 0, 1, 2, 1, 2, 0, 3, 3, 3, 4, 1, 0, 4, 1)",7921.27232 +"(0, 1, 0, 0, 0, 1, 0, 2, 0, 0, 3, 2, 4, 0, 1, 4, 3, 2, 2, 4, 2, 2, 0, 3)",7550.66624 +"(0, 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3, 3, 3, 2, 1, 1, 1, 1, 4, 1, 2, 2)",7991.592448 +"(0, 1, 0, 0, 0, 1, 1, 2, 0, 3, 3, 0, 1, 4, 1, 0, 1, 3, 4, 1, 1, 4, 2, 3)",7578.84672 +"(0, 0, 0, 0, 0, 1, 1, 3, 0, 1, 3, 0, 1, 4, 4, 3, 0, 2, 0, 4, 2, 4, 2, 1)",7453.148672 +"(0, 1, 0, 0, 0, 2, 1, 2, 1, 2, 1, 1, 2, 2, 1, 3, 4, 4, 1, 2, 3, 2, 4, 0)",7392.593408 +"(0, 1, 0, 0, 0, 0, 0, 1, 2, 0, 1, 3, 0, 2, 2, 4, 3, 1, 0, 2, 4, 4, 3, 0)",7674.594816 +"(0, 0, 0, 0, 0, 0, 1, 2, 0, 2, 1, 3, 0, 4, 4, 1, 3, 4, 2, 3, 1, 1, 0, 0)",8047.822336 +"(0, 0, 0, 0, 0, 1, 2, 1, 0, 3, 3, 0, 2, 1, 0, 4, 4, 1, 0, 0, 0, 2, 4, 0)",8608.810496 +"(0, 1, 0, 0, 0, 0, 0, 0, 1, 3, 2, 3, 4, 3, 0, 3, 3, 4, 3, 3, 4, 4, 1, 2)",6324.16 +"(0, 1, 0, 0, 0, 1, 1, 2, 0, 2, 2, 2, 0, 3, 2, 3, 4, 1, 2, 2, 1, 0, 2, 4)",7857.440256 +"(0, 1, 0, 0, 0, 2, 2, 2, 2, 3, 4, 2, 4, 3, 0, 3, 3, 2, 0, 3, 2, 1, 1, 0)",7734.429184 +"(0, 1, 0, 0, 0, 2, 0, 3, 1, 1, 3, 1, 3, 1, 4, 4, 0, 2, 2, 2, 4, 0, 4, 2)",7306.806784 +"(0, 0, 0, 0, 0, 0, 2, 0, 1, 1, 1, 1, 3, 2, 4, 2, 3, 3, 3, 2, 3, 2, 1, 3)",7067.796992 +"(0, 1, 0, 0, 0, 1, 0, 3, 1, 1, 2, 1, 0, 2, 4, 1, 3, 1, 0, 1, 0, 1, 4, 4)",8218.936832 +"(0, 0, 0, 0, 0, 1, 1, 2, 0, 3, 3, 2, 0, 3, 1, 2, 1, 2, 0, 3, 4, 2, 1, 3)",7820.871168 +"(0, 1, 0, 0, 0, 1, 2, 3, 0, 2, 1, 1, 3, 2, 1, 2, 3, 2, 1, 1, 4, 3, 2, 4)",7352.223232 +"(0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 4, 1, 3, 3, 4, 1, 4, 4, 0, 3, 0, 1, 3, 4)",7247.627776 +"(0, 1, 0, 0, 0, 2, 1, 0, 1, 0, 2, 0, 0, 4, 1, 3, 0, 2, 0, 2, 2, 2, 2, 4)",8069.38368 +"(0, 1, 0, 0, 0, 2, 0, 2, 1, 1, 2, 1, 3, 4, 1, 3, 3, 2, 2, 2, 3, 0, 2, 2)",7475.29984 +"(0, 0, 0, 0, 0, 2, 1, 0, 2, 0, 0, 2, 0, 2, 3, 4, 0, 3, 3, 4, 1, 2, 2, 1)",7739.40992 +"(0, 1, 0, 0, 0, 0, 1, 2, 1, 3, 1, 1, 2, 1, 1, 4, 0, 0, 4, 1, 2, 4, 3, 3)",7535.396352 +"(0, 1, 0, 0, 0, 2, 0, 3, 0, 2, 0, 1, 1, 2, 3, 2, 3, 4, 3, 0, 1, 4, 2, 4)",7382.435328 +"(0, 0, 0, 0, 0, 1, 2, 2, 0, 3, 4, 0, 0, 0, 3, 1, 1, 2, 3, 3, 3, 0, 4, 4)",7660.832256 +"(0, 1, 0, 0, 0, 1, 0, 2, 2, 0, 4, 2, 3, 4, 1, 4, 1, 3, 1, 1, 1, 4, 3, 3)",7105.414656 +"(0, 0, 0, 0, 0, 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"324 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"330 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"333 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"334 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"339 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"340 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"342 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"343 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"347 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"348 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "359 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"359 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "361 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"361 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "362 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"362 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "363 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"363 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"364 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"365 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "367 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"367 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"370 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"371 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "373 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"373 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"374 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"375 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "377 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"377 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"380 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"381 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "393 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"383 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"384 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "386 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"386 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "387 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"387 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "395 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"388 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"389 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "391 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"391 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "392 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"392 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"393 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "394 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"394 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"395 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "397 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"397 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "398 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"398 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "399 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"399 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "400 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"400 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "402 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"402 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "403 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"403 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "404 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"404 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"405 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"406 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "408 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"408 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"411 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"412 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "414 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"414 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"415 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"416 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "418 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"418 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"421 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"422 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "434 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"424 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"425 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "427 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"427 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "428 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"428 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "436 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"429 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"430 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "432 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"432 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "433 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"433 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"434 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "435 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"435 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"436 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "438 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"438 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "439 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"439 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "440 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"440 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "441 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"441 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "443 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"443 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "444 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"444 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "445 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"445 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"446 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"447 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "449 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"449 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"452 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"453 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "455 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"455 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"456 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"457 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "459 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"459 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" -> "461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "491 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"462 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"463 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "475 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"465 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"466 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "468 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"468 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "469 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"469 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "477 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"470 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"471 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "473 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"473 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "474 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"474 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "483 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"475 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "476 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"476 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "478 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"477 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "478 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"478 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "479 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"479 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "480 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"480 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "481 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"481 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "482 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"482 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "483 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"483 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "484 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"484 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "485 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"485 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "486 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"486 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "489 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"487 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "489 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"488 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "489 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"489 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "490 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"490 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "491 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"491 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "492 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"492 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "495 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"492 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "324 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"324 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" -> "329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "330 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "331 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "333 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3072})])",MACs,7727.351296,top1_acc,-88.77551020408163 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 512, 9: 320, 10: 384, 11: 704, 12: 2618, 13: 2097, 14: 2632, 15: 1494, 16: 872, 17: 787, 18: 1955, 19: 1117, 20: 3072, 21: 291, 22: 678, 23: 1206})])",MACs,6944.851456,top1_acc,-89.87993138936535 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 640, 8: 576, 9: 640, 10: 192, 11: 704, 12: 2618, 13: 930, 14: 3072, 15: 2127, 16: 2645, 17: 1362, 18: 1955, 19: 2494, 20: 409, 21: 3072, 22: 3072, 23: 1925})])",MACs,8512.07936,top1_acc,-89.84509466437176 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 512, 10: 768, 11: 704, 12: 2618, 13: 1520, 14: 3072, 15: 2664, 16: 872, 17: 2574, 18: 672, 19: 1117, 20: 2391, 21: 1395, 22: 1324, 23: 308})])",MACs,7607.813632,top1_acc,-89.5368782161235 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 640, 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3072})])",MACs,8523.810304,top1_acc,-90.1023890784983 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 768, 8: 512, 9: 768, 10: 384, 11: 768, 12: 995, 13: 3072, 14: 3072, 15: 3072, 16: 1456, 17: 1362, 18: 1955, 19: 3072, 20: 866, 21: 2153, 22: 678, 23: 3072})])",MACs,8507.360768,top1_acc,-88.62068965517241 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 768, 9: 768, 10: 192, 11: 768, 12: 1524, 13: 1520, 14: 1526, 15: 2127, 16: 2645, 17: 2574, 18: 2561, 19: 2494, 20: 409, 21: 2153, 22: 1324, 23: 1206})])",MACs,7991.592448,top1_acc,-89.04109589041096 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 640, 8: 768, 9: 320, 10: 384, 11: 768, 12: 2618, 13: 930, 14: 2632, 15: 3072, 16: 2645, 17: 1362, 18: 672, 19: 2494, 20: 2391, 21: 291, 22: 1324, 23: 642})])",MACs,7578.84672,top1_acc,-89.96539792387543 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 768, 9: 640, 10: 384, 11: 768, 12: 2618, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 1925})])",MACs,7453.148672,top1_acc,-89.6434634974533 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 640, 8: 576, 9: 512, 10: 576, 11: 704, 12: 2120, 13: 2097, 14: 2632, 15: 1494, 16: 872, 17: 787, 18: 2561, 19: 1791, 20: 866, 21: 1395, 22: 300, 23: 3072})])",MACs,7392.593408,top1_acc,-89.5368782161235 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 512, 9: 768, 10: 576, 11: 192, 12: 3072, 13: 2097, 14: 2117, 15: 931, 16: 1456, 17: 2574, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 3072})])",MACs,7674.594816,top1_acc,-90.18932874354562 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 640, 8: 768, 9: 512, 10: 576, 11: 192, 12: 3072, 13: 930, 14: 928, 15: 2664, 16: 1456, 17: 787, 18: 1955, 19: 1117, 20: 2391, 21: 2153, 22: 3072, 23: 3072})])",MACs,8047.822336,top1_acc,-88.9655172413793 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 704, 8: 768, 9: 320, 10: 384, 11: 768, 12: 2120, 13: 2621, 14: 3072, 15: 931, 16: 872, 17: 2574, 18: 3072, 19: 3072, 20: 3072, 21: 1395, 22: 300, 23: 3072})])",MACs,8608.810496,top1_acc,-89.3103448275862 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 448, 11: 192, 12: 995, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 1206})])",MACs,6324.16,top1_acc,-87.60611205432937 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 640, 8: 768, 9: 512, 10: 448, 11: 512, 12: 3072, 13: 1520, 14: 2117, 15: 1494, 16: 872, 17: 2574, 18: 1955, 19: 1791, 20: 2391, 21: 3072, 22: 1324, 23: 308})])",MACs,7857.440256,top1_acc,-88.9267461669506 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 640, 8: 512, 9: 320, 10: 192, 11: 512, 12: 995, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 1117, 20: 1627, 21: 2153, 22: 2070, 23: 3072})])",MACs,7734.429184,top1_acc,-88.73949579831934 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 640, 10: 384, 11: 704, 12: 1524, 13: 2621, 14: 928, 15: 931, 16: 3072, 17: 2019, 18: 1955, 19: 1791, 20: 409, 21: 3072, 22: 300, 23: 1206})])",MACs,7306.806784,top1_acc,-90.06849315068493 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 640, 10: 576, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 2127, 16: 1456, 17: 1362, 18: 1245, 19: 1791, 20: 866, 21: 1395, 22: 2070, 23: 642})])",MACs,7067.796992,top1_acc,-89.93055555555554 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 576, 9: 640, 10: 448, 11: 704, 12: 3072, 13: 2097, 14: 928, 15: 2664, 16: 1456, 17: 2574, 18: 3072, 19: 2494, 20: 3072, 21: 2153, 22: 300, 23: 308})])",MACs,8218.936832,top1_acc,-89.87993138936535 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 640, 8: 768, 9: 320, 10: 384, 11: 512, 12: 3072, 13: 1520, 14: 2632, 15: 2127, 16: 2645, 17: 2019, 18: 3072, 19: 1117, 20: 409, 21: 1395, 22: 2070, 23: 642})])",MACs,7820.871168,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 512, 8: 768, 9: 512, 10: 576, 11: 704, 12: 1524, 13: 2097, 14: 2632, 15: 2127, 16: 1456, 17: 2019, 18: 2561, 19: 2494, 20: 409, 21: 692, 22: 1324, 23: 308})])",MACs,7352.223232,top1_acc,-89.87993138936535 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 768, 8: 768, 9: 768, 10: 192, 11: 704, 12: 1524, 13: 1520, 14: 928, 15: 2664, 16: 872, 17: 787, 18: 3072, 19: 1117, 20: 3072, 21: 2153, 22: 678, 23: 308})])",MACs,7247.627776,top1_acc,-88.50771869639793 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 930, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 308})])",MACs,8069.38368,top1_acc,-90.75342465753423 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 640, 10: 448, 11: 704, 12: 1524, 13: 930, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 1955, 19: 1791, 20: 866, 21: 3072, 22: 1324, 23: 1206})])",MACs,7475.29984,top1_acc,-89.61937716262976 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 512, 9: 768, 10: 768, 11: 512, 12: 3072, 13: 2097, 14: 1526, 15: 931, 16: 3072, 17: 1362, 18: 1245, 19: 579, 20: 2391, 21: 1395, 22: 1324, 23: 1925})])",MACs,7739.40992,top1_acc,-89.81001727115718 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 640, 8: 576, 9: 320, 10: 576, 11: 704, 12: 2120, 13: 2621, 14: 2632, 15: 931, 16: 3072, 17: 3072, 18: 672, 19: 2494, 20: 1627, 21: 291, 22: 678, 23: 642})])",MACs,7535.396352,top1_acc,-89.81001727115718 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 512, 10: 768, 11: 704, 12: 2618, 13: 2097, 14: 1526, 15: 2127, 16: 1456, 17: 787, 18: 1245, 19: 3072, 20: 2391, 21: 291, 22: 1324, 23: 308})])",MACs,7382.435328,top1_acc,-88.58131487889273 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 640, 8: 768, 9: 320, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1526, 15: 2664, 16: 2645, 17: 2019, 18: 1245, 19: 1117, 20: 866, 21: 3072, 22: 300, 23: 308})])",MACs,7660.832256,top1_acc,-90.12131715771231 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 640, 8: 512, 9: 768, 10: 192, 11: 512, 12: 1524, 13: 930, 14: 2632, 15: 931, 16: 2645, 17: 1362, 18: 2561, 19: 2494, 20: 2391, 21: 291, 22: 678, 23: 642})])",MACs,7105.414656,top1_acc,-88.8888888888889 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 2120, 13: 2621, 14: 3072, 15: 931, 16: 872, 17: 2574, 18: 3072, 19: 3072, 20: 3072, 21: 1395, 22: 300, 23: 3072})])",MACs,8663.336448,top1_acc,-89.50086058519794 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 3072, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 2391, 21: 3072, 22: 1324, 23: 308})])",MACs,9192.01536,top1_acc,-90.37800687285223 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 640, 8: 768, 9: 768, 10: 192, 11: 704, 12: 1524, 13: 1520, 14: 928, 15: 2664, 16: 872, 17: 787, 18: 3072, 19: 1791, 20: 3072, 21: 2153, 22: 678, 23: 308})])",MACs,7325.615616,top1_acc,-88.38821490467937 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 640, 8: 512, 9: 320, 10: 384, 11: 768, 12: 2618, 13: 930, 14: 2632, 15: 3072, 16: 2645, 17: 1362, 18: 672, 19: 2494, 20: 2391, 21: 291, 22: 1324, 23: 642})])",MACs,7469.794816,top1_acc,-89.42807625649914 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 640, 10: 384, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 3072, 16: 3072, 17: 2019, 18: 1955, 19: 1791, 20: 409, 21: 3072, 22: 300, 23: 1206})])",MACs,7651.984896,top1_acc,-90.27777777777779 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2618, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,7003.76832,top1_acc,-90.3114186851211 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 640, 8: 768, 9: 512, 10: 576, 11: 192, 12: 3072, 13: 930, 14: 3072, 15: 2664, 16: 1456, 17: 787, 18: 1955, 19: 1117, 20: 2391, 21: 2153, 22: 3072, 23: 1206})])",MACs,8102.47936,top1_acc,-89.76109215017065 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 768, 9: 640, 10: 768, 11: 704, 12: 3072, 13: 2621, 14: 2117, 15: 3072, 16: 1456, 17: 1362, 18: 1245, 19: 1791, 20: 2391, 21: 3072, 22: 300, 23: 1925})])",MACs,8455.783936,top1_acc,-89.79591836734693 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 512, 9: 768, 10: 768, 11: 512, 12: 3072, 13: 2097, 14: 1526, 15: 931, 16: 3072, 17: 1362, 18: 1245, 19: 1791, 20: 409, 21: 3072, 22: 1324, 23: 1925})])",MACs,7917.733376,top1_acc,-89.77469670710572 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 512, 8: 768, 9: 640, 10: 768, 11: 704, 12: 2618, 13: 1520, 14: 3072, 15: 2664, 16: 2139, 17: 2574, 18: 1245, 19: 1117, 20: 2391, 21: 1395, 22: 1324, 23: 308})])",MACs,8051.36128,top1_acc,-90.37800687285223 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 704, 8: 768, 9: 320, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 3072, 15: 931, 16: 872, 17: 2574, 18: 3072, 19: 3072, 20: 3072, 21: 1395, 22: 300, 23: 3072})])",MACs,8850.507264,top1_acc,-89.04109589041096 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 768, 9: 768, 10: 576, 11: 192, 12: 3072, 13: 2097, 14: 3072, 15: 2664, 16: 3072, 17: 2574, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 2070, 23: 3072})])",MACs,8903.525888,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 512, 9: 320, 10: 384, 11: 704, 12: 2618, 13: 2097, 14: 2632, 15: 1494, 16: 872, 17: 3072, 18: 1955, 19: 1117, 20: 3072, 21: 291, 22: 678, 23: 1206})])",MACs,7394.100736,top1_acc,-89.69072164948454 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 640, 8: 512, 9: 320, 10: 384, 11: 512, 12: 3072, 13: 930, 14: 2632, 15: 2127, 16: 2645, 17: 2019, 18: 3072, 19: 2494, 20: 409, 21: 1395, 22: 678, 23: 642})])",MACs,7592.871424,top1_acc,-89.84509466437176 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 512, 10: 576, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 2127, 16: 1456, 17: 787, 18: 2561, 19: 1791, 20: 866, 21: 1395, 22: 2070, 23: 642})])",MACs,7131.694592,top1_acc,-89.00523560209423 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 512, 12: 2618, 13: 930, 14: 1526, 15: 1494, 16: 872, 17: 3072, 18: 2561, 19: 1791, 20: 3072, 21: 291, 22: 678, 23: 308})])",MACs,6967.789056,top1_acc,-89.19382504288164 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 704, 8: 576, 9: 640, 10: 576, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 2127, 16: 1456, 17: 1362, 18: 1245, 19: 1791, 20: 866, 21: 1395, 22: 2070, 23: 642})])",MACs,7013.27104,top1_acc,-89.3542757417103 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 512, 9: 640, 10: 768, 11: 704, 12: 2120, 13: 930, 14: 2117, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 579, 20: 1627, 21: 1395, 22: 300, 23: 1925})])",MACs,6798.64064,top1_acc,-89.15254237288136 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 512, 10: 576, 11: 704, 12: 2120, 13: 2097, 14: 2632, 15: 1494, 16: 872, 17: 787, 18: 2561, 19: 1117, 20: 866, 21: 1395, 22: 300, 23: 3072})])",MACs,7314.605568,top1_acc,-89.5368782161235 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 320, 10: 448, 11: 768, 12: 2618, 13: 930, 14: 928, 15: 3072, 16: 3072, 17: 2574, 18: 2561, 19: 579, 20: 866, 21: 1395, 22: 300, 23: 3072})])",MACs,7836.4032,top1_acc,-88.66328257191202 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 768, 9: 640, 10: 384, 11: 704, 12: 1524, 13: 1520, 14: 928, 15: 931, 16: 2139, 17: 1362, 18: 1245, 19: 1117, 20: 2391, 21: 2153, 22: 1324, 23: 308})])",MACs,6848.448,top1_acc,-88.73720136518772 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 512, 9: 640, 10: 384, 11: 768, 12: 2618, 13: 930, 14: 2632, 15: 1494, 16: 872, 17: 787, 18: 3072, 19: 1117, 20: 3072, 21: 291, 22: 1324, 23: 1925})])",MACs,7394.231808,top1_acc,-89.19382504288164 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 448, 11: 192, 12: 995, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 3072})])",MACs,6269.502976,top1_acc,-87.9864636209814 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 512, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 3072, 15: 931, 16: 2139, 17: 2574, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 1925})])",MACs,6650.267136,top1_acc,-89.3835616438356 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 640, 10: 384, 11: 704, 12: 1524, 13: 2621, 14: 928, 15: 931, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 3072, 21: 1395, 22: 300, 23: 1206})])",MACs,7262.373376,top1_acc,-89.419795221843 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 512, 10: 384, 11: 704, 12: 1524, 13: 930, 14: 928, 15: 3072, 16: 872, 17: 1362, 18: 672, 19: 1117, 20: 2391, 21: 2153, 22: 1324, 23: 308})])",MACs,6737.102336,top1_acc,-88.73720136518772 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 2120, 13: 930, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 308})])",MACs,7827.686912,top1_acc,-90.75342465753423 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 512, 8: 512, 9: 512, 10: 448, 11: 192, 12: 2120, 13: 3072, 14: 2117, 15: 931, 16: 1456, 17: 1362, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6452.151808,top1_acc,-89.04347826086956 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 512, 12: 2618, 13: 930, 14: 1526, 15: 1494, 16: 872, 17: 787, 18: 2561, 19: 1791, 20: 3072, 21: 291, 22: 678, 23: 642})])",MACs,6584.206848,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 640, 8: 768, 9: 768, 10: 192, 11: 512, 12: 1524, 13: 1520, 14: 2632, 15: 931, 16: 2645, 17: 1362, 18: 2561, 19: 1117, 20: 2391, 21: 291, 22: 2070, 23: 308})])",MACs,7267.747328,top1_acc,-88.42832469775476 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 640, 8: 576, 9: 640, 10: 576, 11: 704, 12: 2120, 13: 2097, 14: 2632, 15: 1494, 16: 872, 17: 1362, 18: 1245, 19: 1791, 20: 866, 21: 1395, 22: 300, 23: 3072})])",MACs,7328.695808,top1_acc,-89.96539792387543 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 768, 11: 512, 12: 3072, 13: 2097, 14: 1526, 15: 931, 16: 3072, 17: 1362, 18: 1955, 19: 1791, 20: 2391, 21: 3072, 22: 1324, 23: 1925})])",MACs,8501.528064,top1_acc,-89.93055555555554 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 640, 8: 768, 9: 320, 10: 384, 11: 768, 12: 2618, 13: 930, 14: 2632, 15: 2664, 16: 2645, 17: 1362, 18: 672, 19: 2494, 20: 2391, 21: 291, 22: 1324, 23: 642})])",MACs,7498.630656,top1_acc,-89.7391304347826 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 768, 9: 640, 10: 448, 11: 704, 12: 1524, 13: 930, 14: 928, 15: 3072, 16: 2139, 17: 2574, 18: 3072, 19: 2494, 20: 3072, 21: 2153, 22: 1324, 23: 308})])",MACs,8210.023936,top1_acc,-89.60817717206135 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 640, 8: 512, 9: 640, 10: 448, 11: 704, 12: 1524, 13: 930, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 1245, 19: 579, 20: 866, 21: 1395, 22: 1324, 23: 1206})])",MACs,6713.181696,top1_acc,-89.19860627177701 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 640, 8: 768, 9: 640, 10: 192, 11: 512, 12: 1524, 13: 1520, 14: 2117, 15: 3072, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 1395, 22: 3072, 23: 3072})])",MACs,8273.856,top1_acc,-88.73720136518772 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 576, 9: 640, 10: 384, 11: 704, 12: 3072, 13: 2097, 14: 928, 15: 2664, 16: 1456, 17: 1362, 18: 1245, 19: 1117, 20: 2391, 21: 2153, 22: 300, 23: 308})])",MACs,7189.56288,top1_acc,-90.0523560209424 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 768, 9: 640, 10: 768, 11: 768, 12: 2120, 13: 2621, 14: 2632, 15: 3072, 16: 1456, 17: 1362, 18: 1245, 19: 579, 20: 2391, 21: 3072, 22: 300, 23: 1925})])",MACs,8213.366272,top1_acc,-90.56603773584906 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 512, 9: 320, 10: 384, 11: 704, 12: 2618, 13: 930, 14: 2117, 15: 3072, 16: 2645, 17: 1362, 18: 672, 19: 2494, 20: 2391, 21: 291, 22: 1324, 23: 642})])",MACs,7286.752768,top1_acc,-88.9655172413793 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 640, 10: 768, 11: 704, 12: 2120, 13: 930, 14: 2117, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,7474.120192,top1_acc,-90.01692047377327 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 768, 9: 640, 10: 384, 11: 704, 12: 2120, 13: 930, 14: 3072, 15: 3072, 16: 872, 17: 2019, 18: 1245, 19: 1117, 20: 2391, 21: 2153, 22: 678, 23: 308})])",MACs,7445.15328,top1_acc,-89.6434634974533 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 512, 9: 768, 10: 768, 11: 512, 12: 1524, 13: 2097, 14: 1526, 15: 931, 16: 2645, 17: 1362, 18: 2561, 19: 1791, 20: 2391, 21: 3072, 22: 1324, 23: 308})])",MACs,7887.1936,top1_acc,-89.81001727115718 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 640, 8: 512, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 1520, 14: 3072, 15: 931, 16: 2645, 17: 2574, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 2070, 23: 1925})])",MACs,7237.862912,top1_acc,-89.69072164948454 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 768, 10: 448, 11: 192, 12: 3072, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 1117, 20: 1627, 21: 291, 22: 1324, 23: 3072})])",MACs,7562.921472,top1_acc,-89.5368782161235 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 3072, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 2391, 21: 1395, 22: 1324, 23: 308})])",MACs,8835.040768,top1_acc,-90.53356282271946 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 512, 9: 640, 10: 768, 11: 704, 12: 2618, 13: 2621, 14: 2117, 15: 3072, 16: 1456, 17: 1362, 18: 1245, 19: 579, 20: 2391, 21: 3072, 22: 300, 23: 1206})])",MACs,7877.821952,top1_acc,-89.6434634974533 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 640, 8: 768, 9: 640, 10: 384, 11: 768, 12: 2618, 13: 1520, 14: 2632, 15: 3072, 16: 2645, 17: 1362, 18: 672, 19: 2494, 20: 2391, 21: 291, 22: 1324, 23: 642})])",MACs,7858.423296,top1_acc,-89.99999999999999 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 576, 9: 640, 10: 448, 11: 704, 12: 995, 13: 2621, 14: 928, 15: 931, 16: 3072, 17: 2019, 18: 1955, 19: 1791, 20: 409, 21: 3072, 22: 300, 23: 1206})])",MACs,7284.59008,top1_acc,-89.57264957264958 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 512, 12: 2618, 13: 1520, 14: 1526, 15: 1494, 16: 872, 17: 787, 18: 2561, 19: 1791, 20: 3072, 21: 291, 22: 678, 23: 308})])",MACs,6634.538496,top1_acc,-88.58131487889273 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 640, 10: 576, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 2127, 16: 1456, 17: 1362, 18: 1245, 19: 1791, 20: 866, 21: 1395, 22: 2070, 23: 642})])",MACs,7122.322944,top1_acc,-89.89547038327525 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8578.401792,top1_acc,-91.37931034482759 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 768, 9: 320, 10: 576, 11: 704, 12: 2618, 13: 930, 14: 2632, 15: 3072, 16: 3072, 17: 1362, 18: 672, 19: 1117, 20: 2391, 21: 2153, 22: 1324, 23: 3072})])",MACs,8290.436608,top1_acc,-89.50086058519794 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1520, 14: 2632, 15: 2127, 16: 2645, 17: 2019, 18: 3072, 19: 1117, 20: 409, 21: 1395, 22: 2070, 23: 642})])",MACs,8175.289856,top1_acc,-90.46793760831888 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 640, 10: 576, 11: 704, 12: 2120, 13: 2097, 14: 2632, 15: 1494, 16: 872, 17: 2574, 18: 1245, 19: 1791, 20: 866, 21: 1395, 22: 300, 23: 3072})])",MACs,7594.24768,top1_acc,-90.08695652173914 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 2618, 13: 930, 14: 1526, 15: 1494, 16: 872, 17: 3072, 18: 3072, 19: 1791, 20: 3072, 21: 1395, 22: 1324, 23: 642})])",MACs,7587.03872,top1_acc,-88.8888888888889 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 640, 8: 768, 9: 640, 10: 448, 11: 768, 12: 2120, 13: 2621, 14: 2632, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 579, 20: 2391, 21: 1395, 22: 1324, 23: 1925})])",MACs,7583.892992,top1_acc,-90.15544041450777 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 512, 9: 512, 10: 576, 11: 192, 12: 2120, 13: 3072, 14: 2117, 15: 931, 16: 1456, 17: 2574, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 3072})])",MACs,7249.987072,top1_acc,-88.92733564013841 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 512, 9: 768, 10: 384, 11: 768, 12: 2120, 13: 930, 14: 2632, 15: 1494, 16: 1456, 17: 1362, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 300, 23: 308})])",MACs,7152.20736,top1_acc,-89.87993138936535 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 640, 10: 448, 11: 768, 12: 1524, 13: 2097, 14: 928, 15: 931, 16: 2139, 17: 1362, 18: 1245, 19: 1117, 20: 2391, 21: 2153, 22: 1324, 23: 308})])",MACs,7016.416768,top1_acc,-89.61937716262976 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 640, 8: 576, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 930, 14: 2632, 15: 931, 16: 3072, 17: 1362, 18: 1955, 19: 2494, 20: 2391, 21: 291, 22: 678, 23: 1925})])",MACs,7654.082048,top1_acc,-89.00343642611685 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 640, 8: 768, 9: 320, 10: 384, 11: 512, 12: 2120, 13: 1520, 14: 2632, 15: 2127, 16: 2139, 17: 2019, 18: 3072, 19: 1117, 20: 409, 21: 1395, 22: 678, 23: 642})])",MACs,7233.275392,top1_acc,-90.3448275862069 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 320, 10: 448, 11: 768, 12: 995, 13: 930, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 1791, 20: 409, 21: 1395, 22: 2070, 23: 308})])",MACs,6775.965184,top1_acc,-88.8888888888889 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 768, 8: 576, 9: 640, 10: 576, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 2127, 16: 1456, 17: 1362, 18: 1245, 19: 1791, 20: 866, 21: 3072, 22: 2070, 23: 642})])",MACs,7424.771584,top1_acc,-89.7391304347826 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7047.218688,top1_acc,-91.25874125874125 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 1524, 13: 930, 14: 928, 15: 931, 16: 2139, 17: 1362, 18: 1245, 19: 1117, 20: 2391, 21: 2153, 22: 1324, 23: 308})])",MACs,6568.871424,top1_acc,-88.0672268907563 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 1206})])",MACs,6346.376704,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 448, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 3072, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 3072})])",MACs,6602.753536,top1_acc,-88.55721393034827 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 192, 12: 995, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 1206})])",MACs,6269.634048,top1_acc,-87.75510204081631 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 640, 10: 384, 11: 704, 12: 1524, 13: 930, 14: 928, 15: 931, 16: 3072, 17: 2019, 18: 1955, 19: 1791, 20: 409, 21: 3072, 22: 300, 23: 308})])",MACs,6797.788672,top1_acc,-88.77721943048577 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 512, 8: 512, 9: 640, 10: 384, 11: 192, 12: 1524, 13: 3072, 14: 928, 15: 3072, 16: 2139, 17: 2574, 18: 1245, 19: 2494, 20: 1627, 21: 291, 22: 2070, 23: 308})])",MACs,7414.02368,top1_acc,-89.5368782161235 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 640, 8: 576, 9: 320, 10: 448, 11: 512, 12: 3072, 13: 2621, 14: 2632, 15: 3072, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 2391, 21: 3072, 22: 1324, 23: 308})])",MACs,8837.596672,top1_acc,-90.37800687285223 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 704, 8: 512, 9: 768, 10: 576, 11: 192, 12: 3072, 13: 2097, 14: 2117, 15: 931, 16: 1456, 17: 1362, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 3072})])",MACs,7409.042944,top1_acc,-89.65517241379311 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 384, 11: 512, 12: 2120, 13: 930, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 2561, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,7274.10432,top1_acc,-90.2229845626072 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 640, 8: 512, 9: 640, 10: 768, 11: 704, 12: 1524, 13: 930, 14: 2632, 15: 3072, 16: 1456, 17: 2019, 18: 1245, 19: 579, 20: 866, 21: 3072, 22: 300, 23: 1206})])",MACs,7342.654976,top1_acc,-89.04109589041096 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 704, 8: 768, 9: 768, 10: 448, 11: 192, 12: 3072, 13: 2097, 14: 3072, 15: 2664, 16: 3072, 17: 1362, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 2070, 23: 642})])",MACs,8105.690624,top1_acc,-90.6896551724138 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 768, 8: 576, 9: 640, 10: 576, 11: 768, 12: 1524, 13: 2097, 14: 928, 15: 2127, 16: 1456, 17: 1362, 18: 1245, 19: 1791, 20: 866, 21: 1395, 22: 2070, 23: 308})])",MACs,7056.655872,top1_acc,-89.89547038327525 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 512, 12: 2618, 13: 930, 14: 1526, 15: 1494, 16: 872, 17: 3072, 18: 2561, 19: 1791, 20: 3072, 21: 1395, 22: 678, 23: 308})])",MACs,7184.844288,top1_acc,-89.1156462585034 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 930, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 642})])",MACs,8080.5248,top1_acc,-90.72164948453609 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 512, 9: 640, 10: 768, 11: 704, 12: 2120, 13: 930, 14: 2117, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 579, 20: 1627, 21: 291, 22: 300, 23: 1925})])",MACs,6581.585408,top1_acc,-88.85077186963979 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 320, 10: 448, 11: 704, 12: 3072, 13: 930, 14: 2632, 15: 1494, 16: 2139, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 642})])",MACs,7788.037632,top1_acc,-90.25641025641026 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 512, 12: 2618, 13: 930, 14: 1526, 15: 1494, 16: 872, 17: 787, 18: 2561, 19: 1791, 20: 3072, 21: 1395, 22: 678, 23: 642})])",MACs,6773.999104,top1_acc,-88.1646655231561 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 640, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7238.05952,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 640, 10: 576, 11: 704, 12: 995, 13: 2097, 14: 928, 15: 2127, 16: 1456, 17: 787, 18: 1245, 19: 1791, 20: 409, 21: 1395, 22: 2070, 23: 3072})])",MACs,7265.91232,top1_acc,-87.58620689655173 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 704, 8: 576, 9: 768, 10: 384, 11: 512, 12: 2618, 13: 930, 14: 1526, 15: 1494, 16: 872, 17: 3072, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6817.3184,top1_acc,-88.62068965517241 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 640, 10: 576, 11: 192, 12: 995, 13: 930, 14: 928, 15: 2127, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 3072})])",MACs,6496.060928,top1_acc,-87.16216216216218 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 768, 10: 384, 11: 512, 12: 2618, 13: 930, 14: 1526, 15: 1494, 16: 1456, 17: 3072, 18: 2561, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6749.881856,top1_acc,-89.34707903780068 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 704, 12: 995, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 1395, 22: 2070, 23: 1206})])",MACs,6907.692544,top1_acc,-88.1646655231561 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8551.138816,top1_acc,-91.37931034482759 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 640, 8: 768, 9: 640, 10: 448, 11: 704, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 1955, 19: 579, 20: 866, 21: 1395, 22: 1324, 23: 1925})])",MACs,6768.1664,top1_acc,-87.68971332209105 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 3072, 15: 931, 16: 2139, 17: 2574, 18: 1245, 19: 1117, 20: 409, 21: 1395, 22: 2070, 23: 1925})])",MACs,7278.69184,top1_acc,-89.19382504288164 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 768, 9: 320, 10: 448, 11: 512, 12: 3072, 13: 1520, 14: 2632, 15: 2127, 16: 2645, 17: 2019, 18: 3072, 19: 1117, 20: 409, 21: 1395, 22: 2070, 23: 642})])",MACs,7875.39712,top1_acc,-90.6896551724138 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 512, 9: 640, 10: 384, 11: 704, 12: 2618, 13: 2097, 14: 2632, 15: 1494, 16: 872, 17: 1362, 18: 1955, 19: 1117, 20: 3072, 21: 291, 22: 678, 23: 1206})])",MACs,7194.215936,top1_acc,-90.18932874354562 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 768, 10: 384, 11: 512, 12: 2618, 13: 930, 14: 2632, 15: 1494, 16: 3072, 17: 3072, 18: 3072, 19: 1791, 20: 3072, 21: 291, 22: 1324, 23: 642})])",MACs,8101.758464,top1_acc,-90.37800687285223 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 512, 9: 512, 10: 448, 11: 512, 12: 2120, 13: 3072, 14: 2117, 15: 931, 16: 2139, 17: 1362, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6695.486976,top1_acc,-89.08145580589255 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 768, 10: 384, 11: 704, 12: 1524, 13: 930, 14: 928, 15: 931, 16: 3072, 17: 1362, 18: 1245, 19: 1117, 20: 2391, 21: 2153, 22: 1324, 23: 308})])",MACs,6861.358592,top1_acc,-88.25503355704699 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 1206})])",MACs,8388.609536,top1_acc,-91.00346020761245 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 512, 9: 320, 10: 768, 11: 704, 12: 2120, 13: 930, 14: 2117, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 579, 20: 1627, 21: 291, 22: 300, 23: 1925})])",MACs,6390.744576,top1_acc,-88.85077186963979 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6016.861696,top1_acc,-88.9655172413793 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 512, 9: 320, 10: 576, 11: 192, 12: 3072, 13: 2097, 14: 2117, 15: 931, 16: 1456, 17: 2574, 18: 2561, 19: 1791, 20: 3072, 21: 291, 22: 678, 23: 3072})])",MACs,7825.065472,top1_acc,-89.76109215017065 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 448, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 3072, 18: 1245, 19: 1791, 20: 866, 21: 1395, 22: 2070, 23: 642})])",MACs,7115.965952,top1_acc,-90.18932874354562 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 512, 9: 320, 10: 576, 11: 192, 12: 3072, 13: 2097, 14: 2117, 15: 931, 16: 872, 17: 2574, 18: 3072, 19: 1791, 20: 3072, 21: 291, 22: 678, 23: 3072})])",MACs,7892.502016,top1_acc,-89.57264957264958 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 704, 8: 576, 9: 640, 10: 576, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 2127, 16: 1456, 17: 787, 18: 1245, 19: 1791, 20: 409, 21: 291, 22: 2070, 23: 642})])",MACs,6375.212544,top1_acc,-89.3169877408056 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 768, 10: 384, 11: 512, 12: 2120, 13: 930, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 2561, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,7301.367296,top1_acc,-90.2229845626072 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 512, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6992.233984,top1_acc,-90.0523560209424 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5695.735296,top1_acc,-87.56388415672913 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 640, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 930, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 308})])",MACs,8014.857728,top1_acc,-90.87779690189328 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 3072, 13: 2097, 14: 928, 15: 2664, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 2391, 21: 2153, 22: 300, 23: 308})])",MACs,6940.1984,top1_acc,-89.58333333333334 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 2120, 13: 930, 14: 1526, 15: 1494, 16: 872, 17: 2019, 18: 2561, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 308})])",MACs,6759.384576,top1_acc,-88.9267461669506 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 2632, 15: 2127, 16: 1456, 17: 2019, 18: 3072, 19: 1117, 20: 409, 21: 1395, 22: 678, 23: 642})])",MACs,6989.940224,top1_acc,-90.03436426116839 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 640, 8: 768, 9: 320, 10: 576, 11: 512, 12: 3072, 13: 2097, 14: 2632, 15: 2127, 16: 2645, 17: 2019, 18: 3072, 19: 1117, 20: 866, 21: 1395, 22: 2070, 23: 642})])",MACs,8105.952768,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 930, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 308})])",MACs,8014.857728,top1_acc,-90.56603773584906 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 768, 9: 320, 10: 448, 11: 704, 12: 1524, 13: 930, 14: 2632, 15: 1494, 16: 2139, 17: 2019, 18: 1245, 19: 1117, 20: 2391, 21: 2153, 22: 1324, 23: 1206})])",MACs,7347.570176,top1_acc,-88.35616438356165 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 448, 11: 512, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 3072, 18: 3072, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 3072})])",MACs,7346.718208,top1_acc,-89.1156462585034 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 640, 10: 768, 11: 704, 12: 2120, 13: 2097, 14: 2117, 15: 2127, 16: 1456, 17: 1362, 18: 1245, 19: 1791, 20: 1627, 21: 1395, 22: 300, 23: 1925})])",MACs,7581.664768,top1_acc,-89.58333333333334 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 640, 10: 384, 11: 704, 12: 1524, 13: 1520, 14: 928, 15: 2127, 16: 1456, 17: 1362, 18: 1245, 19: 1791, 20: 409, 21: 1395, 22: 2070, 23: 642})])",MACs,6782.715392,top1_acc,-88.8888888888889 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 2120, 13: 930, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 308})])",MACs,7882.212864,top1_acc,-90.75342465753423 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 640, 8: 512, 9: 640, 10: 384, 11: 704, 12: 1524, 13: 930, 14: 928, 15: 931, 16: 1456, 17: 1362, 18: 1245, 19: 579, 20: 866, 21: 1395, 22: 1324, 23: 308})])",MACs,5934.482944,top1_acc,-88.08290155440415 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 640, 8: 768, 9: 320, 10: 384, 11: 192, 12: 995, 13: 1520, 14: 2632, 15: 2127, 16: 2139, 17: 2019, 18: 1245, 19: 1117, 20: 409, 21: 1395, 22: 678, 23: 642})])",MACs,6489.31072,top1_acc,-88.50771869639793 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 512, 9: 640, 10: 576, 11: 704, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 579, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6122.243584,top1_acc,-89.00343642611685 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 2120, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 308})])",MACs,8187.414016,top1_acc,-91.00346020761245 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 2070, 23: 1206})])",MACs,5969.413632,top1_acc,-87.56388415672913 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 640, 10: 384, 11: 512, 12: 2618, 13: 2097, 14: 1526, 15: 1494, 16: 3072, 17: 3072, 18: 2561, 19: 1791, 20: 3072, 21: 291, 22: 678, 23: 308})])",MACs,7847.872,top1_acc,-90.5982905982906 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 640, 8: 768, 9: 320, 10: 384, 11: 512, 12: 3072, 13: 2097, 14: 2632, 15: 2127, 16: 2645, 17: 2019, 18: 3072, 19: 1117, 20: 2391, 21: 1395, 22: 2070, 23: 642})])",MACs,8351.254016,top1_acc,-90.625 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 640, 10: 576, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 2127, 16: 3072, 17: 1362, 18: 1245, 19: 1791, 20: 1627, 21: 1395, 22: 2070, 23: 1206})])",MACs,7700.547072,top1_acc,-89.54703832752612 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6044.124672,top1_acc,-88.9655172413793 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 512, 9: 320, 10: 448, 11: 704, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 1791, 20: 3072, 21: 291, 22: 1324, 23: 1206})])",MACs,8082.097664,top1_acc,-90.72164948453609 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2618, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 3072})])",MACs,6561.334784,top1_acc,-89.27335640138409 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 640, 8: 576, 9: 320, 10: 448, 11: 192, 12: 995, 13: 1520, 14: 2632, 15: 2127, 16: 2139, 17: 2019, 18: 1245, 19: 1117, 20: 1627, 21: 1395, 22: 678, 23: 642})])",MACs,6674.253312,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6905.857536,top1_acc,-91.25874125874125 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 576, 11: 512, 12: 2120, 13: 930, 14: 2632, 15: 1494, 16: 2645, 17: 2019, 18: 2561, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 308})])",MACs,7263.487488,top1_acc,-90.2229845626072 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8719.762944,top1_acc,-91.22203098106712 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 576, 9: 640, 10: 384, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,6694.11072,top1_acc,-89.1566265060241 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 192, 12: 995, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 579, 20: 866, 21: 291, 22: 2070, 23: 1206})])",MACs,6366.7584,top1_acc,-88.23529411764706 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 704, 8: 576, 9: 640, 10: 576, 11: 512, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1791, 20: 409, 21: 291, 22: 2070, 23: 642})])",MACs,6157.633024,top1_acc,-88.58603066439524 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 576, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8687.453696,top1_acc,-91.72413793103448 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 2632, 15: 2664, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 2153, 22: 2070, 23: 1206})])",MACs,6883.247616,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 930, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 1206})])",MACs,8028.882432,top1_acc,-90.46793760831888 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6072.698368,top1_acc,-88.31615120274915 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 872, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,6357.976576,top1_acc,-88.85077186963979 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 3072, 13: 1520, 14: 928, 15: 2664, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 2153, 22: 300, 23: 308})])",MACs,6409.815552,top1_acc,-89.39130434782608 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2618, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 1955, 19: 579, 20: 866, 21: 291, 22: 678, 23: 642})])",MACs,6425.544192,top1_acc,-90.12131715771231 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 995, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 1206})])",MACs,6242.371072,top1_acc,-87.75510204081631 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 768, 10: 384, 11: 768, 12: 2618, 13: 2621, 14: 2632, 15: 1494, 16: 872, 17: 2019, 18: 1955, 19: 1117, 20: 1627, 21: 1395, 22: 678, 23: 1206})])",MACs,7441.155584,top1_acc,-89.23076923076923 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 704, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6711.936512,top1_acc,-89.46459412780656 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 1324, 23: 1206})])",MACs,8203.666944,top1_acc,-91.16117850953206 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 640, 10: 384, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 3072, 16: 3072, 17: 2019, 18: 1955, 19: 1791, 20: 409, 21: 3072, 22: 300, 23: 1925})])",MACs,7793.346048,top1_acc,-90.27777777777779 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 640, 8: 768, 9: 320, 10: 384, 11: 512, 12: 3072, 13: 2097, 14: 2632, 15: 2127, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 642})])",MACs,8116.5696,top1_acc,-90.87779690189328 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 512, 9: 640, 10: 768, 11: 704, 12: 2120, 13: 930, 14: 2117, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 579, 20: 1627, 21: 291, 22: 300, 23: 1206})])",MACs,6440.224256,top1_acc,-88.85077186963979 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6560.810496,top1_acc,-90.08695652173914 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 640, 8: 512, 9: 640, 10: 384, 11: 704, 12: 1524, 13: 930, 14: 928, 15: 931, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 1395, 22: 1324, 23: 308})])",MACs,5837.358592,top1_acc,-87.4354561101549 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 768, 10: 384, 11: 192, 12: 2618, 13: 2621, 14: 1526, 15: 2127, 16: 1456, 17: 3072, 18: 2561, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,7070.483968,top1_acc,-90.15544041450777 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 640, 10: 448, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 2127, 16: 1456, 17: 1362, 18: 1245, 19: 1791, 20: 866, 21: 1395, 22: 2070, 23: 642})])",MACs,6986.008064,top1_acc,-89.3542757417103 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 3072, 13: 2097, 14: 1526, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 2391, 21: 291, 22: 300, 23: 308})])",MACs,6434.391552,top1_acc,-89.00523560209423 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1520, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 2070, 23: 642})])",MACs,8452.244992,top1_acc,-90.94017094017094 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 3072})])",MACs,7354.516992,top1_acc,-90.94076655052264 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 640, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6688.54016,top1_acc,-90.55944055944055 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 512, 12: 2120, 13: 930, 14: 2632, 15: 2127, 16: 2645, 17: 2019, 18: 3072, 19: 1117, 20: 409, 21: 1395, 22: 1324, 23: 308})])",MACs,7196.313088,top1_acc,-90.03436426116839 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 1520, 14: 928, 15: 1494, 16: 872, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 1925})])",MACs,5847.3856,top1_acc,-88.02698145025295 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 995, 13: 1520, 14: 2632, 15: 2127, 16: 2139, 17: 2019, 18: 1245, 19: 579, 20: 1627, 21: 1395, 22: 678, 23: 1925})])",MACs,7038.83008,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2097, 14: 1526, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8230.667776,top1_acc,-90.87779690189328 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 704, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 2153, 22: 2070, 23: 642})])",MACs,6628.312576,top1_acc,-88.9655172413793 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 995, 13: 1520, 14: 2632, 15: 1494, 16: 872, 17: 787, 18: 3072, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 1925})])",MACs,6814.238208,top1_acc,-88.34782608695653 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2618, 13: 2097, 14: 3072, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,7479.821824,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 640, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 1395, 22: 678, 23: 1925})])",MACs,7735.608832,top1_acc,-90.84628670120898 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 1206})])",MACs,6603.802112,top1_acc,-89.3542757417103 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 1206})])",MACs,8470.398464,top1_acc,-91.1917098445596 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 704, 8: 768, 9: 640, 10: 576, 11: 512, 12: 2618, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1791, 20: 409, 21: 291, 22: 2070, 23: 3072})])",MACs,7048.267264,top1_acc,-88.92733564013841 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 931, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6795.167232,top1_acc,-89.65517241379311 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5921.44128,top1_acc,-88.23529411764706 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1245, 19: 579, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,6487.475712,top1_acc,-90.52631578947367 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 2070, 23: 1206})])",MACs,8404.862464,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 640, 10: 384, 11: 704, 12: 995, 13: 1520, 14: 928, 15: 1494, 16: 872, 17: 2019, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 1925})])",MACs,6444.025344,top1_acc,-88.43537414965985 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2618, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1117, 20: 1627, 21: 291, 22: 2070, 23: 1206})])",MACs,7519.53664,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 2070, 23: 1206})])",MACs,8697.808384,top1_acc,-91.22203098106712 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 576, 9: 768, 10: 384, 11: 704, 12: 3072, 13: 2621, 14: 928, 15: 2664, 16: 3072, 17: 787, 18: 1245, 19: 1117, 20: 2391, 21: 2153, 22: 300, 23: 308})])",MACs,7551.780352,top1_acc,-90.15544041450777 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 576, 9: 512, 10: 448, 11: 192, 12: 2120, 13: 3072, 14: 3072, 15: 1494, 16: 1456, 17: 1362, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6805.128704,top1_acc,-89.81001727115718 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 3072, 13: 2097, 14: 928, 15: 2664, 16: 1456, 17: 787, 18: 1955, 19: 1117, 20: 409, 21: 2153, 22: 300, 23: 642})])",MACs,6810.306048,top1_acc,-89.58333333333334 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 640, 8: 512, 9: 640, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 931, 16: 1456, 17: 787, 18: 3072, 19: 1117, 20: 409, 21: 1395, 22: 1324, 23: 308})])",MACs,7222.920704,top1_acc,-89.34707903780068 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 2120, 13: 2621, 14: 2117, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7411.271168,top1_acc,-90.59233449477352 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 1520, 14: 928, 15: 2664, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5825.627648,top1_acc,-88.85017421602788 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 576, 11: 192, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,7720.601088,top1_acc,-90.78260869565217 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 2070, 23: 1206})])",MACs,5493.360128,top1_acc,-87.75510204081631 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 1206})])",MACs,8053.589504,top1_acc,-91.16117850953206 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5485.757952,top1_acc,-88.81239242685025 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 1395, 22: 1324, 23: 1925})])",MACs,8453.031424,top1_acc,-91.37931034482759 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 642})])",MACs,5670.700544,top1_acc,-88.17567567567566 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 640, 8: 512, 9: 640, 10: 384, 11: 704, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 1395, 22: 1324, 23: 308})])",MACs,5948.048896,top1_acc,-88.13559322033899 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6335.104512,top1_acc,-89.65517241379311 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 640, 8: 512, 9: 640, 10: 384, 11: 704, 12: 1524, 13: 930, 14: 928, 15: 931, 16: 1456, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 1395, 22: 1324, 23: 308})])",MACs,6352.864768,top1_acc,-87.90459965928449 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 1324, 23: 642})])",MACs,6359.614976,top1_acc,-89.1566265060241 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,6641.419776,top1_acc,-90.625 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 3072})])",MACs,5753.734656,top1_acc,-88.09523809523809 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 1324, 23: 642})])",MACs,5870.192128,top1_acc,-88.77374784110535 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 320, 10: 448, 11: 768, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,7966.81984,top1_acc,-90.1023890784983 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 512, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 2117, 15: 931, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5719.721472,top1_acc,-87.34835355285962 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2618, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 1245, 19: 579, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,6025.053696,top1_acc,-89.04347826086956 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 576, 11: 704, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,7301.891584,top1_acc,-88.29431438127091 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 2120, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2574, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 642})])",MACs,8362.198528,top1_acc,-91.00346020761245 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 640, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1117, 20: 1627, 21: 291, 22: 1324, 23: 1925})])",MACs,7470.843392,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 1520, 14: 928, 15: 1494, 16: 872, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,5540.218368,top1_acc,-87.64805414551608 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7101.74464,top1_acc,-91.25874125874125 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 704, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 1395, 22: 1324, 23: 1925})])",MACs,8234.927616,top1_acc,-91.06529209621993 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 3072, 13: 1520, 14: 928, 15: 2664, 16: 1456, 17: 1362, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5993.2032,top1_acc,-89.66725043782837 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 640, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1117, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7452.886528,top1_acc,-90.52631578947367 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6447.760896,top1_acc,-89.50086058519794 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5584.848384,top1_acc,-87.56388415672913 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1925})])",MACs,7961.511424,top1_acc,-91.66666666666667 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 1520, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,6172.837376,top1_acc,-88.9267461669506 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,6668.682752,top1_acc,-90.625 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1117, 20: 1627, 21: 291, 22: 2070, 23: 1925})])",MACs,7287.080448,top1_acc,-90.55944055944055 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 1206})])",MACs,8108.115456,top1_acc,-91.1917098445596 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 768, 9: 320, 10: 448, 11: 768, 12: 2120, 13: 1520, 14: 2632, 15: 1494, 16: 3072, 17: 1362, 18: 3072, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,7500.400128,top1_acc,-89.81001727115718 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 995, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 2070, 23: 1206})])",MACs,6066.341376,top1_acc,-89.1891891891892 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,5985.601024,top1_acc,-88.77374784110535 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 2070, 23: 1206})])",MACs,6311.118336,top1_acc,-89.04109589041096 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6445.532672,top1_acc,-90.46793760831888 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 768, 10: 384, 11: 704, 12: 2618, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 1245, 19: 579, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,6270.42048,top1_acc,-89.04347826086956 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6393.234944,top1_acc,-89.81001727115718 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5857.87136,top1_acc,-88.58131487889273 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 642})])",MACs,5558.04416,top1_acc,-88.13559322033899 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5596.644864,top1_acc,-88.81239242685025 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 1206})])",MACs,7636.84608,top1_acc,-91.06529209621993 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 928, 15: 2664, 16: 3072, 17: 787, 18: 3072, 19: 1791, 20: 409, 21: 1395, 22: 1324, 23: 1925})])",MACs,8105.821696,top1_acc,-90.15544041450777 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5458.494976,top1_acc,-88.81239242685025 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 512, 8: 576, 9: 640, 10: 384, 11: 704, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 1362, 18: 1955, 19: 579, 20: 866, 21: 291, 22: 678, 23: 642})])",MACs,5995.103744,top1_acc,-88.77374784110535 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,6992.692736,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 192, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,7611.549184,top1_acc,-90.59233449477352 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2618, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,5452.072448,top1_acc,-89.04347826086956 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 1324, 23: 642})])",MACs,5555.291648,top1_acc,-88.58603066439524 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5485.757952,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 3072, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 642})])",MACs,6208.226816,top1_acc,-88.01369863013697 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 2070, 23: 1206})])",MACs,7202.604544,top1_acc,-89.5368782161235 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6615.336448,top1_acc,-89.70331588132635 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 704, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7047.218688,top1_acc,-90.87719298245615 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5158.209024,top1_acc,-87.87878787878788 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 768, 10: 448, 11: 768, 12: 995, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 1324, 23: 1206})])",MACs,6869.157376,top1_acc,-88.62068965517241 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1245, 19: 579, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,6432.94976,top1_acc,-90.9090909090909 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1245, 19: 579, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,6569.26464,top1_acc,-90.84507042253522 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6253.315584,top1_acc,-89.65517241379311 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5920.654848,top1_acc,-89.69072164948454 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 1395, 22: 1324, 23: 1925})])",MACs,8480.2944,top1_acc,-91.37931034482759 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 768, 9: 768, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 3072, 23: 642})])",MACs,6948.652544,top1_acc,-90.0523560209424 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 640, 10: 448, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7265.322496,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 384, 11: 768, 12: 2120, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,7727.089152,top1_acc,-90.55944055944055 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2618, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1925})])",MACs,7842.9568,top1_acc,-90.63032367972743 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,6288.967168,top1_acc,-89.93055555555554 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6365.971968,top1_acc,-89.87993138936535 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 640, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 2070, 23: 1925})])",MACs,7539.000832,top1_acc,-90.9090909090909 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 768, 10: 448, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 3072, 19: 579, 20: 866, 21: 1395, 22: 678, 23: 1206})])",MACs,7439.386112,top1_acc,-90.625 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5463.606784,top1_acc,-88.92733564013841 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 872, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,5634.590208,top1_acc,-88.8888888888889 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 704, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 1362, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,5576.263168,top1_acc,-89.43661971830987 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8801.551872,top1_acc,-91.37931034482759 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 1520, 14: 928, 15: 2664, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5607.19616,top1_acc,-89.51048951048952 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 768, 9: 768, 10: 576, 11: 192, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,7853.901312,top1_acc,-91.22203098106712 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 2664, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5548.54144,top1_acc,-88.54166666666666 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 768, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,5900.207616,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8551.138816,top1_acc,-91.37931034482759 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2618, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 1245, 19: 579, 20: 866, 21: 291, 22: 300, 23: 308})])",MACs,6005.261824,top1_acc,-89.04347826086956 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 576, 11: 704, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8062.109184,top1_acc,-90.08695652173914 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,5570.627072,top1_acc,-89.51048951048952 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5766.055424,top1_acc,-89.58333333333334 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5345.838592,top1_acc,-88.62068965517241 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 678, 23: 642})])",MACs,5743.18336,top1_acc,-88.77374784110535 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 1206})])",MACs,7544.702464,top1_acc,-91.0344827586207 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 704, 12: 995, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 2070, 23: 642})])",MACs,6088.492544,top1_acc,-88.88888888888889 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 1117, 20: 1627, 21: 291, 22: 678, 23: 642})])",MACs,6405.031424,top1_acc,-89.46459412780656 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2618, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6491.145728,top1_acc,-89.419795221843 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6097.012224,top1_acc,-90.65743944636677 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5376.640512,top1_acc,-88.33333333333333 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7474.97216,top1_acc,-90.49295774647887 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 3072, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 1362, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6041.306624,top1_acc,-89.19860627177701 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2618, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,5564.728832,top1_acc,-88.85017421602788 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 640, 10: 384, 11: 704, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 1117, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7015.433728,top1_acc,-89.65517241379311 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6899.828224,top1_acc,-90.29982363315698 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5373.101568,top1_acc,-88.62068965517241 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6557.730304,top1_acc,-90.9090909090909 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8644.003328,top1_acc,-91.40893470790378 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 704, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 1362, 18: 1245, 19: 1791, 20: 866, 21: 291, 22: 1324, 23: 1206})])",MACs,7456.753152,top1_acc,-91.0344827586207 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 640, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2618, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 866, 21: 291, 22: 1324, 23: 308})])",MACs,6965.298688,top1_acc,-90.5982905982906 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6483.74016,top1_acc,-90.625 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6533.54752,top1_acc,-89.89547038327525 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5651.170816,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 768, 8: 576, 9: 768, 10: 576, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8856.077824,top1_acc,-91.37931034482759 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1117, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7039.550976,top1_acc,-89.42807625649914 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7129.007616,top1_acc,-90.94076655052264 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2621, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 1117, 20: 409, 21: 291, 22: 1324, 23: 642})])",MACs,6270.223872,top1_acc,-89.19382504288164 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1791, 20: 866, 21: 1395, 22: 678, 23: 308})])",MACs,6053.234176,top1_acc,-89.3542757417103 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5602.93632,top1_acc,-89.00523560209423 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5263.984128,top1_acc,-88.0672268907563 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,6129.059328,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6393.234944,top1_acc,-89.72602739726027 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 768, 10: 576, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 1395, 22: 1324, 23: 1206})])",MACs,8393.4592,top1_acc,-91.06529209621993 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 1245, 19: 1791, 20: 1627, 21: 1395, 22: 300, 23: 1925})])",MACs,7683.966464,top1_acc,-90.56603773584906 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 768, 10: 448, 11: 192, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 1395, 22: 1324, 23: 1206})])",MACs,8093.566464,top1_acc,-91.06529209621993 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6280.57856,top1_acc,-89.69072164948454 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,4992.79616,top1_acc,-88.36424957841484 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 1395, 22: 1324, 23: 1206})])",MACs,8284.407296,top1_acc,-91.40893470790378 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5466.162688,top1_acc,-89.46459412780656 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6530.467328,top1_acc,-90.9090909090909 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 1520, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1791, 20: 409, 21: 1395, 22: 678, 23: 1925})])",MACs,7668.565504,top1_acc,-89.9830220713073 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7478.90432,top1_acc,-90.2654867256637 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5781.325312,top1_acc,-89.1156462585034 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5270.865408,top1_acc,-88.25503355704699 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6400.902656,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5345.838592,top1_acc,-88.62068965517241 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8774.288896,top1_acc,-91.56626506024097 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 1791, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6926.304768,top1_acc,-91.03690685413005 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 640, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7156.270592,top1_acc,-91.06830122591944 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1206})])",MACs,7904.298496,top1_acc,-90.27777777777779 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1925})])",MACs,7502.82496,top1_acc,-89.65517241379311 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5267.326464,top1_acc,-88.9655172413793 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 576, 11: 768, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8318.879232,top1_acc,-91.22203098106712 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5267.588608,top1_acc,-88.3720930232558 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 2120, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 1324, 23: 1925})])",MACs,7481.85344,top1_acc,-89.89547038327525 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6712.002048,top1_acc,-90.29982363315698 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5569.381888,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2621, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6470.30528,top1_acc,-89.1156462585034 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 576, 11: 768, 12: 3072, 13: 930, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,7375.35744,top1_acc,-89.79591836734693 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6742.27968,top1_acc,-91.28919860627178 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 2645, 17: 787, 18: 672, 19: 1791, 20: 866, 21: 1395, 22: 678, 23: 1206})])",MACs,6463.555072,top1_acc,-89.51048951048952 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 3072, 19: 1791, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,6894.126592,top1_acc,-90.94076655052264 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6578.701824,top1_acc,-91.28919860627178 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8692.499968,top1_acc,-91.37931034482759 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,6268.651008,top1_acc,-90.78260869565217 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 1395, 22: 678, 23: 1206})])",MACs,6162.089472,top1_acc,-89.3835616438356 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 768, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 1395, 22: 1324, 23: 1925})])",MACs,8350.008832,top1_acc,-91.0344827586207 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1955, 19: 579, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,6572.54144,top1_acc,-90.94076655052264 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2618, 13: 2621, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 1955, 19: 579, 20: 866, 21: 291, 22: 678, 23: 642})])",MACs,6528.566784,top1_acc,-89.81001727115718 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 576, 11: 768, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1206})])",MACs,7866.22208,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 995, 13: 2621, 14: 2632, 15: 1494, 16: 872, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 1395, 22: 678, 23: 1925})])",MACs,7566.919168,top1_acc,-89.57264957264958 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1791, 20: 409, 21: 1395, 22: 678, 23: 1925})])",MACs,5921.572352,top1_acc,-88.54700854700855 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1955, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5764.679168,top1_acc,-88.69863013698631 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 1791, 20: 866, 21: 291, 22: 2070, 23: 1206})])",MACs,7037.19168,top1_acc,-90.84507042253522 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 704, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,5517.673984,top1_acc,-88.17567567567566 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 2139, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,6545.868288,top1_acc,-90.36777583187391 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 1520, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1117, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8038.843904,top1_acc,-91.28205128205128 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6565.529088,top1_acc,-90.78260869565217 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 1395, 22: 678, 23: 1206})])",MACs,7553.418752,top1_acc,-91.03690685413005 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6261.310976,top1_acc,-90.9090909090909 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 930, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 1324, 23: 1925})])",MACs,7558.53056,top1_acc,-89.65517241379311 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8747.02592,top1_acc,-91.53713298791018 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5957.420544,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,5467.60448,top1_acc,-89.63093145869946 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 2632, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 1324, 23: 1206})])",MACs,6092.097024,top1_acc,-87.71331058020478 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 1206})])",MACs,6250.75968,top1_acc,-89.9488926746167 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 448, 11: 704, 12: 995, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 642})])",MACs,7032.735232,top1_acc,-89.69072164948454 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5596.317184,top1_acc,-89.45578231292517 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 678, 23: 642})])",MACs,6178.080256,top1_acc,-89.93055555555554 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1245, 19: 1117, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,6343.49312,top1_acc,-90.08695652173914 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 1791, 20: 409, 21: 291, 22: 300, 23: 1206})])",MACs,7076.447744,top1_acc,-89.77469670710572 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 704, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,6421.284352,top1_acc,-90.75043630017451 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6290.015744,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,4938.270208,top1_acc,-88.0672268907563 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 1520, 14: 928, 15: 2664, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 1395, 22: 1324, 23: 308})])",MACs,6815.155712,top1_acc,-89.3103448275862 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6737.888768,top1_acc,-89.96539792387543 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 866, 21: 291, 22: 2070, 23: 642})])",MACs,5935.597056,top1_acc,-89.3542757417103 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6887.11424,top1_acc,-89.6797153024911 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5690.820096,top1_acc,-89.03878583473862 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5780.86656,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6105.26976,top1_acc,-89.60817717206135 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 768, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5721.687552,top1_acc,-88.9267461669506 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 512, 8: 576, 9: 320, 10: 576, 11: 768, 12: 3072, 13: 1520, 14: 928, 15: 2664, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 1395, 22: 1324, 23: 308})])",MACs,6851.855872,top1_acc,-88.85017421602788 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 768, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7457.670656,top1_acc,-90.9090909090909 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,6358.697472,top1_acc,-90.17543859649123 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8671.266304,top1_acc,-91.56626506024097 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 768, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 866, 21: 1395, 22: 678, 23: 1925})])",MACs,7642.023424,top1_acc,-91.06529209621993 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 768, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 1520, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1117, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8093.369856,top1_acc,-90.9710391822828 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 300, 23: 308})])",MACs,6491.407872,top1_acc,-91.28919860627178 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6349.260288,top1_acc,-89.34010152284263 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 704, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 1362, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,5689.705984,top1_acc,-89.5575221238938 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,6177.555968,top1_acc,-90.52631578947367 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2618, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,5628.626432,top1_acc,-89.2361111111111 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5631.641088,top1_acc,-88.8888888888889 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6291.457536,top1_acc,-88.70151770657672 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 768, 8: 576, 9: 768, 10: 384, 11: 192, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 1791, 20: 1627, 21: 291, 22: 300, 23: 1206})])",MACs,7442.793984,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8222.475776,top1_acc,-91.53713298791018 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 1362, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5612.832256,top1_acc,-89.43661971830987 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 704, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 1362, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,5549.000192,top1_acc,-89.27943760984182 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 320, 10: 384, 11: 704, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 1206})])",MACs,7131.039232,top1_acc,-90.15544041450777 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5216.339456,top1_acc,-88.55218855218855 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 1520, 14: 928, 15: 2664, 16: 1456, 17: 1362, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6244.075008,top1_acc,-89.86013986013987 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5222.237696,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,5354.161664,top1_acc,-89.3169877408056 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5350.491648,top1_acc,-89.82456140350877 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6002.836992,top1_acc,-89.46459412780656 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8578.401792,top1_acc,-91.34948096885815 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 384, 11: 704, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,7922.25536,top1_acc,-90.625 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,5880.612352,top1_acc,-89.57264957264958 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 1520, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8072.66048,top1_acc,-90.7849829351536 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5403.969024,top1_acc,-88.62068965517241 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6448.285184,top1_acc,-91.28919860627178 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 640, 8: 768, 9: 768, 10: 448, 11: 192, 12: 3072, 13: 930, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 1925})])",MACs,6972.507648,top1_acc,-89.9488926746167 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5406.656,top1_acc,-88.58131487889273 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1117, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6872.04096,top1_acc,-90.55944055944055 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 1395, 22: 1324, 23: 1206})])",MACs,8263.173632,top1_acc,-91.0344827586207 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5103.683072,top1_acc,-87.87878787878788 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8665.236992,top1_acc,-91.37931034482759 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5105.452544,top1_acc,-88.55218855218855 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5047.322112,top1_acc,-88.0672268907563 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 640, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 300, 23: 308})])",MACs,5916.984832,top1_acc,-89.26746166950595 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5903.0912,top1_acc,-89.45578231292517 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 1362, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 1324, 23: 1206})])",MACs,7638.287872,top1_acc,-91.0344827586207 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 576, 11: 192, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 1395, 22: 678, 23: 1206})])",MACs,7622.75584,top1_acc,-90.08403361344538 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5388.895744,top1_acc,-90.01751313485114 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5387.65056,top1_acc,-88.69863013698631 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5733.877248,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8774.288896,top1_acc,-91.72413793103448 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 1206})])",MACs,6719.866368,top1_acc,-91.31944444444444 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5264.049664,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5838.407168,top1_acc,-89.30390492359932 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5297.604096,top1_acc,-88.27586206896552 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 1206})])",MACs,7047.02208,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1791, 20: 866, 21: 291, 22: 1324, 23: 308})])",MACs,6418.85952,top1_acc,-89.27335640138409 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5646.386688,top1_acc,-88.81469115191986 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,6039.209472,top1_acc,-89.86486486486487 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 1362, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5906.630144,top1_acc,-89.63093145869946 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8671.266304,top1_acc,-91.5951972555746 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7689.93024,top1_acc,-91.2280701754386 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5240.063488,top1_acc,-88.58131487889273 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 3072, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1925})])",MACs,8050.181632,top1_acc,-90.78260869565217 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 320, 10: 576, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8199.865856,top1_acc,-91.06529209621993 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,6088.55808,top1_acc,-89.93055555555554 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5636.752896,top1_acc,-88.8888888888889 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,5573.379584,top1_acc,-89.78873239436619 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 512, 8: 576, 9: 768, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6445.008384,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,6323.50464,top1_acc,-90.78260869565217 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 704, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,5899.224576,top1_acc,-89.77469670710572 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1206})])",MACs,7143.097856,top1_acc,-90.78260869565217 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 576, 11: 192, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,7942.964736,top1_acc,-91.00346020761245 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5154.932224,top1_acc,-88.14691151919867 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6066.472448,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 512, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 1925})])",MACs,8209.892864,top1_acc,-91.34948096885815 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 768, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5902.697984,top1_acc,-88.73949579831934 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5321.852416,top1_acc,-88.81239242685025 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 642})])",MACs,5329.913344,top1_acc,-88.42832469775476 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8442.086912,top1_acc,-91.72413793103448 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 576, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8467.84256,top1_acc,-91.34948096885815 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8170.702336,top1_acc,-91.56626506024097 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6926.042624,top1_acc,-90.9090909090909 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,6206.064128,top1_acc,-89.4736842105263 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1791, 20: 1627, 21: 1395, 22: 300, 23: 1925})])",MACs,7667.582464,top1_acc,-90.40139616055846 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5049.15712,top1_acc,-88.0672268907563 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6149.703168,top1_acc,-90.94076655052264 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8801.551872,top1_acc,-91.72413793103448 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1117, 20: 409, 21: 1395, 22: 678, 23: 1206})])",MACs,6463.555072,top1_acc,-89.99999999999999 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6537.217536,top1_acc,-90.87719298245615 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,6407.06304,top1_acc,-90.3114186851211 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6256.068096,top1_acc,-90.44368600682594 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5577.115136,top1_acc,-88.58603066439524 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 300, 23: 308})])",MACs,6112.871936,top1_acc,-90.46793760831888 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 704, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 1791, 20: 866, 21: 1395, 22: 1324, 23: 1206})])",MACs,7257.785856,top1_acc,-90.08695652173914 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 576, 11: 768, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 1791, 20: 409, 21: 291, 22: 1324, 23: 1206})])",MACs,6751.913472,top1_acc,-90.0523560209424 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8094.746112,top1_acc,-91.22203098106712 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 576, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8052.01664,top1_acc,-90.87779690189328 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,6785.336832,top1_acc,-91.47826086956522 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5044.045312,top1_acc,-87.95986622073578 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 1206})])",MACs,6304.040448,top1_acc,-91.16117850953206 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8644.003328,top1_acc,-91.5951972555746 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,6344.869376,top1_acc,-91.28919860627178 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6311.970304,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1791, 20: 409, 21: 1395, 22: 678, 23: 1925})])",MACs,6904.940032,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,7648.511488,top1_acc,-90.52631578947367 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5623.58016,top1_acc,-89.45578231292517 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6445.008384,top1_acc,-90.71803852889667 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 768, 12: 1524, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,7083.525632,top1_acc,-90.55944055944055 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 1627, 21: 1395, 22: 678, 23: 642})])",MACs,7324.435968,top1_acc,-90.12131715771231 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 576, 11: 768, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1206})])",MACs,8457.422336,top1_acc,-90.9710391822828 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 2120, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,6632.310272,top1_acc,-90.20979020979021 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 300, 23: 642})])",MACs,6157.567488,top1_acc,-90.24390243902441 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 704, 8: 576, 9: 768, 10: 384, 11: 192, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 1395, 22: 678, 23: 1206})])",MACs,6864.111104,top1_acc,-89.77469670710572 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5951.981056,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 1206})])",MACs,6808.733184,top1_acc,-90.52631578947367 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,7380.403712,top1_acc,-90.41095890410959 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5601.166848,top1_acc,-89.04109589041096 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 320, 10: 448, 11: 704, 12: 1524, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 866, 21: 291, 22: 1324, 23: 1925})])",MACs,7809.402368,top1_acc,-90.3114186851211 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6043.207168,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 642})])",MACs,5745.346048,top1_acc,-89.51048951048952 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5147.13344,top1_acc,-88.81239242685025 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 642})])",MACs,6069.093888,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6417.745408,top1_acc,-91.31944444444444 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6393.759232,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 2632, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 642})])",MACs,5814.552064,top1_acc,-88.19444444444444 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 1395, 22: 1324, 23: 642})])",MACs,7249.20064,top1_acc,-90.37800687285223 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 576, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8660.19072,top1_acc,-91.72413793103448 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 642})])",MACs,6868.895232,top1_acc,-89.03654485049834 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 1627, 21: 1395, 22: 678, 23: 1925})])",MACs,6978.733568,top1_acc,-90.55944055944055 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 1362, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 642})])",MACs,7117.669888,top1_acc,-90.71803852889667 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,7728.399872,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5575.345664,top1_acc,-89.27943760984182 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,8028.358144,top1_acc,-91.00346020761245 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 576, 11: 768, 12: 3072, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 1395, 22: 1324, 23: 1206})])",MACs,7589.66016,top1_acc,-89.9830220713073 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,5644.158464,top1_acc,-89.82456140350877 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5098.571264,top1_acc,-88.21548821548822 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5835.392512,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 1395, 22: 1324, 23: 1206})])",MACs,7867.598336,top1_acc,-91.00346020761245 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,6846.940672,top1_acc,-89.42807625649914 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8671.266304,top1_acc,-91.5951972555746 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 768, 10: 384, 11: 192, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6240.077312,top1_acc,-89.69072164948454 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 704, 8: 576, 9: 320, 10: 448, 11: 704, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6250.10432,top1_acc,-88.77374784110535 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 768, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 1395, 22: 1324, 23: 1206})])",MACs,7614.432768,top1_acc,-90.9090909090909 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1791, 20: 866, 21: 1395, 22: 678, 23: 1925})])",MACs,6616.516096,top1_acc,-89.3542757417103 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5616.69888,top1_acc,-89.81001727115718 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 1324, 23: 1206})])",MACs,6493.505024,top1_acc,-90.94076655052264 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 3072, 14: 2632, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 642})])",MACs,6124.733952,top1_acc,-89.11917098445595 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,4978.37824,top1_acc,-87.95986622073578 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 768, 9: 320, 10: 448, 11: 192, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7856.195072,top1_acc,-91.31944444444444 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 642})])",MACs,5082.646016,top1_acc,-88.17567567567566 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5995.82464,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 1206})])",MACs,7411.533312,top1_acc,-90.2229845626072 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5273.486848,top1_acc,-88.24531516183987 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5416.15872,top1_acc,-89.82456140350877 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 768, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 1395, 22: 1324, 23: 1206})])",MACs,7366.379008,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5209.785856,top1_acc,-88.96672504378283 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6097.012224,top1_acc,-90.65743944636677 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 1206})])",MACs,5808.326144,top1_acc,-88.33333333333333 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5201.659392,top1_acc,-88.58131487889273 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 768, 9: 768, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,6976.177664,top1_acc,-91.47826086956522 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 1925})])",MACs,8019.052032,top1_acc,-91.31944444444444 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,6186.86208,top1_acc,-90.46793760831888 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 192, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 1206})])",MACs,7541.622272,top1_acc,-90.43478260869566 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 1324, 23: 1925})])",MACs,6276.6464,top1_acc,-88.77551020408163 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6472.27136,top1_acc,-90.75043630017451 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 642})])",MACs,5923.669504,top1_acc,-90.18932874354562 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 768, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6682.183168,top1_acc,-91.28919860627178 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 768, 8: 576, 9: 768, 10: 576, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8687.453696,top1_acc,-91.37931034482759 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 642})])",MACs,6242.305536,top1_acc,-90.3114186851211 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5387.65056,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,4992.79616,top1_acc,-88.51351351351352 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,7883.523584,top1_acc,-90.78260869565217 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 576, 11: 768, 12: 2120, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8261.993984,top1_acc,-90.59233449477352 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 512, 8: 576, 9: 768, 10: 384, 11: 192, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,7037.322752,top1_acc,-90.43478260869566 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1925})])",MACs,8774.288896,top1_acc,-91.56626506024097 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 576, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8469.349888,top1_acc,-91.56626506024097 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5233.31328,top1_acc,-89.42807625649914 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6254.167552,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 2120, 13: 2621, 14: 2632, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 866, 21: 1395, 22: 678, 23: 1206})])",MACs,6544.623104,top1_acc,-89.08145580589255 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 930, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 308})])",MACs,7372.998144,top1_acc,-89.69072164948454 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 308})])",MACs,5299.635712,top1_acc,-88.96672504378283 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7426.737664,top1_acc,-89.66725043782837 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 1627, 21: 291, 22: 678, 23: 642})])",MACs,5338.039808,top1_acc,-88.25503355704699 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8143.43936,top1_acc,-91.40893470790378 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 512, 8: 576, 9: 768, 10: 576, 11: 768, 12: 2120, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 1395, 22: 1324, 23: 1206})])",MACs,8179.025408,top1_acc,-91.16117850953206 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 1324, 23: 642})])",MACs,5376.312832,top1_acc,-88.27586206896552 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 768, 9: 768, 10: 448, 11: 192, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,7736.657408,top1_acc,-91.06529209621993 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6377.440768,top1_acc,-90.46793760831888 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 2120, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,7445.349888,top1_acc,-90.625 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1925})])",MACs,7858.488832,top1_acc,-91.53713298791018 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8632.927744,top1_acc,-91.72413793103448 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5318.83776,top1_acc,-88.96672504378283 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5552.80128,top1_acc,-89.30390492359932 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5606.999552,top1_acc,-89.78873239436619 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5213.98016,top1_acc,-88.92733564013841 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 1206})])",MACs,5729.617408,top1_acc,-88.39590443686006 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5283.251712,top1_acc,-88.70431893687709 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5512.693248,top1_acc,-89.45578231292517 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 1324, 23: 1206})])",MACs,5985.207808,top1_acc,-88.6561954624782 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6077.613568,top1_acc,-90.94076655052264 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 768, 10: 576, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 308})])",MACs,7884.768768,top1_acc,-90.87779690189328 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 642})])",MACs,7623.4112,top1_acc,-91.37931034482759 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5583.341056,top1_acc,-89.63093145869946 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 768, 10: 576, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 1395, 22: 678, 23: 1206})])",MACs,7533.364736,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,8660.19072,top1_acc,-91.37931034482759 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1206})])",MACs,7442.990592,top1_acc,-90.78260869565217 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5298.980352,top1_acc,-89.42807625649914 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6194.595328,top1_acc,-90.625 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 308})])",MACs,7213.417984,top1_acc,-91.22203098106712 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5264.311808,top1_acc,-88.81118881118883 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6196.561408,top1_acc,-89.91452991452992 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5082.383872,top1_acc,-88.13559322033899 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,5999.166976,top1_acc,-89.07849829351535 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 1206})])",MACs,6552.55296,top1_acc,-90.40139616055846 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5190.321664,top1_acc,-88.74172185430463 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,8103.003648,top1_acc,-91.88255613126081 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6727.468544,top1_acc,-92.01388888888889 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5323.228672,top1_acc,-90.01751313485114 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,6426.134016,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 768, 10: 448, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1925})])",MACs,7621.248512,top1_acc,-90.71803852889667 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5159.454208,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 995, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5097.65376,top1_acc,-88.05460750853243 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6019.483136,top1_acc,-90.94076655052264 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,4965.533184,top1_acc,-88.51351351351352 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6624.380416,top1_acc,-91.47826086956522 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 576, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 1324, 23: 1206})])",MACs,7903.774208,top1_acc,-91.56626506024097 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 768, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6638.798336,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 768, 12: 3072, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 308})])",MACs,6555.633152,top1_acc,-89.69072164948454 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 866, 21: 291, 22: 678, 23: 642})])",MACs,5419.828736,top1_acc,-89.16083916083916 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6093.735424,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 320, 10: 384, 11: 704, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1925})])",MACs,6212.486656,top1_acc,-87.91946308724832 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 1395, 22: 678, 23: 642})])",MACs,5954.471424,top1_acc,-89.66725043782837 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,6071.256576,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 704, 8: 576, 9: 768, 10: 448, 11: 192, 12: 1524, 13: 2621, 14: 2632, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 1206})])",MACs,7278.953984,top1_acc,-88.92733564013841 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,4872.603136,top1_acc,-88.0672268907563 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 768, 9: 768, 10: 384, 11: 192, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,7347.111424,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 768, 10: 448, 11: 768, 12: 2120, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,7799.768576,top1_acc,-90.43478260869566 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 642})])",MACs,5978.195456,top1_acc,-90.18932874354562 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 866, 21: 291, 22: 678, 23: 1206})])",MACs,6510.872064,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 642})])",MACs,7647.266304,top1_acc,-90.9090909090909 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6035.932672,top1_acc,-90.46793760831888 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 1324, 23: 308})])",MACs,6709.315072,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5093.787136,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 640, 8: 768, 9: 320, 10: 576, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6050.350592,top1_acc,-88.9267461669506 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 192, 12: 995, 13: 2621, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 1117, 20: 409, 21: 291, 22: 1324, 23: 308})])",MACs,6397.298176,top1_acc,-88.9267461669506 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6809.257472,top1_acc,-91.82608695652175 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 192, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,7781.877248,top1_acc,-91.25214408233276 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5688.78848,top1_acc,-90.14084507042254 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 642})])",MACs,6169.036288,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6196.03712,top1_acc,-90.94076655052264 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,6208.554496,top1_acc,-91.31944444444444 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 2632, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1206})])",MACs,6942.557696,top1_acc,-89.3835616438356 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5102.044672,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 768, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 1627, 21: 1395, 22: 678, 23: 642})])",MACs,6588.466688,top1_acc,-89.03878583473862 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,7003.44064,top1_acc,-91.25874125874125 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 3072, 13: 1520, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,6800.082432,top1_acc,-89.9830220713073 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6542.591488,top1_acc,-91.16117850953206 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,7048.594944,top1_acc,-90.2654867256637 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 512, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1925})])",MACs,7531.33312,top1_acc,-91.1917098445596 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5706.614272,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 308})])",MACs,6127.486464,top1_acc,-91.16117850953206 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5950.539264,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,6096.4224,top1_acc,-90.03436426116839 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 768, 8: 768, 9: 768, 10: 448, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1925})])",MACs,8049.329664,top1_acc,-91.16117850953206 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 308})])",MACs,6594.561536,top1_acc,-90.75043630017451 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 930, 14: 2632, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 642})])",MACs,6186.665472,top1_acc,-89.3103448275862 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 1206})])",MACs,6358.5664,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5213.98016,top1_acc,-88.27586206896552 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6447.957504,top1_acc,-91.69550173010381 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 576, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,6934.62784,top1_acc,-91.34948096885815 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 995, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 1324, 23: 308})])",MACs,6854.608384,top1_acc,-89.6434634974533 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5050.926592,top1_acc,-88.25503355704699 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5435.885056,top1_acc,-90.01751313485114 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5640.9472,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5609.293312,top1_acc,-89.87993138936535 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6409.750016,top1_acc,-90.24390243902441 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5858.919936,top1_acc,-90.15544041450777 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,7882.147328,top1_acc,-89.84509466437176 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 768, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5849.220608,top1_acc,-89.82456140350877 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 768, 10: 576, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1206})])",MACs,8120.043008,top1_acc,-91.6083916083916 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6088.55808,top1_acc,-90.15544041450777 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5910.431232,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,7479.625216,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5477.172736,top1_acc,-89.3760539629005 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5901.059584,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5793.252864,top1_acc,-90.15544041450777 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6282.87232,top1_acc,-91.31944444444444 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 192, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1791, 20: 409, 21: 1395, 22: 1324, 23: 308})])",MACs,7366.968832,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 642})])",MACs,5424.809472,top1_acc,-88.55721393034827 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6313.739776,top1_acc,-91.31944444444444 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5948.835328,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,8157.5296,top1_acc,-91.34948096885815 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6192.76032,top1_acc,-90.94076655052264 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5716.051456,top1_acc,-89.94708994708994 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5733.877248,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6167.52896,top1_acc,-89.51048951048952 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,7041.12384,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5129.307648,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5623.121408,top1_acc,-90.14084507042254 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 308})])",MACs,5567.54688,top1_acc,-90.01751313485114 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,4798.285312,top1_acc,-88.0672268907563 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 1206})])",MACs,7070.94272,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6409.553408,top1_acc,-91.82608695652175 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 1117, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6175.524352,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6754.73152,top1_acc,-91.16117850953206 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6205.736448,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6142.166528,top1_acc,-88.8888888888889 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5883.168256,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5255.988736,top1_acc,-88.74172185430463 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5795.087872,top1_acc,-89.54703832752612 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 1206})])",MACs,6416.696832,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6491.538944,top1_acc,-90.625 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 995, 13: 2621, 14: 2632, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,6342.772224,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 704, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6018.696704,top1_acc,-88.42832469775476 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,6197.413376,top1_acc,-91.28919860627178 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6675.10528,top1_acc,-91.31944444444444 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6632.83456,top1_acc,-89.5368782161235 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5976.098304,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5497.947648,top1_acc,-89.82456140350877 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 1627, 21: 1395, 22: 1324, 23: 1206})])",MACs,7762.806272,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 704, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6557.009408,top1_acc,-91.28919860627178 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5948.835328,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 448, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 1791, 20: 1627, 21: 1395, 22: 678, 23: 1206})])",MACs,8072.857088,top1_acc,-91.09589041095889 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 768, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6720.587264,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6006.507008,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5795.087872,top1_acc,-89.54703832752612 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,5956.306432,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 1791, 20: 1627, 21: 1395, 22: 1324, 23: 308})])",MACs,7766.410752,top1_acc,-91.1917098445596 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,7316.964864,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5159.454208,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6475.22048,top1_acc,-91.82608695652175 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 642})])",MACs,6165.89056,top1_acc,-90.6896551724138 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,4927.129088,top1_acc,-88.51351351351352 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 1324, 23: 308})])",MACs,5992.351232,top1_acc,-90.29982363315698 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6201.083392,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 3072, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,8191.673856,top1_acc,-91.12627986348123 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5937.694208,top1_acc,-90.55944055944055 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5158.995456,top1_acc,-89.42807625649914 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5508.2368,top1_acc,-88.66666666666667 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,5885.462016,top1_acc,-88.50174216027874 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5116.00384,top1_acc,-88.3720930232558 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 384, 11: 704, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,7098.009088,top1_acc,-90.65743944636677 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5047.322112,top1_acc,-88.51351351351352 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5719.393792,top1_acc,-89.22558922558923 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,5551.228416,top1_acc,-89.61937716262976 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5217.58464,top1_acc,-88.66666666666667 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5578.294784,top1_acc,-89.61937716262976 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6173.623808,top1_acc,-90.43478260869566 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6355.027456,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 1206})])",MACs,5227.08736,top1_acc,-87.95986622073578 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,5868.946944,top1_acc,-89.96539792387543 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6255.609344,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6485.247488,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6709.446144,top1_acc,-91.06830122591944 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,7709.26336,top1_acc,-91.06529209621993 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 768, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6224.610816,top1_acc,-90.78260869565217 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,5584.061952,top1_acc,-88.26446280991736 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5435.885056,top1_acc,-90.01751313485114 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6102.976,top1_acc,-90.12131715771231 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 642})])",MACs,8168.67072,top1_acc,-91.88255613126081 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5765.989888,top1_acc,-90.3114186851211 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6475.22048,top1_acc,-91.31944444444444 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5159.454208,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5194.97472,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 1324, 23: 308})])",MACs,7400.064512,top1_acc,-91.22203098106712 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5808.326144,top1_acc,-89.419795221843 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6282.87232,top1_acc,-91.31944444444444 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5093.787136,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5531.698688,top1_acc,-89.3760539629005 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1206})])",MACs,6339.23328,top1_acc,-91.16117850953206 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5582.030336,top1_acc,-89.50086058519794 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 384, 11: 704, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5841.48736,top1_acc,-89.03654485049834 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 384, 11: 192, 12: 995, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6006.441472,top1_acc,-89.07849829351535 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5432.280576,top1_acc,-89.82456140350877 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,8103.003648,top1_acc,-91.34948096885815 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5214.701056,top1_acc,-88.2051282051282 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,4929.55392,top1_acc,-88.39590443686006 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 642})])",MACs,7178.159616,top1_acc,-91.44851657940663 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5261.690368,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,5614.470656,top1_acc,-89.94708994708994 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 300, 23: 308})])",MACs,5831.98464,top1_acc,-89.76109215017065 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5131.73248,top1_acc,-89.27335640138409 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5206.050304,top1_acc,-89.27335640138409 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 642})])",MACs,7199.786496,top1_acc,-89.91452991452992 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 704, 12: 3072, 13: 930, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 642})])",MACs,7034.832384,top1_acc,-89.99999999999999 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5424.154112,top1_acc,-89.2361111111111 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5019.469312,top1_acc,-88.42832469775476 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 384, 11: 704, 12: 3072, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 2561, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 642})])",MACs,6949.70112,top1_acc,-89.87993138936535 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5517.673984,top1_acc,-89.98242530755711 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6355.027456,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 768, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 642})])",MACs,8250.459648,top1_acc,-91.72413793103448 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5315.102208,top1_acc,-89.42807625649914 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 192, 12: 995, 13: 2621, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 1324, 23: 308})])",MACs,6103.762432,top1_acc,-88.8888888888889 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6255.609344,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5606.999552,top1_acc,-89.78873239436619 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,6126.765568,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5230.102016,top1_acc,-88.42832469775476 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6836.520448,top1_acc,-91.82608695652175 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5320.14848,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5551.031808,top1_acc,-89.96539792387543 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,6088.361472,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5271.717376,top1_acc,-89.27335640138409 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5819.270656,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5836.113408,top1_acc,-90.94076655052264 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6270.158336,top1_acc,-90.25641025641026 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6163.138048,top1_acc,-90.44368600682594 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5476.713984,top1_acc,-89.77469670710572 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6023.087616,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 448, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6836.520448,top1_acc,-91.82608695652175 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6003.36128,top1_acc,-90.94076655052264 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5753.603584,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,4902.290944,top1_acc,-88.43537414965985 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,4825.548288,top1_acc,-88.51351351351352 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6091.83488,top1_acc,-90.43478260869566 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6162.679296,top1_acc,-91.00346020761245 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 1925})])",MACs,5337.384448,top1_acc,-88.31615120274915 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,7580.8128,top1_acc,-91.2280701754386 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5208.4096,top1_acc,-89.66725043782837 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,5884.544512,top1_acc,-90.3114186851211 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,6170.1504,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6355.027456,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5020.059136,top1_acc,-87.91946308724832 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5027.726848,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 995, 13: 2621, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,6959.597056,top1_acc,-88.9655172413793 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5958.862336,top1_acc,-90.3114186851211 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5822.350848,top1_acc,-89.51048951048952 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 1324, 23: 308})])",MACs,5795.481088,top1_acc,-88.85191347753744 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5042.27584,top1_acc,-88.28522920203736 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6070.53568,top1_acc,-89.72602739726027 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5948.835328,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5937.694208,top1_acc,-90.55944055944055 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1791, 20: 1627, 21: 291, 22: 300, 23: 642})])",MACs,7171.474944,top1_acc,-90.06849315068493 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6579.815936,top1_acc,-89.67851099830796 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5405.0176,top1_acc,-89.82456140350877 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5459.346944,top1_acc,-88.58131487889273 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5451.417088,top1_acc,-89.19860627177701 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,5523.768832,top1_acc,-89.45578231292517 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 640, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5708.44928,top1_acc,-89.23076923076923 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6037.308928,top1_acc,-90.12131715771231 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5808.129536,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5641.143808,top1_acc,-89.89547038327525 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,4899.866112,top1_acc,-88.51351351351352 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5093.787136,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5565.449728,top1_acc,-89.98242530755711 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5274.076672,top1_acc,-89.86013986013987 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 1791, 20: 2391, 21: 291, 22: 1324, 23: 308})])",MACs,6958.745088,top1_acc,-90.43478260869566 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6180.111872,top1_acc,-89.34010152284263 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5276.173824,top1_acc,-89.82456140350877 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,6061.098496,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5719.131648,top1_acc,-88.85135135135135 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6226.773504,top1_acc,-90.1023890784983 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5463.148032,top1_acc,-89.82456140350877 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5668.210176,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 384, 11: 192, 12: 995, 13: 930, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,6092.752384,top1_acc,-88.24531516183987 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,5093.39392,top1_acc,-88.50771869639793 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5551.031808,top1_acc,-89.96539792387543 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6112.8064,top1_acc,-90.625 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6091.83488,top1_acc,-90.43478260869566 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 300, 23: 1925})])",MACs,6105.990656,top1_acc,-88.9267461669506 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 308})])",MACs,6100.223488,top1_acc,-90.84628670120898 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,4814.734848,top1_acc,-88.39590443686006 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,5197.399552,top1_acc,-89.27335640138409 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5432.280576,top1_acc,-89.98242530755711 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6507.857408,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,4978.968064,top1_acc,-88.50771869639793 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 2645, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6040.454656,top1_acc,-88.96434634974534 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,6346.376704,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,4938.270208,top1_acc,-88.0672268907563 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5054.989824,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 384, 11: 192, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,7337.805312,top1_acc,-90.65743944636677 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 1925})])",MACs,5337.384448,top1_acc,-88.31615120274915 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 2117, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5987.370496,top1_acc,-90.25641025641026 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6471.812608,top1_acc,-90.40139616055846 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6188.369408,top1_acc,-90.25641025641026 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 300, 23: 308})])",MACs,5398.464,top1_acc,-89.11917098445595 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 1324, 23: 642})])",MACs,7901.9392,top1_acc,-91.22203098106712 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6130.238976,top1_acc,-90.27777777777779 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5411.505664,top1_acc,-89.3760539629005 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5172.495872,top1_acc,-88.17567567567566 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 872, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,4912.907776,top1_acc,-87.90459965928449 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 300, 23: 308})])",MACs,5589.763584,top1_acc,-89.30390492359932 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 1925})])",MACs,6515.328512,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,4929.55392,top1_acc,-88.39590443686006 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5776.016896,top1_acc,-89.61937716262976 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5695.473152,top1_acc,-90.81455805892547 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5523.768832,top1_acc,-89.96539792387543 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6464.07936,top1_acc,-91.63763066202091 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6217.926144,top1_acc,-89.84509466437176 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5532.419584,top1_acc,-89.1156462585034 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6355.027456,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 2645, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 308})])",MACs,6016.271872,top1_acc,-90.40139616055846 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,5556.798976,top1_acc,-89.98242530755711 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5158.27456,top1_acc,-88.62068965517241 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5092.607488,top1_acc,-88.62068965517241 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,6757.68064,top1_acc,-88.51913477537437 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5818.87744,top1_acc,-90.3114186851211 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6453.331456,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5438.76864,top1_acc,-89.22558922558923 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 768, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 1324, 23: 1925})])",MACs,7072.58112,top1_acc,-91.28919860627178 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5513.938432,top1_acc,-89.07849829351535 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,5085.136384,top1_acc,-88.62068965517241 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5373.953536,top1_acc,-89.65517241379311 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,6482.691584,top1_acc,-91.44851657940663 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,5834.737152,top1_acc,-89.83050847457628 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,7757.891072,top1_acc,-91.40893470790378 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5485.430272,top1_acc,-89.45578231292517 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5156.570624,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 1791, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,6777.734656,top1_acc,-90.6896551724138 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 2120, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,7549.35552,top1_acc,-90.75043630017451 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5449.844224,top1_acc,-89.3760539629005 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 1324, 23: 308})])",MACs,6993.479168,top1_acc,-90.27777777777779 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 642})])",MACs,6260.2624,top1_acc,-90.15544041450777 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 1791, 20: 409, 21: 291, 22: 1324, 23: 308})])",MACs,7029.392896,top1_acc,-90.9090909090909 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5641.143808,top1_acc,-89.89547038327525 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 2561, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6374.753792,top1_acc,-91.47826086956522 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 642})])",MACs,6807.488,top1_acc,-90.3114186851211 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5358.224896,top1_acc,-88.85191347753744 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5014.947328,top1_acc,-88.05460750853243 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5491.131904,top1_acc,-90.14084507042254 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5368.251904,top1_acc,-88.66666666666667 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5345.445376,top1_acc,-89.45578231292517 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6050.350592,top1_acc,-90.75043630017451 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6214.518272,top1_acc,-88.58603066439524 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5377.754624,top1_acc,-89.82456140350877 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5121.050112,top1_acc,-88.27586206896552 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6255.609344,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,6956.25472,top1_acc,-90.75342465753423 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5419.7632,top1_acc,-89.45578231292517 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,4976.608768,top1_acc,-88.43537414965985 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 512, 10: 448, 11: 704, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 1324, 23: 642})])",MACs,7717.12768,top1_acc,-91.25214408233276 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 1395, 22: 678, 23: 308})])",MACs,5858.002432,top1_acc,-90.3448275862069 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 1925})])",MACs,6379.013632,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 642})])",MACs,6854.01856,top1_acc,-89.93055555555554 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,6055.921152,top1_acc,-90.43478260869566 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6355.027456,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5372.708352,top1_acc,-89.57264957264958 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5344.462336,top1_acc,-88.62876254180601 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1791, 20: 409, 21: 291, 22: 1324, 23: 308})])",MACs,6954.878464,top1_acc,-90.68541300527241 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5303.4368,top1_acc,-89.82456140350877 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5593.892352,top1_acc,-90.65743944636677 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 640, 10: 384, 11: 192, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 642})])",MACs,6679.889408,top1_acc,-90.52631578947367 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 872, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6294.930944,top1_acc,-90.01751313485114 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5986.125312,top1_acc,-90.46793760831888 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6178.473472,top1_acc,-90.625 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 300, 23: 308})])",MACs,7003.309568,top1_acc,-89.93055555555554 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5411.702272,top1_acc,-89.1156462585034 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,5786.43712,top1_acc,-89.54703832752612 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5886.05184,top1_acc,-89.50086058519794 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5217.58464,top1_acc,-88.66666666666667 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5808.850432,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5937.694208,top1_acc,-90.55944055944055 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 192, 12: 995, 13: 2621, 14: 2632, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 1324, 23: 642})])",MACs,6193.088,top1_acc,-88.50771869639793 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5691.672064,top1_acc,-90.3114186851211 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5820.51584,top1_acc,-90.12131715771231 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5889.918464,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,7450.265088,top1_acc,-90.41095890410959 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5449.451008,top1_acc,-89.77469670710572 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 768, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5650.384384,top1_acc,-89.94708994708994 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5248.910848,top1_acc,-90.01751313485114 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,5632.296448,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5948.835328,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 384, 11: 192, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,7335.0528,top1_acc,-91.40893470790378 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6228.346368,top1_acc,-91.16117850953206 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5597.69344,top1_acc,-89.23076923076923 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,5659.559424,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5668.210176,top1_acc,-90.46793760831888 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,4976.608768,top1_acc,-88.43537414965985 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,5859.247616,top1_acc,-89.78873239436619 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 768, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,7387.547136,top1_acc,-90.27777777777779 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1245, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6050.350592,top1_acc,-90.75043630017451 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,4891.21536,top1_acc,-88.51351351351352 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5050.533376,top1_acc,-88.107202680067 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 192, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 579, 20: 1627, 21: 291, 22: 678, 23: 308})])",MACs,6862.931456,top1_acc,-91.06529209621993 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5631.1168,top1_acc,-89.82456140350877 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,6829.049344,top1_acc,-91.09947643979058 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,6034.621952,top1_acc,-88.96321070234114 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5566.629376,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5401.675264,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 704, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 642})])",MACs,8141.407744,top1_acc,-91.25214408233276 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5102.044672,top1_acc,-88.65979381443299 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6491.342336,top1_acc,-91.63763066202091 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6605.374976,top1_acc,-90.08695652173914 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6112.8064,top1_acc,-90.625 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,6135.41632,top1_acc,-91.50779896013866 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2621, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 1791, 20: 409, 21: 291, 22: 1324, 23: 642})])",MACs,6946.686464,top1_acc,-90.87719298245615 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5818.87744,top1_acc,-90.3114186851211 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 1955, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,6088.361472,top1_acc,-91.13043478260869 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5260.576256,top1_acc,-89.27335640138409 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 704, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,5986.125312,top1_acc,-90.50086355785838 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 642})])",MACs,5314.57792,top1_acc,-90.01751313485114 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 1520, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5209.785856,top1_acc,-88.96672504378283 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 995, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5722.998272,top1_acc,-89.14858096828046 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 768, 10: 448, 11: 192, 12: 3072, 13: 2621, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 642})])",MACs,7950.566912,top1_acc,-91.88255613126081 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 1925})])",MACs,5722.932736,top1_acc,-89.66725043782837 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 2019, 18: 672, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,5709.235712,top1_acc,-89.91150442477877 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 787, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,6232.999424,top1_acc,-90.97222222222221 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 995, 13: 2097, 14: 928, 15: 1494, 16: 3072, 17: 2019, 18: 3072, 19: 579, 20: 409, 21: 291, 22: 300, 23: 308})])",MACs,6114.051584,top1_acc,-90.25641025641026 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 704, 12: 1524, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5424.154112,top1_acc,-89.2361111111111 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 768, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 2097, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 308})])",MACs,5405.0176,top1_acc,-89.82456140350877 +"OrderedDict([(, {0: 768, 1: 704, 2: 768, 3: 768, 4: 768, 5: 640, 6: 640, 7: 512, 8: 576, 9: 320, 10: 384, 11: 192, 12: 2120, 13: 930, 14: 928, 15: 1494, 16: 1456, 17: 787, 18: 672, 19: 579, 20: 409, 21: 291, 22: 678, 23: 642})])",MACs,5159.454208,top1_acc,-88.46815834767642 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 640, 7: 512, 8: 576, 9: 320, 10: 448, 11: 704, 12: 3072, 13: 2097, 14: 2632, 15: 1494, 16: 3072, 17: 2019, 18: 672, 19: 1791, 20: 1627, 21: 291, 22: 1324, 23: 308})])",MACs,7337.281024,top1_acc,-91.06529209621993 diff --git a/eftnas-s1-bert-base-mrpc/search_progression.png b/eftnas-s1-bert-base-mrpc/search_progression.png new file mode 100644 index 0000000000000000000000000000000000000000..cdd65db3249217152e4bec6b51199371b4bcd007 --- /dev/null +++ b/eftnas-s1-bert-base-mrpc/search_progression.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c5102b39b21989e6c19853c300c4d7b6bf37bf48cb8b9cdcb71c96456e27cbf5 +size 120988 diff --git a/eftnas-s1-bert-base-mrpc/special_tokens_map.json b/eftnas-s1-bert-base-mrpc/special_tokens_map.json new file mode 100644 index 0000000000000000000000000000000000000000..a8b3208c2884c4efb86e49300fdd3dc877220cdf --- /dev/null +++ b/eftnas-s1-bert-base-mrpc/special_tokens_map.json @@ -0,0 +1,7 @@ +{ + "cls_token": "[CLS]", + "mask_token": "[MASK]", + "pad_token": "[PAD]", + "sep_token": "[SEP]", + "unk_token": "[UNK]" +} diff --git a/eftnas-s1-bert-base-mrpc/subnetwork_best.pth b/eftnas-s1-bert-base-mrpc/subnetwork_best.pth new file mode 100644 index 0000000000000000000000000000000000000000..fe5fd1e139b877c8a96b694d9f20ca13a4dc4ec4 --- /dev/null +++ b/eftnas-s1-bert-base-mrpc/subnetwork_best.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3625beaeaf6be77b0d71d38254a59c8971ef094b9157218cce375e102c7d6fef +size 1071 diff --git a/eftnas-s1-bert-base-mrpc/tokenizer.json b/eftnas-s1-bert-base-mrpc/tokenizer.json new file mode 100644 index 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b/eftnas-s1-bert-base-qnli/EFTNAS_S1_subnet.pth new file mode 100644 index 0000000000000000000000000000000000000000..221d85d78eb4eaae2c87b43dba5eb48f962a1d24 --- /dev/null +++ b/eftnas-s1-bert-base-qnli/EFTNAS_S1_subnet.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1e876683660957bf62b34f6f35ac6d07482ac195e4699e0662ecfdec95360c8f +size 961 diff --git a/eftnas-s1-bert-base-qnli/README.md b/eftnas-s1-bert-base-qnli/README.md new file mode 100644 index 0000000000000000000000000000000000000000..35c8a532c1f0650a6ea8204c36eb299aa7fc6b24 --- /dev/null +++ b/eftnas-s1-bert-base-qnli/README.md @@ -0,0 +1,88 @@ +--- +language: +- en +license: apache-2.0 +tags: +- generated_from_trainer +datasets: +- glue +metrics: +- accuracy +model-index: +- name: first_try + results: + - task: + name: Text Classification + type: text-classification + dataset: + name: GLUE QNLI + type: glue + config: qnli + split: validation + args: qnli + metrics: + - name: Accuracy + type: accuracy + value: 0.8973091707852828 +--- + + + +# first_try + +This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE QNLI dataset. +It achieves the following results on the evaluation set: +- Loss: 0.5902 +- Accuracy: 0.8973 + +## Model description + +More information needed + +## Intended uses & limitations + +More information needed + +## Training and evaluation data + +More information needed + +## Training procedure + +### Training hyperparameters + +The following hyperparameters were used during training: +- learning_rate: 2e-05 +- train_batch_size: 32 +- eval_batch_size: 128 +- seed: 42 +- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 +- lr_scheduler_type: linear +- num_epochs: 6 +- mixed_precision_training: Native AMP + +### Training results + +| Training Loss | Epoch | Step | Validation Loss | Accuracy | | +|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| +| 0.8032 | 1.0 | 3274 | 0.3192 | 0.8891 | OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1104, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 205})]) | +| 0.8032 | 1.0 | 3274 | 0.2594 | 0.9059 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.5165 | 2.0 | 6548 | 0.3693 | 0.8925 | OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1104, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 205})]) | +| 0.5165 | 2.0 | 6548 | 0.2860 | 0.9200 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.2972 | 3.0 | 9822 | 0.4699 | 0.8949 | OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1104, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 205})]) | +| 0.2972 | 3.0 | 9822 | 0.3910 | 0.9162 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.1611 | 4.0 | 13096 | 0.5542 | 0.8964 | OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1104, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 205})]) | +| 0.1611 | 4.0 | 13096 | 0.4473 | 0.9160 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.1155 | 5.0 | 16370 | 0.5926 | 0.8969 | OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1104, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 205})]) | +| 0.1155 | 5.0 | 16370 | 0.4788 | 0.9180 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0867 | 6.0 | 19644 | 0.6002 | 0.8958 | OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1104, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 205})]) | +| 0.0867 | 6.0 | 19644 | 0.4831 | 0.9176 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | + + +### Framework versions + +- Transformers 4.29.1 +- Pytorch 1.12.1 +- Datasets 2.13.1 +- Tokenizers 0.13.3 diff --git a/eftnas-s1-bert-base-qnli/all_results.json b/eftnas-s1-bert-base-qnli/all_results.json new file mode 100644 index 0000000000000000000000000000000000000000..1575566f7ae70b4f920fdfe182a52b7f6274a099 --- /dev/null +++ b/eftnas-s1-bert-base-qnli/all_results.json @@ -0,0 +1,14 @@ +{ + "epoch": 6.0, + "eval_accuracy": 0.8973091707852828, + "eval_loss": 0.590233564376831, + "eval_runtime": 6.2215, + "eval_samples": 5463, + "eval_samples_per_second": 878.087, + "eval_steps_per_second": 6.912, + "train_loss": 0.3564307890654921, + "train_runtime": 30220.0432, + "train_samples": 104743, + "train_samples_per_second": 20.796, + "train_steps_per_second": 0.65 +} \ No newline at end of file diff --git a/eftnas-s1-bert-base-qnli/cache_MACs.csv b/eftnas-s1-bert-base-qnli/cache_MACs.csv new file mode 100644 index 0000000000000000000000000000000000000000..2bb1d2b3521341304245be5a3fb9781adcea0dfa --- /dev/null +++ b/eftnas-s1-bert-base-qnli/cache_MACs.csv @@ -0,0 +1,993 @@ +"(0, 2, 0, 0, 0, 1, 3, 1, 1, 0, 2, 3, 2, 1, 1, 1, 1, 4, 1, 2, 2, 1, 1, 1)",8741.586432 +"(3, 0, 1, 1, 1, 1, 0, 1, 2, 0, 1, 1, 0, 1, 3, 4, 1, 1, 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1)",9179.760128 +"(2, 2, 3, 2, 1, 1, 2, 1, 2, 0, 2, 1, 1, 2, 4, 4, 4, 2, 2, 3, 0, 4, 4, 4)",6546.458112 +"(0, 1, 3, 2, 0, 0, 3, 1, 0, 0, 0, 4, 2, 1, 2, 0, 3, 1, 3, 4, 1, 2, 0, 0)",8727.168512 +"(0, 1, 3, 2, 1, 0, 1, 0, 1, 1, 0, 1, 1, 3, 2, 1, 2, 0, 4, 1, 2, 3, 2, 1)",8308.131328 +"(3, 0, 3, 0, 0, 1, 1, 1, 1, 1, 0, 4, 1, 3, 1, 1, 0, 2, 3, 1, 1, 4, 3, 3)",8029.07904 +"(1, 2, 3, 0, 1, 1, 2, 1, 2, 1, 2, 2, 3, 4, 1, 3, 1, 1, 3, 3, 0, 2, 2, 3)",7362.119168 +"(0, 1, 1, 0, 1, 2, 1, 2, 2, 0, 2, 1, 0, 1, 3, 3, 4, 2, 0, 0, 2, 2, 3, 2)",7979.92704 +"(2, 2, 3, 2, 0, 0, 2, 0, 1, 0, 1, 1, 1, 3, 2, 4, 4, 4, 1, 3, 0, 4, 3, 4)",6923.290112 +"(2, 2, 0, 2, 1, 1, 0, 1, 2, 1, 1, 1, 3, 2, 2, 2, 3, 2, 0, 0, 2, 1, 3, 3)",7906.52672 +"(0, 1, 2, 2, 2, 2, 0, 1, 0, 1, 0, 0, 3, 2, 2, 0, 3, 1, 3, 1, 4, 4, 0, 3)",7770.53952 +"(0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 2, 0, 3, 1, 3, 0, 1, 2, 0, 3)",9175.369216 +"(1, 1, 0, 0, 0, 1, 3, 1, 1, 1, 1, 2, 4, 3, 1, 2, 2, 1, 4, 3, 3, 2, 2, 3)",7288.391168 +"(0, 1, 1, 1, 2, 2, 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4)",6278.088192 +"(0, 2, 3, 2, 2, 2, 2, 2, 2, 0, 2, 4, 3, 3, 4, 4, 4, 2, 3, 1, 4, 4, 3, 2)",6073.15712 +"(2, 2, 3, 2, 1, 1, 3, 1, 2, 2, 2, 3, 3, 3, 2, 2, 4, 4, 3, 3, 4, 4, 3, 4)",5733.02528 +"(3, 1, 3, 2, 1, 2, 2, 1, 2, 1, 1, 3, 3, 3, 4, 2, 4, 4, 0, 1, 0, 4, 3, 4)",6509.757952 +"(2, 2, 3, 0, 1, 2, 2, 1, 3, 1, 2, 4, 3, 4, 4, 4, 4, 2, 3, 4, 0, 4, 3, 3)",5792.859648 +"(2, 2, 3, 0, 1, 1, 2, 1, 2, 1, 2, 2, 3, 4, 1, 4, 4, 1, 3, 3, 0, 4, 3, 3)",6516.770304 +"(0, 1, 2, 0, 1, 1, 2, 1, 0, 0, 2, 0, 3, 3, 2, 4, 3, 2, 3, 0, 4, 4, 3, 3)",6925.321728 +"(1, 1, 1, 2, 2, 2, 3, 2, 0, 1, 0, 4, 4, 1, 2, 4, 2, 0, 3, 0, 0, 0, 2, 1)",8192.984576 +"(0, 1, 2, 2, 2, 2, 0, 1, 2, 0, 2, 4, 3, 3, 1, 4, 4, 2, 3, 1, 4, 2, 3, 2)",6820.988416 +"(1, 1, 3, 2, 1, 1, 3, 1, 2, 1, 2, 2, 3, 4, 4, 4, 2, 1, 4, 3, 4, 4, 3, 3)",5849.024 +"(1, 1, 3, 0, 1, 1, 0, 2, 2, 1, 2, 4, 0, 4, 1, 2, 1, 4, 3, 4, 4, 1, 3, 2)",7037.388288 +"(0, 1, 1, 0, 0, 2, 0, 1, 0, 0, 0, 0, 2, 1, 2, 3, 3, 1, 3, 0, 1, 2, 0, 3)",8698.660352 +"(3, 1, 2, 0, 1, 0, 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4)",7174.292992 +"(0, 1, 3, 2, 1, 2, 1, 1, 2, 0, 2, 1, 0, 1, 3, 0, 1, 1, 0, 0, 4, 4, 2, 2)",8231.126528 +"(2, 2, 3, 2, 1, 2, 2, 1, 2, 0, 2, 1, 1, 2, 4, 4, 4, 2, 2, 3, 0, 4, 3, 4)",6567.495168 +"(2, 2, 3, 0, 0, 2, 2, 1, 2, 0, 2, 4, 2, 1, 3, 3, 4, 2, 3, 3, 1, 2, 3, 4)",6910.248448 +"(0, 1, 3, 2, 2, 2, 1, 2, 2, 1, 2, 1, 2, 3, 4, 4, 4, 2, 0, 0, 0, 4, 4, 1)",7059.8016 +"(1, 1, 3, 0, 1, 1, 2, 1, 2, 1, 2, 2, 3, 4, 1, 4, 2, 1, 3, 3, 0, 4, 3, 3)",6842.942976 +"(0, 1, 1, 0, 1, 2, 1, 1, 2, 0, 2, 1, 0, 1, 3, 3, 4, 2, 0, 0, 2, 2, 3, 2)",8007.190016 +"(0, 2, 3, 2, 1, 2, 3, 1, 2, 2, 2, 3, 3, 3, 2, 2, 4, 4, 3, 3, 4, 4, 3, 4)",5733.02528 +"(0, 1, 1, 0, 1, 2, 0, 1, 2, 0, 0, 1, 1, 2, 2, 3, 1, 2, 2, 1, 2, 1, 3, 2)",8396.015104 +"(0, 1, 1, 0, 1, 2, 0, 0, 2, 0, 0, 1, 0, 1, 2, 0, 1, 2, 0, 0, 2, 1, 3, 2)",9150.137856 +"(2, 2, 3, 2, 1, 2, 2, 1, 2, 1, 2, 4, 3, 4, 4, 4, 4, 2, 3, 3, 2, 4, 3, 4)",5596.972544 +"(0, 1, 1, 0, 2, 2, 1, 1, 0, 1, 0, 0, 0, 1, 2, 1, 1, 0, 0, 0, 0, 0, 2, 1)",9705.686528 +"(2, 2, 3, 0, 1, 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4)",6223.56224 +"(2, 2, 3, 2, 1, 2, 2, 1, 2, 2, 1, 3, 3, 4, 4, 4, 4, 4, 3, 1, 4, 4, 3, 4)",5376.706048 +"(0, 1, 1, 0, 1, 2, 1, 2, 2, 0, 0, 1, 0, 1, 2, 3, 4, 2, 0, 0, 2, 2, 3, 2)",8253.998592 +"(0, 1, 3, 0, 1, 1, 2, 1, 2, 1, 1, 2, 3, 4, 2, 0, 1, 1, 3, 0, 1, 4, 3, 4)",7473.202688 +"(2, 2, 3, 0, 1, 1, 2, 1, 2, 0, 2, 1, 0, 2, 2, 4, 4, 1, 0, 0, 0, 2, 4, 4)",7699.76064 +"(2, 2, 3, 2, 1, 1, 3, 1, 2, 2, 2, 1, 3, 3, 2, 4, 4, 4, 2, 3, 0, 2, 4, 4)",6202.197504 +"(2, 2, 3, 2, 1, 1, 2, 2, 3, 1, 2, 4, 3, 4, 4, 4, 4, 2, 3, 4, 4, 4, 3, 3)",5355.079168 +"(2, 2, 1, 2, 1, 2, 1, 2, 2, 1, 2, 1, 3, 1, 4, 4, 4, 2, 2, 1, 2, 4, 3, 4)",6452.545024 +"(0, 1, 3, 0, 0, 2, 2, 2, 2, 0, 2, 4, 3, 4, 4, 3, 4, 4, 0, 0, 2, 4, 4, 3)",6394.676736 +"(0, 1, 3, 0, 2, 2, 3, 1, 0, 1, 0, 0, 3, 4, 2, 1, 1, 0, 0, 0, 1, 0, 2, 4)",8467.711488 +"(0, 1, 3, 0, 0, 2, 1, 2, 2, 0, 0, 1, 2, 1, 2, 0, 1, 1, 3, 0, 1, 2, 2, 2)",8737.916416 +"(0, 2, 3, 2, 1, 1, 3, 1, 2, 1, 2, 4, 3, 4, 4, 4, 4, 2, 3, 3, 2, 4, 3, 4)",5706.024448 +"(0, 1, 1, 0, 2, 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4)",6993.544704 +"(2, 1, 3, 2, 0, 2, 3, 2, 1, 1, 2, 2, 3, 4, 1, 4, 1, 2, 4, 0, 1, 4, 3, 3)",6725.436928 +"(2, 2, 3, 2, 1, 2, 3, 2, 2, 2, 2, 2, 3, 4, 4, 4, 4, 4, 3, 4, 0, 2, 3, 4)",5570.82368 +"(2, 2, 3, 2, 1, 2, 3, 2, 3, 2, 2, 4, 3, 4, 4, 4, 4, 4, 3, 3, 4, 4, 4, 3)",4943.250944 +"(2, 2, 3, 2, 1, 2, 3, 2, 3, 1, 2, 2, 3, 4, 4, 4, 4, 2, 3, 3, 0, 2, 4, 3)",5927.405056 +"(2, 1, 3, 0, 0, 2, 1, 2, 2, 1, 0, 3, 2, 4, 2, 2, 1, 1, 1, 0, 0, 2, 3, 3)",8027.244032 +"(2, 2, 3, 0, 1, 2, 3, 2, 2, 1, 2, 2, 3, 4, 2, 4, 3, 2, 4, 3, 2, 4, 4, 3)",5871.896064 +"(2, 2, 3, 0, 0, 2, 2, 1, 3, 1, 0, 2, 3, 4, 1, 4, 1, 1, 4, 0, 1, 4, 3, 3)",7053.837824 +"(2, 2, 3, 0, 0, 2, 2, 2, 3, 2, 2, 2, 3, 4, 4, 4, 3, 2, 3, 3, 0, 2, 3, 3)",6293.751296 +"(0, 1, 2, 0, 0, 2, 2, 1, 0, 1, 0, 2, 2, 4, 3, 0, 1, 1, 4, 0, 1, 2, 2, 3)",7997.818368 +"(2, 2, 2, 0, 0, 2, 2, 2, 0, 1, 0, 3, 0, 4, 3, 4, 3, 2, 3, 0, 4, 2, 4, 3)",6806.439424 +"(2, 2, 3, 0, 0, 2, 2, 2, 2, 1, 1, 3, 1, 4, 3, 2, 1, 2, 3, 0, 1, 4, 3, 3)",7169.967616 +"(2, 2, 3, 2, 1, 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4)",6334.711296 +"(2, 2, 3, 2, 1, 2, 3, 2, 2, 2, 1, 4, 3, 4, 4, 4, 4, 3, 4, 3, 4, 4, 3, 4)",5057.283584 +"(2, 2, 3, 2, 1, 2, 3, 2, 3, 2, 2, 2, 3, 4, 4, 4, 3, 4, 3, 3, 0, 2, 2, 3)",5986.715136 +"(2, 2, 3, 0, 1, 2, 3, 2, 2, 2, 2, 4, 3, 4, 4, 4, 4, 1, 3, 4, 4, 4, 2, 4)",5430.773248 +"(2, 2, 3, 0, 0, 2, 2, 1, 2, 1, 1, 2, 3, 4, 2, 4, 4, 2, 4, 3, 2, 4, 4, 4)",5861.017088 +"(2, 1, 3, 0, 1, 2, 2, 1, 3, 1, 2, 2, 3, 4, 1, 4, 1, 2, 3, 3, 1, 2, 3, 3)",6847.79264 +"(2, 2, 3, 0, 1, 2, 2, 1, 2, 1, 2, 2, 2, 4, 3, 3, 4, 2, 4, 0, 2, 2, 3, 4)",6482.953728 +"(2, 2, 3, 0, 1, 2, 2, 1, 2, 1, 0, 2, 3, 4, 2, 0, 4, 1, 3, 0, 1, 4, 3, 4)",7019.890176 +"(2, 2, 3, 2, 1, 2, 3, 2, 2, 2, 2, 4, 3, 4, 4, 4, 4, 2, 3, 3, 2, 4, 4, 4)",5357.83168 +"(2, 1, 3, 0, 0, 2, 2, 1, 2, 1, 2, 1, 3, 4, 2, 0, 1, 1, 3, 3, 0, 2, 4, 3)",7334.72512 +"(2, 1, 3, 2, 1, 2, 3, 2, 3, 2, 2, 4, 3, 2, 4, 4, 4, 1, 4, 3, 4, 4, 4, 4)",5391.779328 +"(2, 1, 2, 0, 0, 2, 2, 0, 0, 1, 0, 3, 1, 4, 2, 0, 1, 2, 0, 0, 1, 2, 2, 3)",8501.724672 +"(2, 1, 2, 0, 0, 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3)",6435.636736 +"(2, 2, 3, 0, 0, 2, 2, 1, 2, 1, 0, 2, 3, 4, 1, 0, 1, 1, 4, 0, 1, 4, 3, 3)",7468.41856 +"(2, 1, 3, 0, 0, 2, 2, 1, 2, 1, 0, 1, 3, 4, 2, 0, 1, 1, 2, 0, 1, 2, 3, 3)",7913.73568 +"(2, 2, 3, 0, 0, 2, 2, 2, 2, 1, 1, 2, 3, 4, 2, 4, 1, 2, 3, 3, 1, 4, 4, 4)",6406.276608 +"(2, 2, 3, 2, 1, 2, 3, 2, 2, 1, 2, 4, 3, 4, 4, 4, 4, 2, 4, 3, 4, 4, 4, 4)",5071.635968 +"(2, 1, 3, 0, 0, 2, 2, 0, 1, 1, 0, 3, 1, 4, 2, 2, 3, 2, 1, 0, 1, 4, 3, 3)",7612.92544 +"(2, 2, 3, 2, 1, 2, 2, 1, 3, 1, 2, 2, 3, 4, 2, 4, 4, 2, 4, 3, 2, 4, 4, 4)",5642.91328 +"(2, 1, 3, 2, 1, 2, 2, 1, 2, 1, 2, 2, 3, 4, 1, 4, 4, 2, 4, 3, 4, 4, 3, 3)",5770.118656 +"(2, 1, 3, 0, 0, 2, 2, 0, 0, 1, 0, 2, 0, 4, 3, 0, 1, 1, 0, 0, 1, 2, 2, 3)",8553.03936 +"(2, 1, 3, 0, 1, 2, 2, 1, 2, 1, 2, 2, 3, 4, 1, 4, 4, 2, 3, 3, 1, 4, 3, 3)",6304.105984 +"(0, 1, 2, 0, 0, 2, 2, 1, 2, 1, 0, 0, 2, 4, 3, 0, 1, 1, 4, 0, 1, 2, 3, 3)",7848.85504 +"(2, 1, 3, 2, 0, 2, 3, 2, 2, 2, 1, 4, 3, 4, 4, 0, 1, 4, 4, 3, 4, 4, 4, 4)",5674.37056 +"(2, 2, 3, 0, 1, 2, 3, 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3)",7296.583168 +"(2, 1, 3, 0, 1, 2, 3, 2, 2, 1, 2, 2, 3, 4, 4, 4, 4, 1, 3, 3, 2, 4, 4, 4)",5713.495552 +"(0, 1, 3, 0, 0, 2, 2, 1, 0, 1, 1, 2, 0, 4, 1, 0, 1, 2, 4, 3, 1, 2, 3, 3)",7713.654272 +"(2, 1, 3, 0, 1, 2, 3, 2, 3, 1, 1, 2, 3, 4, 1, 4, 4, 2, 0, 3, 2, 4, 3, 4)",6344.738304 +"(0, 1, 3, 2, 0, 2, 3, 1, 3, 2, 2, 0, 3, 4, 4, 4, 4, 4, 0, 0, 4, 2, 4, 4)",6006.63808 +"(0, 1, 2, 0, 1, 2, 2, 0, 0, 1, 0, 0, 3, 4, 4, 0, 1, 1, 4, 0, 1, 2, 4, 3)",7670.9248 +"(2, 2, 3, 2, 0, 2, 2, 2, 2, 2, 2, 4, 3, 2, 2, 4, 4, 2, 4, 3, 4, 4, 4, 4)",5601.560064 +"(2, 2, 3, 2, 1, 2, 3, 2, 2, 2, 2, 2, 3, 4, 4, 4, 1, 4, 3, 3, 4, 4, 4, 4)",5294.786048 +"(2, 1, 3, 0, 1, 2, 3, 2, 2, 1, 0, 4, 3, 4, 3, 0, 4, 1, 3, 0, 4, 4, 3, 3)",6566.708736 +"(2, 2, 3, 0, 1, 2, 2, 2, 2, 2, 2, 2, 3, 4, 2, 4, 4, 2, 3, 3, 2, 4, 4, 4)",5786.961408 +"(0, 1, 3, 0, 1, 2, 3, 0, 3, 2, 2, 2, 0, 4, 3, 0, 1, 2, 3, 3, 1, 2, 4, 4)",7205.225984 +"(2, 1, 3, 2, 1, 2, 3, 2, 3, 2, 2, 4, 3, 4, 4, 4, 1, 2, 4, 3, 4, 4, 3, 4)",5491.459584 +"(0, 1, 3, 0, 0, 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "39 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"39 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "40 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"40 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "41 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"41 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "44 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"41 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"42 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "44 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"43 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "44 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"44 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"46 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"47 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" -> "51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"52 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"53 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"56 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"324 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"330 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"333 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"334 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"339 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"340 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"342 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"343 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"347 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"348 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "359 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"359 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "361 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"361 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "362 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"362 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "363 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"363 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"364 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"365 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "367 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"367 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"370 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"371 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "373 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"373 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"374 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"375 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "377 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"377 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"380 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"381 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "393 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"383 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"384 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "386 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"386 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "387 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"387 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "395 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"388 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"389 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "391 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"391 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "392 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"392 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"393 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "394 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"394 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"395 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "397 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"397 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "398 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"398 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "399 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"399 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "400 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"400 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "402 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"402 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "403 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"403 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "404 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"404 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"405 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"406 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "408 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"408 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"411 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"412 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "414 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"414 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"415 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"416 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "418 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"418 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"421 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"422 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "434 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"424 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"425 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "427 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"427 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "428 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"428 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "436 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"429 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"430 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "432 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"432 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "433 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"433 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"434 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "435 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"435 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"436 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "438 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"438 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "439 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"439 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "440 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"440 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "441 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"441 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "443 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"443 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "444 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"444 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "445 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"445 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"446 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"447 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "449 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"449 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"452 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"453 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "455 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"455 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"456 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"457 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "459 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"459 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" -> "461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "491 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"462 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"463 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "475 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"465 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"466 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "468 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"468 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "469 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"469 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "477 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"470 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"471 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "472 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"42 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "43 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"43 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"44 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "46 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"46 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"47 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "52 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"52 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "53 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"53 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "56 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"56 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "311 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0000000000000000000000000000000000000000..e57fe619d5bb3245e1a55cf11d1b81ce61561c54 --- /dev/null +++ b/eftnas-s1-bert-base-qnli/search_progression.csv @@ -0,0 +1,1000 @@ +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 768, 4: 768, 5: 704, 6: 448, 7: 512, 8: 576, 9: 768, 10: 384, 11: 512, 12: 2272, 13: 2787, 14: 2806, 15: 2810, 16: 2818, 17: 1023, 18: 2773, 19: 2205, 20: 2123, 21: 2568, 22: 2402, 23: 2064})])",MACs,8741.586432,top1_acc,-91.25022881200805 +"OrderedDict([(, {0: 512, 1: 768, 2: 512, 3: 704, 4: 640, 5: 704, 6: 768, 7: 512, 8: 512, 9: 768, 10: 512, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 1102, 16: 2818, 17: 2794, 18: 1048, 19: 2205, 20: 1548, 21: 772, 22: 1132, 23: 205})])",MACs,7397.312,top1_acc,-90.62786015010069 +"OrderedDict([(, {0: 640, 1: 448, 2: 384, 3: 576, 4: 576, 5: 768, 6: 576, 7: 768, 8: 448, 9: 768, 10: 512, 11: 448, 12: 1708, 13: 3072, 14: 2338, 15: 3072, 16: 1067, 17: 2233, 18: 1048, 19: 2205, 20: 2690, 21: 3072, 22: 3072, 23: 1194})])",MACs,8208.385536,top1_acc,-91.03056928427604 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 768, 6: 448, 7: 768, 8: 448, 9: 768, 10: 384, 11: 640, 12: 1708, 13: 1066, 14: 1126, 15: 2810, 16: 2310, 17: 1637, 18: 2212, 19: 1061, 20: 3072, 21: 772, 22: 1132, 23: 2064})])",MACs,7340.492288,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 704, 4: 640, 5: 768, 6: 448, 7: 768, 8: 576, 9: 448, 10: 512, 11: 576, 12: 1104, 13: 1716, 14: 2806, 15: 3072, 16: 2310, 17: 1023, 18: 1048, 19: 1670, 20: 3072, 21: 1367, 22: 1751, 23: 205})])",MACs,6965.75744,top1_acc,-90.73768991396669 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 768, 4: 576, 5: 704, 6: 704, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 2810, 13: 1716, 14: 1126, 15: 2281, 16: 1714, 17: 2794, 18: 2773, 19: 3072, 20: 3072, 21: 1925, 22: 2402, 23: 2064})])",MACs,8373.405184,top1_acc,-91.21361889071939 +"OrderedDict([(, {0: 512, 1: 448, 2: 384, 3: 704, 4: 576, 5: 512, 6: 448, 7: 512, 8: 448, 9: 768, 10: 384, 11: 768, 12: 1104, 13: 1066, 14: 2806, 15: 3072, 16: 3072, 17: 3072, 18: 2212, 19: 1061, 20: 3072, 21: 3072, 22: 3072, 23: 3072})])",MACs,8603.82976,top1_acc,-91.25022881200805 +"OrderedDict([(, {0: 512, 1: 448, 2: 768, 3: 704, 4: 576, 5: 704, 6: 704, 7: 448, 8: 448, 9: 768, 10: 512, 11: 768, 12: 1708, 13: 1716, 14: 1126, 15: 1740, 16: 1714, 17: 1023, 18: 1048, 19: 2760, 20: 2123, 21: 1367, 22: 3072, 23: 1194})])",MACs,7184.188928,top1_acc,-90.35328574043567 +"OrderedDict([(, {0: 640, 1: 448, 2: 320, 3: 768, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 2281, 16: 2310, 17: 2794, 18: 3072, 19: 2205, 20: 984, 21: 1925, 22: 1132, 23: 584})])",MACs,7222.724096,top1_acc,-90.82921471718835 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 576, 4: 768, 5: 768, 6: 576, 7: 448, 8: 512, 9: 320, 10: 768, 11: 768, 12: 1708, 13: 1716, 14: 2338, 15: 3072, 16: 1714, 17: 2233, 18: 2773, 19: 2760, 20: 3072, 21: 1367, 22: 609, 23: 584})])",MACs,7734.756864,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 640, 1: 320, 2: 768, 3: 576, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 448, 10: 768, 11: 448, 12: 1104, 13: 3072, 14: 2338, 15: 2281, 16: 2310, 17: 1023, 18: 3072, 19: 1061, 20: 2123, 21: 1925, 22: 2402, 23: 584})])",MACs,7824.868864,top1_acc,-90.86582463847702 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 576, 4: 768, 5: 704, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 448, 12: 2272, 13: 1716, 14: 1776, 15: 1740, 16: 2310, 17: 1637, 18: 2212, 19: 2760, 20: 1548, 21: 1925, 22: 3072, 23: 205})])",MACs,7528.252928,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 576, 4: 768, 5: 512, 6: 704, 7: 768, 8: 448, 9: 768, 10: 512, 11: 448, 12: 2810, 13: 1716, 14: 2806, 15: 3072, 16: 2818, 17: 3072, 18: 2773, 19: 1061, 20: 984, 21: 2568, 22: 3072, 23: 2064})])",MACs,8801.289728,top1_acc,-91.01226432363171 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 704, 4: 576, 5: 768, 6: 448, 7: 512, 8: 512, 9: 768, 10: 512, 11: 640, 12: 2272, 13: 2787, 14: 2338, 15: 3072, 16: 1714, 17: 1023, 18: 2212, 19: 2760, 20: 1548, 21: 1367, 22: 1751, 23: 1194})])",MACs,7725.581824,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 576, 4: 576, 5: 512, 6: 448, 7: 512, 8: 768, 9: 768, 10: 384, 11: 640, 12: 2272, 13: 1716, 14: 2338, 15: 2810, 16: 2818, 17: 1023, 18: 1642, 19: 2205, 20: 984, 21: 1367, 22: 2402, 23: 1194})])",MACs,7585.531392,top1_acc,-90.79260479589969 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 576, 4: 768, 5: 512, 6: 448, 7: 512, 8: 448, 9: 768, 10: 384, 11: 448, 12: 2810, 13: 1066, 14: 1126, 15: 3072, 16: 1714, 17: 3072, 18: 2773, 19: 1670, 20: 984, 21: 3072, 22: 2402, 23: 205})])",MACs,7575.111168,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 576, 4: 768, 5: 704, 6: 704, 7: 768, 8: 448, 9: 448, 10: 512, 11: 640, 12: 1708, 13: 3072, 14: 2338, 15: 3072, 16: 2310, 17: 2233, 18: 2212, 19: 2205, 20: 984, 21: 772, 22: 3072, 23: 1194})])",MACs,8139.376128,top1_acc,-90.48142046494601 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 576, 4: 768, 5: 704, 6: 704, 7: 768, 8: 576, 9: 768, 10: 768, 11: 640, 12: 1708, 13: 1716, 14: 2338, 15: 2281, 16: 2310, 17: 1637, 18: 3072, 19: 2205, 20: 2123, 21: 1367, 22: 2402, 23: 1194})])",MACs,8250.983936,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 576, 4: 640, 5: 704, 6: 704, 7: 768, 8: 576, 9: 320, 10: 384, 11: 512, 12: 1104, 13: 3072, 14: 1776, 15: 1740, 16: 1067, 17: 2794, 18: 2212, 19: 2205, 20: 2690, 21: 1367, 22: 2402, 23: 2064})])",MACs,7924.090368,top1_acc,-90.71938495332235 +"OrderedDict([(, {0: 640, 1: 448, 2: 320, 3: 768, 4: 576, 5: 512, 6: 448, 7: 768, 8: 576, 9: 320, 10: 768, 11: 640, 12: 1104, 13: 3072, 14: 3072, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 1548, 21: 3072, 22: 3072, 23: 2064})])",MACs,7977.698816,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 704, 4: 768, 5: 768, 6: 448, 7: 768, 8: 512, 9: 320, 10: 384, 11: 512, 12: 2272, 13: 1716, 14: 1126, 15: 1740, 16: 3072, 17: 2794, 18: 1048, 19: 2205, 20: 984, 21: 3072, 22: 3072, 23: 2064})])",MACs,7756.318208,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 768, 5: 768, 6: 576, 7: 768, 8: 576, 9: 768, 10: 768, 11: 512, 12: 2810, 13: 2787, 14: 2338, 15: 1740, 16: 1714, 17: 1637, 18: 3072, 19: 1061, 20: 984, 21: 2568, 22: 1132, 23: 205})])",MACs,7416.120832,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 576, 4: 640, 5: 704, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 3072, 15: 3072, 16: 3072, 17: 2233, 18: 2212, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,8218.543616,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 704, 4: 768, 5: 768, 6: 576, 7: 768, 8: 576, 9: 320, 10: 512, 11: 640, 12: 3072, 13: 1716, 14: 3072, 15: 1102, 16: 1067, 17: 1023, 18: 2773, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,7255.42656,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 576, 4: 576, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2272, 14: 2338, 15: 1102, 16: 2310, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8152.745472,top1_acc,-91.54310818231741 +"OrderedDict([(, {0: 640, 1: 768, 2: 512, 3: 704, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 320, 10: 512, 11: 768, 12: 2272, 13: 1716, 14: 1776, 15: 1740, 16: 2818, 17: 2794, 18: 2212, 19: 1061, 20: 984, 21: 3072, 22: 2402, 23: 584})])",MACs,7606.240768,top1_acc,-90.82921471718835 +"OrderedDict([(, {0: 640, 1: 448, 2: 768, 3: 768, 4: 640, 5: 768, 6: 448, 7: 512, 8: 448, 9: 320, 10: 768, 11: 512, 12: 1104, 13: 3072, 14: 2806, 15: 2281, 16: 3072, 17: 1023, 18: 1642, 19: 1670, 20: 1548, 21: 3072, 22: 1751, 23: 1194})])",MACs,7764.3136,top1_acc,-90.71938495332235 +"OrderedDict([(, {0: 640, 1: 320, 2: 512, 3: 576, 4: 640, 5: 512, 6: 704, 7: 512, 8: 576, 9: 768, 10: 512, 11: 768, 12: 1708, 13: 1716, 14: 1776, 15: 1102, 16: 2818, 17: 3072, 18: 1048, 19: 2760, 20: 1548, 21: 3072, 22: 3072, 23: 2064})])",MACs,8063.354368,top1_acc,-90.51803038623467 +"OrderedDict([(, {0: 640, 1: 320, 2: 512, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 512, 11: 448, 12: 1708, 13: 2272, 14: 2338, 15: 1102, 16: 2310, 17: 2233, 18: 3072, 19: 1670, 20: 3072, 21: 1367, 22: 3072, 23: 584})])",MACs,7684.556288,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 768, 1: 768, 2: 512, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 448, 9: 448, 10: 384, 11: 640, 12: 2272, 13: 3072, 14: 1126, 15: 1740, 16: 2818, 17: 2233, 18: 2212, 19: 1061, 20: 3072, 21: 772, 22: 609, 23: 3072})])",MACs,7675.18464,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 640, 1: 448, 2: 320, 3: 576, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 448, 10: 384, 11: 448, 12: 2810, 13: 1716, 14: 2806, 15: 2810, 16: 2818, 17: 1023, 18: 1642, 19: 1061, 20: 2690, 21: 772, 22: 1751, 23: 584})])",MACs,7201.752576,top1_acc,-90.79260479589969 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 640, 5: 704, 6: 448, 7: 512, 8: 576, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2787, 14: 2806, 15: 1102, 16: 1714, 17: 2233, 18: 1048, 19: 3072, 20: 984, 21: 1925, 22: 1751, 23: 2064})])",MACs,8209.499648,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 768, 4: 640, 5: 768, 6: 448, 7: 768, 8: 512, 9: 768, 10: 512, 11: 512, 12: 1104, 13: 1066, 14: 2338, 15: 1740, 16: 3072, 17: 1023, 18: 1642, 19: 2205, 20: 984, 21: 1925, 22: 3072, 23: 2064})])",MACs,7343.834624,top1_acc,-90.591250228812 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 576, 4: 576, 5: 768, 6: 704, 7: 512, 8: 768, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 1716, 14: 2338, 15: 2810, 16: 1067, 17: 3072, 18: 3072, 19: 2760, 20: 3072, 21: 1367, 22: 1751, 23: 2064})])",MACs,8648.263168,top1_acc,-91.43327841845141 +"OrderedDict([(, {0: 512, 1: 320, 2: 384, 3: 768, 4: 640, 5: 768, 6: 704, 7: 448, 8: 512, 9: 768, 10: 768, 11: 640, 12: 1104, 13: 2787, 14: 1126, 15: 1740, 16: 2818, 17: 2233, 18: 2212, 19: 1061, 20: 3072, 21: 1367, 22: 609, 23: 2064})])",MACs,7444.628992,top1_acc,-90.536335346879 +"OrderedDict([(, {0: 640, 1: 320, 2: 768, 3: 576, 4: 768, 5: 512, 6: 704, 7: 512, 8: 448, 9: 768, 10: 768, 11: 448, 12: 1104, 13: 2272, 14: 1776, 15: 1740, 16: 2818, 17: 2794, 18: 1642, 19: 1061, 20: 3072, 21: 772, 22: 2402, 23: 3072})])",MACs,7903.118848,top1_acc,-90.28006589785832 +"OrderedDict([(, {0: 576, 1: 320, 2: 512, 3: 576, 4: 768, 5: 512, 6: 768, 7: 512, 8: 768, 9: 448, 10: 384, 11: 448, 12: 2272, 13: 2787, 14: 1126, 15: 2281, 16: 1067, 17: 2233, 18: 1642, 19: 2760, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7232.16128,top1_acc,-90.93904448105437 +"OrderedDict([(, {0: 512, 1: 768, 2: 384, 3: 576, 4: 640, 5: 704, 6: 576, 7: 768, 8: 512, 9: 320, 10: 768, 11: 448, 12: 3072, 13: 1066, 14: 2338, 15: 3072, 16: 3072, 17: 1023, 18: 1642, 19: 1061, 20: 2690, 21: 2568, 22: 609, 23: 3072})])",MACs,7943.489024,top1_acc,-90.82921471718835 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 768, 4: 576, 5: 704, 6: 576, 7: 768, 8: 768, 9: 320, 10: 512, 11: 768, 12: 3072, 13: 2787, 14: 1126, 15: 2810, 16: 2310, 17: 1023, 18: 2773, 19: 3072, 20: 2690, 21: 3072, 22: 1132, 23: 1194})])",MACs,8456.242688,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 768, 6: 768, 7: 512, 8: 512, 9: 768, 10: 768, 11: 768, 12: 1708, 13: 1716, 14: 2338, 15: 3072, 16: 1714, 17: 2794, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 3072, 23: 584})])",MACs,7967.933952,top1_acc,-91.28683873329673 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 576, 9: 768, 10: 768, 11: 768, 12: 1708, 13: 1716, 14: 2338, 15: 3072, 16: 2310, 17: 2794, 18: 3072, 19: 2205, 20: 2123, 21: 1367, 22: 3072, 23: 1194})])",MACs,8956.544512,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 768, 4: 640, 5: 768, 6: 704, 7: 768, 8: 512, 9: 768, 10: 512, 11: 512, 12: 1104, 13: 2272, 14: 2338, 15: 1740, 16: 3072, 17: 3072, 18: 1642, 19: 2205, 20: 3072, 21: 1925, 22: 3072, 23: 2064})])",MACs,8503.363072,top1_acc,-91.30514369394106 +"OrderedDict([(, {0: 640, 1: 320, 2: 320, 3: 576, 4: 640, 5: 768, 6: 768, 7: 768, 8: 576, 9: 448, 10: 768, 11: 576, 12: 1104, 13: 3072, 14: 2338, 15: 3072, 16: 2310, 17: 1023, 18: 3072, 19: 1670, 20: 2123, 21: 1925, 22: 2402, 23: 205})])",MACs,7834.7648,top1_acc,-90.93904448105437 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 768, 6: 448, 7: 768, 8: 448, 9: 768, 10: 512, 11: 768, 12: 1708, 13: 1066, 14: 1776, 15: 2810, 16: 2310, 17: 3072, 18: 2212, 19: 1061, 20: 3072, 21: 3072, 22: 3072, 23: 2064})])",MACs,8693.089792,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 512, 1: 768, 2: 512, 3: 704, 4: 768, 5: 768, 6: 576, 7: 768, 8: 576, 9: 768, 10: 768, 11: 640, 12: 3072, 13: 2787, 14: 3072, 15: 1740, 16: 1714, 17: 1637, 18: 3072, 19: 1061, 20: 984, 21: 2568, 22: 1132, 23: 205})])",MACs,7993.624064,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 704, 4: 576, 5: 512, 6: 704, 7: 448, 8: 768, 9: 448, 10: 768, 11: 768, 12: 2272, 13: 1716, 14: 2338, 15: 2810, 16: 2818, 17: 3072, 18: 2212, 19: 2760, 20: 3072, 21: 3072, 22: 1751, 23: 2064})])",MACs,9052.882432,top1_acc,-91.52480322167308 +"OrderedDict([(, {0: 640, 1: 768, 2: 768, 3: 768, 4: 640, 5: 768, 6: 448, 7: 512, 8: 448, 9: 320, 10: 768, 11: 448, 12: 1104, 13: 1716, 14: 2806, 15: 2281, 16: 3072, 17: 1023, 18: 2773, 19: 1670, 20: 1548, 21: 3072, 22: 1751, 23: 1194})])",MACs,7829.128704,top1_acc,-90.51803038623467 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 576, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 640, 12: 3072, 13: 2787, 14: 2338, 15: 1740, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8724.678144,top1_acc,-91.57971810360608 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 576, 5: 704, 6: 768, 7: 448, 8: 512, 9: 768, 10: 512, 11: 640, 12: 1708, 13: 2272, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8012.760576,top1_acc,-91.26853377265239 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 448, 9: 768, 10: 512, 11: 448, 12: 2810, 13: 2787, 14: 1126, 15: 3072, 16: 2818, 17: 2233, 18: 2773, 19: 1061, 20: 1548, 21: 1367, 22: 3072, 23: 2064})])",MACs,8336.836096,top1_acc,-90.9024345597657 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 576, 4: 576, 5: 512, 6: 448, 7: 512, 8: 768, 9: 768, 10: 384, 11: 640, 12: 2272, 13: 1716, 14: 2338, 15: 2810, 16: 2818, 17: 1023, 18: 1642, 19: 2205, 20: 984, 21: 772, 22: 2402, 23: 584})])",MACs,7348.618752,top1_acc,-90.62786015010069 +"OrderedDict([(, {0: 640, 1: 320, 2: 768, 3: 704, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 448, 10: 768, 11: 576, 12: 1104, 13: 3072, 14: 2806, 15: 3072, 16: 2310, 17: 1023, 18: 3072, 19: 1061, 20: 3072, 21: 1925, 22: 2402, 23: 584})])",MACs,8368.031232,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 640, 1: 320, 2: 512, 3: 576, 4: 640, 5: 512, 6: 704, 7: 512, 8: 576, 9: 768, 10: 768, 11: 768, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 2818, 17: 3072, 18: 1048, 19: 2760, 20: 3072, 21: 3072, 22: 3072, 23: 2064})])",MACs,8582.53056,top1_acc,-90.97565440234303 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 576, 4: 768, 5: 512, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 448, 12: 2272, 13: 2787, 14: 1776, 15: 1740, 16: 1067, 17: 2233, 18: 2212, 19: 2760, 20: 2690, 21: 1925, 22: 1132, 23: 205})])",MACs,7372.932608,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 640, 1: 448, 2: 384, 3: 576, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 1067, 17: 2794, 18: 3072, 19: 2205, 20: 984, 21: 1925, 22: 1132, 23: 1194})])",MACs,7161.775616,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 640, 1: 448, 2: 320, 3: 768, 4: 768, 5: 768, 6: 576, 7: 768, 8: 576, 9: 320, 10: 768, 11: 640, 12: 2810, 13: 3072, 14: 3072, 15: 1740, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 1548, 21: 3072, 22: 3072, 23: 2064})])",MACs,8683.914752,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 768, 10: 384, 11: 512, 12: 2272, 13: 2787, 14: 2806, 15: 2810, 16: 2818, 17: 2794, 18: 2773, 19: 2205, 20: 3072, 21: 2568, 22: 2402, 23: 2064})])",MACs,9385.412096,top1_acc,-91.36005857587406 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 576, 4: 576, 5: 768, 6: 704, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 1716, 14: 2338, 15: 2810, 16: 1067, 17: 3072, 18: 3072, 19: 2760, 20: 3072, 21: 1367, 22: 1751, 23: 2064})])",MACs,8539.211264,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 640, 5: 768, 6: 704, 7: 512, 8: 512, 9: 768, 10: 768, 11: 640, 12: 1708, 13: 1716, 14: 2338, 15: 2281, 16: 1714, 17: 1637, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 2402, 23: 584})])",MACs,7262.373376,top1_acc,-90.60955518945634 +"OrderedDict([(, {0: 640, 1: 320, 2: 768, 3: 576, 4: 768, 5: 512, 6: 448, 7: 512, 8: 448, 9: 768, 10: 768, 11: 448, 12: 1104, 13: 1066, 14: 1776, 15: 1740, 16: 2818, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 2402, 23: 3072})])",MACs,6798.247424,top1_acc,-90.31667581914698 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 704, 4: 768, 5: 768, 6: 448, 7: 768, 8: 576, 9: 448, 10: 512, 11: 448, 12: 1104, 13: 1716, 14: 2806, 15: 2281, 16: 2310, 17: 1023, 18: 1048, 19: 1061, 20: 3072, 21: 1367, 22: 1751, 23: 584})])",MACs,6955.861504,top1_acc,-90.536335346879 +"OrderedDict([(, {0: 640, 1: 320, 2: 512, 3: 576, 4: 640, 5: 512, 6: 704, 7: 512, 8: 576, 9: 768, 10: 384, 11: 640, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 2818, 17: 1637, 18: 1048, 19: 2760, 20: 1548, 21: 772, 22: 1132, 23: 2064})])",MACs,6710.756864,top1_acc,-90.591250228812 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 768, 6: 576, 7: 768, 8: 576, 9: 320, 10: 512, 11: 512, 12: 2810, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 2773, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6677.923328,top1_acc,-90.93904448105437 +"OrderedDict([(, {0: 640, 1: 768, 2: 512, 3: 576, 4: 640, 5: 768, 6: 448, 7: 512, 8: 768, 9: 320, 10: 512, 11: 576, 12: 2810, 13: 1716, 14: 1776, 15: 1740, 16: 1067, 17: 2794, 18: 3072, 19: 1061, 20: 984, 21: 1367, 22: 2402, 23: 584})])",MACs,7201.621504,top1_acc,-90.55464030752334 +"OrderedDict([(, {0: 512, 1: 448, 2: 768, 3: 768, 4: 576, 5: 704, 6: 704, 7: 448, 8: 448, 9: 320, 10: 384, 11: 512, 12: 2810, 13: 3072, 14: 1126, 15: 2281, 16: 1714, 17: 2794, 18: 1642, 19: 3072, 20: 3072, 21: 1925, 22: 2402, 23: 2064})])",MACs,8308.59008,top1_acc,-91.30514369394106 +"OrderedDict([(, {0: 512, 1: 320, 2: 384, 3: 576, 4: 640, 5: 768, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 1104, 13: 2272, 14: 1126, 15: 1102, 16: 2310, 17: 2233, 18: 2212, 19: 1061, 20: 3072, 21: 1367, 22: 609, 23: 2064})])",MACs,6872.69632,top1_acc,-90.55464030752334 +"OrderedDict([(, {0: 512, 1: 448, 2: 512, 3: 704, 4: 576, 5: 512, 6: 704, 7: 448, 8: 448, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1716, 14: 1126, 15: 1740, 16: 2310, 17: 1023, 18: 1048, 19: 2760, 20: 2123, 21: 1367, 22: 3072, 23: 1194})])",MACs,7324.173824,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 512, 1: 320, 2: 384, 3: 576, 4: 640, 5: 768, 6: 704, 7: 768, 8: 512, 9: 768, 10: 768, 11: 640, 12: 1104, 13: 1716, 14: 2806, 15: 1740, 16: 2818, 17: 3072, 18: 2212, 19: 1061, 20: 2690, 21: 2568, 22: 609, 23: 2064})])",MACs,7944.86528,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 640, 1: 448, 2: 320, 3: 576, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 448, 10: 384, 11: 448, 12: 2810, 13: 1716, 14: 2806, 15: 2810, 16: 2818, 17: 1023, 18: 1642, 19: 1061, 20: 2690, 21: 1367, 22: 1751, 23: 1194})])",MACs,7438.665216,top1_acc,-90.93904448105437 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 640, 5: 768, 6: 448, 7: 768, 8: 576, 9: 448, 10: 512, 11: 448, 12: 1104, 13: 1716, 14: 2338, 15: 2281, 16: 2310, 17: 1023, 18: 1048, 19: 1670, 20: 2123, 21: 1367, 22: 1751, 23: 205})])",MACs,6422.595072,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 576, 4: 768, 5: 768, 6: 576, 7: 448, 8: 512, 9: 320, 10: 512, 11: 768, 12: 1708, 13: 1716, 14: 1776, 15: 3072, 16: 1714, 17: 2233, 18: 2773, 19: 2760, 20: 1548, 21: 1367, 22: 609, 23: 584})])",MACs,7215.580672,top1_acc,-90.71938495332235 +"OrderedDict([(, {0: 576, 1: 320, 2: 512, 3: 576, 4: 768, 5: 704, 6: 768, 7: 512, 8: 768, 9: 448, 10: 384, 11: 448, 12: 2272, 13: 1716, 14: 1126, 15: 2281, 16: 2310, 17: 1637, 18: 1642, 19: 2760, 20: 1548, 21: 1925, 22: 3072, 23: 584})])",MACs,7387.4816,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 640, 1: 448, 2: 320, 3: 768, 4: 576, 5: 768, 6: 576, 7: 768, 8: 448, 9: 768, 10: 384, 11: 448, 12: 1708, 13: 3072, 14: 2806, 15: 2281, 16: 2310, 17: 2233, 18: 1048, 19: 2205, 20: 2690, 21: 3072, 22: 3072, 23: 584})])",MACs,8269.334016,top1_acc,-91.03056928427604 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 448, 7: 768, 8: 576, 9: 768, 10: 768, 11: 512, 12: 1104, 13: 2787, 14: 2338, 15: 1102, 16: 1714, 17: 1637, 18: 3072, 19: 1061, 20: 984, 21: 2568, 22: 1132, 23: 205})])",MACs,6709.904896,top1_acc,-90.37159070108 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 768, 4: 576, 5: 704, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 2810, 13: 1716, 14: 1126, 15: 2281, 16: 1714, 17: 1023, 18: 2773, 19: 3072, 20: 2123, 21: 1925, 22: 2402, 23: 2064})])",MACs,7729.57952,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 768, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 768, 12: 1708, 13: 1716, 14: 2338, 15: 3072, 16: 1714, 17: 2794, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 3072, 23: 584})])",MACs,8076.985856,top1_acc,-91.41497345780706 +"OrderedDict([(, {0: 640, 1: 448, 2: 320, 3: 768, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 2281, 16: 2310, 17: 2794, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 1132, 23: 584})])",MACs,6836.389376,top1_acc,-90.9024345597657 +"OrderedDict([(, {0: 640, 1: 448, 2: 768, 3: 768, 4: 640, 5: 768, 6: 448, 7: 512, 8: 448, 9: 320, 10: 768, 11: 512, 12: 1104, 13: 3072, 14: 2806, 15: 2281, 16: 3072, 17: 1023, 18: 3072, 19: 2205, 20: 1548, 21: 3072, 22: 1751, 23: 1194})])",MACs,8150.64832,top1_acc,-90.77429983525536 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 448, 10: 768, 11: 448, 12: 2810, 13: 1716, 14: 2806, 15: 2810, 16: 2818, 17: 2233, 18: 1642, 19: 1061, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,7405.962752,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 640, 1: 320, 2: 384, 3: 576, 4: 640, 5: 768, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 1104, 13: 2787, 14: 1126, 15: 1740, 16: 2818, 17: 1023, 18: 2212, 19: 1061, 20: 3072, 21: 1367, 22: 1751, 23: 2064})])",MACs,7240.418816,top1_acc,-90.22515101592532 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 768, 8: 512, 9: 768, 10: 384, 11: 448, 12: 2272, 13: 2787, 14: 1776, 15: 1740, 16: 1067, 17: 2233, 18: 2212, 19: 1061, 20: 2690, 21: 1925, 22: 1132, 23: 205})])",MACs,7066.158592,top1_acc,-90.86582463847702 +"OrderedDict([(, {0: 512, 1: 768, 2: 384, 3: 576, 4: 640, 5: 768, 6: 704, 7: 448, 8: 576, 9: 768, 10: 384, 11: 640, 12: 1104, 13: 2272, 14: 3072, 15: 3072, 16: 3072, 17: 2233, 18: 2212, 19: 2760, 20: 3072, 21: 1367, 22: 1132, 23: 2064})])",MACs,8447.395328,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 576, 4: 768, 5: 768, 6: 704, 7: 768, 8: 576, 9: 320, 10: 512, 11: 512, 12: 2810, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 2794, 18: 2773, 19: 1670, 20: 3072, 21: 2568, 22: 2402, 23: 205})])",MACs,7874.283008,top1_acc,-91.21361889071939 +"OrderedDict([(, {0: 640, 1: 768, 2: 320, 3: 576, 4: 576, 5: 768, 6: 576, 7: 768, 8: 448, 9: 320, 10: 512, 11: 448, 12: 1708, 13: 3072, 14: 2338, 15: 3072, 16: 1714, 17: 2233, 18: 2773, 19: 2760, 20: 2690, 21: 1367, 22: 609, 23: 584})])",MACs,7762.6752,top1_acc,-90.9024345597657 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 576, 5: 512, 6: 704, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2272, 13: 1716, 14: 2338, 15: 2810, 16: 2818, 17: 3072, 18: 2212, 19: 3072, 20: 3072, 21: 3072, 22: 1751, 23: 2064})])",MACs,9277.801984,top1_acc,-91.46988833974007 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 640, 5: 768, 6: 448, 7: 768, 8: 576, 9: 448, 10: 512, 11: 640, 12: 1104, 13: 1716, 14: 2338, 15: 2281, 16: 2310, 17: 1023, 18: 1048, 19: 1670, 20: 2123, 21: 1367, 22: 1751, 23: 205})])",MACs,6667.961856,top1_acc,-90.426505583013 +"OrderedDict([(, {0: 512, 1: 320, 2: 512, 3: 576, 4: 576, 5: 512, 6: 768, 7: 512, 8: 768, 9: 448, 10: 768, 11: 512, 12: 1104, 13: 2787, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 2760, 20: 2123, 21: 1925, 22: 1132, 23: 584})])",MACs,6741.034496,top1_acc,-90.68277503203367 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 448, 10: 768, 11: 768, 12: 2810, 13: 1716, 14: 2806, 15: 3072, 16: 3072, 17: 2233, 18: 1642, 19: 1061, 20: 3072, 21: 772, 22: 3072, 23: 3072})])",MACs,8692.237824,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 768, 1: 320, 2: 512, 3: 768, 4: 576, 5: 512, 6: 704, 7: 512, 8: 512, 9: 768, 10: 768, 11: 640, 12: 3072, 13: 2787, 14: 2338, 15: 1740, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8670.152192,top1_acc,-91.4881933003844 +"OrderedDict([(, {0: 640, 1: 768, 2: 512, 3: 576, 4: 640, 5: 768, 6: 448, 7: 512, 8: 768, 9: 320, 10: 384, 11: 512, 12: 2810, 13: 1716, 14: 1776, 15: 1740, 16: 2818, 17: 2794, 18: 3072, 19: 1061, 20: 3072, 21: 1367, 22: 2402, 23: 584})])",MACs,7874.610688,top1_acc,-90.62786015010069 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 640, 5: 768, 6: 576, 7: 512, 8: 576, 9: 768, 10: 512, 11: 512, 12: 1104, 13: 2272, 14: 2338, 15: 3072, 16: 3072, 17: 3072, 18: 1642, 19: 2205, 20: 3072, 21: 1925, 22: 3072, 23: 2064})])",MACs,8547.14112,top1_acc,-91.19531393007505 +"OrderedDict([(, {0: 640, 1: 448, 2: 768, 3: 704, 4: 768, 5: 704, 6: 448, 7: 512, 8: 576, 9: 448, 10: 512, 11: 448, 12: 1104, 13: 1716, 14: 2806, 15: 2281, 16: 2310, 17: 1023, 18: 1048, 19: 1061, 20: 1548, 21: 1367, 22: 1751, 23: 584})])",MACs,6628.967936,top1_acc,-90.20684605528098 +"OrderedDict([(, {0: 640, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 512, 8: 448, 9: 448, 10: 768, 11: 448, 12: 1104, 13: 1066, 14: 2338, 15: 1740, 16: 2818, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1751, 23: 3072})])",MACs,6453.5936,top1_acc,-90.49972542559034 +"OrderedDict([(, {0: 512, 1: 448, 2: 768, 3: 768, 4: 576, 5: 704, 6: 576, 7: 768, 8: 768, 9: 320, 10: 512, 11: 576, 12: 3072, 13: 1716, 14: 1126, 15: 2810, 16: 2310, 17: 1023, 18: 2773, 19: 3072, 20: 3072, 21: 3072, 22: 1751, 23: 1194})])",MACs,8415.217152,top1_acc,-91.08548416620904 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 640, 12: 3072, 13: 2787, 14: 2338, 15: 1740, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8751.94112,top1_acc,-91.57971810360608 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 768, 4: 768, 5: 704, 6: 704, 7: 768, 8: 576, 9: 768, 10: 768, 11: 512, 12: 1104, 13: 2787, 14: 2806, 15: 1102, 16: 1714, 17: 2233, 18: 3072, 19: 1061, 20: 984, 21: 2568, 22: 1132, 23: 205})])",MACs,7328.040448,top1_acc,-90.60955518945634 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1714, 17: 2233, 18: 3072, 19: 2760, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,7576.815104,top1_acc,-91.08548416620904 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2272, 13: 2787, 14: 2338, 15: 3072, 16: 1714, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 1925, 22: 3072, 23: 584})])",MACs,9069.594112,top1_acc,-91.59802306425041 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 704, 4: 768, 5: 768, 6: 704, 7: 448, 8: 576, 9: 448, 10: 512, 11: 448, 12: 1104, 13: 1716, 14: 2806, 15: 2281, 16: 2310, 17: 1023, 18: 1048, 19: 2760, 20: 3072, 21: 1367, 22: 1751, 23: 584})])",MACs,7262.63552,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 2310, 17: 2233, 18: 2212, 19: 1670, 20: 3072, 21: 772, 22: 609, 23: 205})])",MACs,6763.57888,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 704, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 512, 12: 2272, 13: 2787, 14: 2806, 15: 2810, 16: 2818, 17: 1023, 18: 2773, 19: 2205, 20: 3072, 21: 772, 22: 1132, 23: 2064})])",MACs,8189.052416,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 512, 1: 448, 2: 384, 3: 576, 4: 768, 5: 768, 6: 576, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 1708, 13: 1716, 14: 2338, 15: 3072, 16: 1067, 17: 2233, 18: 1048, 19: 2205, 20: 3072, 21: 3072, 22: 3072, 23: 1194})])",MACs,8180.4672,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 704, 4: 640, 5: 768, 6: 768, 7: 512, 8: 768, 9: 448, 10: 768, 11: 768, 12: 1708, 13: 1716, 14: 2338, 15: 3072, 16: 1714, 17: 2794, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 3072, 23: 584})])",MACs,7852.066304,top1_acc,-91.30514369394106 +"OrderedDict([(, {0: 512, 1: 320, 2: 512, 3: 576, 4: 576, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 384, 11: 448, 12: 3072, 13: 2272, 14: 2338, 15: 1102, 16: 2310, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,7907.378688,top1_acc,-91.06717920556471 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 768, 8: 576, 9: 768, 10: 384, 11: 448, 12: 2272, 13: 2787, 14: 2338, 15: 2281, 16: 1714, 17: 1637, 18: 3072, 19: 1061, 20: 1548, 21: 2568, 22: 1132, 23: 205})])",MACs,7200.441856,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 512, 1: 448, 2: 384, 3: 704, 4: 576, 5: 512, 6: 448, 7: 512, 8: 448, 9: 768, 10: 384, 11: 448, 12: 1104, 13: 1066, 14: 2806, 15: 2810, 16: 2818, 17: 3072, 18: 2212, 19: 1061, 20: 2690, 21: 3072, 22: 609, 23: 584})])",MACs,7317.554688,top1_acc,-90.93904448105437 +"OrderedDict([(, {0: 640, 1: 448, 2: 512, 3: 576, 4: 640, 5: 512, 6: 768, 7: 448, 8: 576, 9: 768, 10: 384, 11: 640, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 2818, 17: 1637, 18: 1048, 19: 2760, 20: 1548, 21: 772, 22: 1132, 23: 2064})])",MACs,6765.282816,top1_acc,-90.55464030752334 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 768, 10: 512, 11: 576, 12: 2272, 13: 2787, 14: 2806, 15: 2810, 16: 1067, 17: 2794, 18: 2773, 19: 2205, 20: 984, 21: 2568, 22: 2402, 23: 2064})])",MACs,8712.422912,top1_acc,-91.21361889071939 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 768, 4: 640, 5: 704, 6: 704, 7: 768, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 3072, 15: 1740, 16: 3072, 17: 2233, 18: 2212, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,8174.765568,top1_acc,-91.36005857587406 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 768, 4: 640, 5: 768, 6: 448, 7: 768, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 2281, 16: 2310, 17: 2794, 18: 1642, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7199.0656,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 512, 1: 320, 2: 768, 3: 576, 4: 640, 5: 768, 6: 448, 7: 768, 8: 576, 9: 768, 10: 512, 11: 448, 12: 1104, 13: 1716, 14: 1776, 15: 2281, 16: 2310, 17: 1023, 18: 1048, 19: 1670, 20: 2123, 21: 1367, 22: 2402, 23: 205})])",MACs,6767.248896,top1_acc,-90.35328574043567 +"OrderedDict([(, {0: 768, 1: 320, 2: 512, 3: 576, 4: 576, 5: 768, 6: 704, 7: 512, 8: 768, 9: 448, 10: 768, 11: 768, 12: 2810, 13: 2787, 14: 2338, 15: 2810, 16: 1067, 17: 3072, 18: 3072, 19: 2760, 20: 2690, 21: 1367, 22: 1132, 23: 2064})])",MACs,8689.288704,top1_acc,-91.46988833974007 +"OrderedDict([(, {0: 512, 1: 320, 2: 384, 3: 576, 4: 576, 5: 768, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 1104, 13: 2272, 14: 1126, 15: 1102, 16: 2310, 17: 2233, 18: 2212, 19: 1061, 20: 3072, 21: 1367, 22: 609, 23: 2064})])",MACs,6845.433344,top1_acc,-90.68277503203367 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 448, 7: 512, 8: 576, 9: 448, 10: 768, 11: 448, 12: 2810, 13: 1716, 14: 2338, 15: 2810, 16: 2818, 17: 1637, 18: 1642, 19: 1061, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,6787.8272,top1_acc,-90.66447007138935 +"OrderedDict([(, {0: 640, 1: 320, 2: 512, 3: 576, 4: 640, 5: 704, 6: 704, 7: 512, 8: 576, 9: 768, 10: 512, 11: 640, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 2818, 17: 1637, 18: 1048, 19: 3072, 20: 1548, 21: 772, 22: 1132, 23: 2064})])",MACs,7146.702336,top1_acc,-90.55464030752334 +"OrderedDict([(, {0: 576, 1: 320, 2: 384, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 2281, 16: 1067, 17: 2233, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,6130.50112,top1_acc,-90.29837085850265 +"OrderedDict([(, {0: 640, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2310, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,7015.106048,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 512, 1: 768, 2: 768, 3: 768, 4: 576, 5: 704, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 2810, 13: 1716, 14: 1126, 15: 2281, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 3072, 21: 1925, 22: 2402, 23: 2064})])",MACs,8481.408512,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 768, 6: 448, 7: 768, 8: 576, 9: 320, 10: 512, 11: 512, 12: 2810, 13: 1716, 14: 2338, 15: 2281, 16: 1067, 17: 1023, 18: 2773, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,6499.206656,top1_acc,-90.48142046494601 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 768, 10: 384, 11: 512, 12: 2272, 13: 2787, 14: 2806, 15: 2810, 16: 1714, 17: 1023, 18: 2773, 19: 2205, 20: 2123, 21: 2568, 22: 2402, 23: 2064})])",MACs,8633.583104,top1_acc,-91.15870400878639 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 576, 5: 512, 6: 704, 7: 448, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 2787, 14: 2338, 15: 2810, 16: 2818, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 1751, 23: 2064})])",MACs,9678.423552,top1_acc,-91.61632802489474 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 768, 6: 576, 7: 768, 8: 576, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 1716, 14: 2338, 15: 2810, 16: 1067, 17: 1023, 18: 3072, 19: 2760, 20: 3072, 21: 1367, 22: 1751, 23: 205})])",MACs,7634.55232,top1_acc,-91.34175361522972 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 576, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 1708, 13: 2272, 14: 2338, 15: 3072, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 3072, 21: 2568, 22: 1132, 23: 1194})])",MACs,8636.92544,top1_acc,-91.28683873329673 +"OrderedDict([(, {0: 640, 1: 320, 2: 320, 3: 768, 4: 640, 5: 768, 6: 768, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2310, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 3072, 23: 584})])",MACs,7669.155328,top1_acc,-91.21361889071939 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 576, 4: 640, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2787, 14: 2338, 15: 1102, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8381.138432,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 768, 6: 448, 7: 768, 8: 576, 9: 768, 10: 512, 11: 512, 12: 2810, 13: 1716, 14: 2338, 15: 2281, 16: 3072, 17: 1023, 18: 2773, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,7709.066752,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 768, 1: 320, 2: 768, 3: 576, 4: 576, 5: 768, 6: 704, 7: 512, 8: 768, 9: 448, 10: 768, 11: 768, 12: 2810, 13: 2787, 14: 2338, 15: 2810, 16: 1067, 17: 3072, 18: 3072, 19: 2760, 20: 2690, 21: 1367, 22: 3072, 23: 2064})])",MACs,9179.760128,top1_acc,-91.45158337909574 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 3072, 21: 772, 22: 609, 23: 205})])",MACs,6546.458112,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 768, 5: 768, 6: 448, 7: 512, 8: 768, 9: 768, 10: 768, 11: 448, 12: 2272, 13: 2787, 14: 2338, 15: 3072, 16: 1714, 17: 2794, 18: 1642, 19: 1061, 20: 2690, 21: 1925, 22: 3072, 23: 3072})])",MACs,8727.168512,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 640, 5: 768, 6: 704, 7: 768, 8: 576, 9: 448, 10: 768, 11: 640, 12: 2810, 13: 1716, 14: 2338, 15: 2810, 16: 2310, 17: 3072, 18: 1048, 19: 2760, 20: 2123, 21: 1367, 22: 1751, 23: 2064})])",MACs,8308.131328,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 448, 10: 768, 11: 448, 12: 2810, 13: 1716, 14: 2806, 15: 2810, 16: 3072, 17: 2233, 18: 1642, 19: 2760, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,8029.07904,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 640, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1740, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,7362.119168,top1_acc,-91.28683873329673 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 1740, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 1925, 22: 1132, 23: 1194})])",MACs,7979.92704,top1_acc,-91.59802306425041 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 768, 6: 576, 7: 768, 8: 576, 9: 768, 10: 512, 11: 640, 12: 2810, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 2773, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6923.290112,top1_acc,-90.68277503203367 +"OrderedDict([(, {0: 576, 1: 320, 2: 768, 3: 576, 4: 640, 5: 704, 6: 768, 7: 512, 8: 512, 9: 448, 10: 512, 11: 640, 12: 1708, 13: 2272, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 584})])",MACs,7906.52672,top1_acc,-91.21361889071939 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 576, 4: 576, 5: 512, 6: 768, 7: 512, 8: 768, 9: 448, 10: 768, 11: 768, 12: 1708, 13: 2272, 14: 2338, 15: 3072, 16: 1714, 17: 2794, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 3072, 23: 584})])",MACs,7770.53952,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2810, 13: 2787, 14: 2338, 15: 3072, 16: 1714, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 1925, 22: 3072, 23: 584})])",MACs,9175.369216,top1_acc,-91.50649826102874 +"OrderedDict([(, {0: 640, 1: 448, 2: 768, 3: 768, 4: 768, 5: 704, 6: 448, 7: 512, 8: 576, 9: 448, 10: 512, 11: 576, 12: 1104, 13: 1716, 14: 2806, 15: 2281, 16: 2310, 17: 2794, 18: 1048, 19: 1670, 20: 1548, 21: 1925, 22: 1751, 23: 584})])",MACs,7288.391168,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 704, 4: 576, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 640, 12: 2272, 13: 1716, 14: 2338, 15: 1740, 16: 2818, 17: 2233, 18: 2212, 19: 2760, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8099.137024,top1_acc,-91.4881933003844 +"OrderedDict([(, {0: 768, 1: 320, 2: 512, 3: 576, 4: 576, 5: 768, 6: 704, 7: 512, 8: 768, 9: 320, 10: 768, 11: 576, 12: 2810, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 3072, 18: 2773, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 2064})])",MACs,7691.634176,top1_acc,-90.86582463847702 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 576, 5: 704, 6: 576, 7: 448, 8: 512, 9: 320, 10: 512, 11: 640, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 3072, 19: 2760, 20: 2123, 21: 1367, 22: 609, 23: 584})])",MACs,7110.592,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 768, 12: 1708, 13: 1716, 14: 2338, 15: 3072, 16: 1714, 17: 2794, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,7422.936576,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 576, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 640, 12: 3072, 13: 2272, 14: 2338, 15: 1740, 16: 2310, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8523.54816,top1_acc,-91.4881933003844 +"OrderedDict([(, {0: 512, 1: 768, 2: 320, 3: 768, 4: 640, 5: 704, 6: 704, 7: 768, 8: 512, 9: 320, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 3072, 15: 1740, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,6964.905472,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 512, 1: 768, 2: 512, 3: 768, 4: 576, 5: 704, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 2810, 13: 1716, 14: 1126, 15: 2281, 16: 1714, 17: 1023, 18: 2773, 19: 3072, 20: 2123, 21: 1925, 22: 609, 23: 2064})])",MACs,7268.009472,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 512, 1: 320, 2: 384, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 2281, 16: 2310, 17: 2233, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,6347.621888,top1_acc,-89.93227164561596 +"OrderedDict([(, {0: 640, 1: 320, 2: 512, 3: 768, 4: 768, 5: 512, 6: 768, 7: 512, 8: 448, 9: 448, 10: 768, 11: 768, 12: 1104, 13: 1066, 14: 2338, 15: 1740, 16: 2818, 17: 1023, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 1751, 23: 584})])",MACs,6796.0192,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 576, 4: 576, 5: 768, 6: 448, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1104, 13: 1716, 14: 2338, 15: 2281, 16: 1067, 17: 1023, 18: 3072, 19: 1670, 20: 3072, 21: 1367, 22: 1751, 23: 205})])",MACs,6899.041792,top1_acc,-90.40820062236867 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 768, 4: 640, 5: 704, 6: 704, 7: 768, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 3072, 15: 1740, 16: 2818, 17: 2233, 18: 2212, 19: 1061, 20: 3072, 21: 772, 22: 609, 23: 205})])",MACs,7551.64928,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 640, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 512, 8: 448, 9: 448, 10: 768, 11: 448, 12: 1104, 13: 1066, 14: 2338, 15: 1102, 16: 2310, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 3072})])",MACs,6106.58048,top1_acc,-90.11532125205932 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 576, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 448, 12: 2272, 13: 2787, 14: 2338, 15: 1740, 16: 3072, 17: 2233, 18: 2212, 19: 2760, 20: 2690, 21: 2568, 22: 1132, 23: 205})])",MACs,8194.88512,top1_acc,-91.39666849716274 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 2310, 17: 2233, 18: 2212, 19: 1670, 20: 3072, 21: 772, 22: 609, 23: 205})])",MACs,6518.212096,top1_acc,-90.591250228812 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 576, 4: 576, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 1132, 23: 1194})])",MACs,6236.734976,top1_acc,-90.33498077979132 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 704, 4: 640, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 1716, 14: 2338, 15: 1102, 16: 2310, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8234.272256,top1_acc,-91.46988833974007 +"OrderedDict([(, {0: 768, 1: 320, 2: 512, 3: 576, 4: 576, 5: 768, 6: 704, 7: 512, 8: 768, 9: 448, 10: 768, 11: 768, 12: 2272, 13: 2787, 14: 2338, 15: 2810, 16: 1067, 17: 3072, 18: 3072, 19: 2760, 20: 2690, 21: 1367, 22: 1132, 23: 2064})])",MACs,8583.5136,top1_acc,-91.4881933003844 +"OrderedDict([(, {0: 640, 1: 448, 2: 320, 3: 704, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 2806, 15: 2281, 16: 2310, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 1367, 22: 1132, 23: 584})])",MACs,6176.966144,top1_acc,-90.40820062236867 +"OrderedDict([(, {0: 640, 1: 320, 2: 384, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1716, 14: 2806, 15: 2281, 16: 2310, 17: 2794, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,6897.27232,top1_acc,-90.71938495332235 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,6248.334848,top1_acc,-90.591250228812 +"OrderedDict([(, {0: 640, 1: 448, 2: 320, 3: 768, 4: 640, 5: 704, 6: 448, 7: 512, 8: 576, 9: 448, 10: 384, 11: 576, 12: 2810, 13: 1716, 14: 2806, 15: 2810, 16: 2310, 17: 2794, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 1132, 23: 584})])",MACs,7312.1152,top1_acc,-91.01226432363171 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 512, 9: 448, 10: 768, 11: 448, 12: 1708, 13: 1066, 14: 2806, 15: 2281, 16: 2818, 17: 2233, 18: 1642, 19: 1061, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,6930.236928,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 576, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 2272, 13: 2787, 14: 2338, 15: 1740, 16: 1714, 17: 2233, 18: 2212, 19: 2760, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,8175.87968,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 576, 5: 768, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2787, 14: 2338, 15: 2810, 16: 1714, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 2064})])",MACs,10020.980224,top1_acc,-91.56141314296174 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 512, 9: 768, 10: 768, 11: 640, 12: 3072, 13: 2787, 14: 2338, 15: 2281, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8994.620928,top1_acc,-91.61632802489474 +"OrderedDict([(, {0: 640, 1: 320, 2: 384, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 768, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2310, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,7369.524736,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 768, 4: 640, 5: 768, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 768, 12: 1708, 13: 1716, 14: 2338, 15: 3072, 16: 1714, 17: 2233, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 3072, 23: 584})])",MACs,7850.82112,top1_acc,-90.88412959912137 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 704, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 1740, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 3072, 21: 1925, 22: 1132, 23: 1194})])",MACs,8248.29696,top1_acc,-91.36005857587406 +"OrderedDict([(, {0: 512, 1: 448, 2: 384, 3: 576, 4: 640, 5: 704, 6: 768, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 2310, 17: 2233, 18: 2212, 19: 1670, 20: 3072, 21: 772, 22: 609, 23: 205})])",MACs,6681.789952,top1_acc,-90.82921471718835 +"OrderedDict([(, {0: 640, 1: 448, 2: 320, 3: 768, 4: 768, 5: 768, 6: 576, 7: 768, 8: 576, 9: 448, 10: 512, 11: 576, 12: 2810, 13: 1066, 14: 2806, 15: 1740, 16: 2818, 17: 2794, 18: 2773, 19: 1670, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,8128.300544,top1_acc,-91.43327841845141 +"OrderedDict([(, {0: 576, 1: 320, 2: 384, 3: 576, 4: 768, 5: 768, 6: 768, 7: 768, 8: 576, 9: 448, 10: 384, 11: 448, 12: 2810, 13: 1716, 14: 2338, 15: 2810, 16: 2310, 17: 2233, 18: 1642, 19: 2760, 20: 984, 21: 1367, 22: 1751, 23: 584})])",MACs,7472.416256,top1_acc,-90.66447007138935 +"OrderedDict([(, {0: 640, 1: 320, 2: 320, 3: 576, 4: 768, 5: 704, 6: 448, 7: 512, 8: 512, 9: 448, 10: 768, 11: 448, 12: 1104, 13: 1066, 14: 2338, 15: 1740, 16: 2818, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 1751, 23: 3072})])",MACs,6909.0688,top1_acc,-90.48142046494601 +"OrderedDict([(, {0: 640, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 2310, 17: 2233, 18: 2212, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,7044.793856,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 576, 4: 576, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2272, 14: 2338, 15: 3072, 16: 2310, 17: 2794, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8650.36032,top1_acc,-91.28683873329673 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 512, 8: 448, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 2338, 15: 2810, 16: 2818, 17: 1023, 18: 3072, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 3072})])",MACs,7592.019456,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 640, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1740, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1751, 23: 584})])",MACs,6777.865728,top1_acc,-90.66447007138935 +"OrderedDict([(, {0: 640, 1: 320, 2: 512, 3: 768, 4: 640, 5: 512, 6: 704, 7: 512, 8: 576, 9: 768, 10: 384, 11: 640, 12: 1708, 13: 1716, 14: 2806, 15: 2281, 16: 2818, 17: 1637, 18: 1642, 19: 2760, 20: 1548, 21: 1925, 22: 1132, 23: 2064})])",MACs,7698.12224,top1_acc,-90.82921471718835 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 704, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 768, 10: 768, 11: 640, 12: 1708, 13: 2787, 14: 2338, 15: 1740, 16: 2310, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 1367, 22: 1132, 23: 584})])",MACs,7891.518976,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 768, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 3072, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 1925, 22: 1132, 23: 1194})])",MACs,8350.8608,top1_acc,-91.45158337909574 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 2310, 17: 2794, 18: 2212, 19: 1670, 20: 3072, 21: 772, 22: 609, 23: 205})])",MACs,6520.899072,top1_acc,-90.73768991396669 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 704, 4: 640, 5: 512, 6: 768, 7: 512, 8: 512, 9: 448, 10: 768, 11: 448, 12: 1708, 13: 1716, 14: 1776, 15: 3072, 16: 1067, 17: 2794, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 3072, 23: 205})])",MACs,6742.345216,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 768, 9: 448, 10: 768, 11: 768, 12: 2272, 13: 2787, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8727.03744,top1_acc,-91.67124290682776 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 448, 8: 576, 9: 768, 10: 384, 11: 448, 12: 2272, 13: 2787, 14: 2338, 15: 1740, 16: 1714, 17: 1637, 18: 3072, 19: 1061, 20: 1548, 21: 2568, 22: 1132, 23: 205})])",MACs,6957.762048,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1716, 14: 2338, 15: 3072, 16: 1714, 17: 2794, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,7068.517888,top1_acc,-91.08548416620904 +"OrderedDict([(, {0: 512, 1: 448, 2: 384, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 2281, 16: 2310, 17: 2794, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,6573.786624,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,6278.088192,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 576, 7: 448, 8: 512, 9: 768, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 1132, 23: 1194})])",MACs,6073.15712,top1_acc,-90.26176093721399 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 2338, 15: 2281, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5733.02528,top1_acc,-90.28006589785832 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 2281, 16: 1067, 17: 1023, 18: 3072, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6509.757952,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,5792.859648,top1_acc,-90.28006589785832 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6516.770304,top1_acc,-90.97565440234303 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 768, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,6925.321728,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 640, 1: 448, 2: 512, 3: 576, 4: 576, 5: 512, 6: 448, 7: 448, 8: 768, 9: 448, 10: 768, 11: 448, 12: 1104, 13: 2787, 14: 2338, 15: 1102, 16: 2310, 17: 3072, 18: 1642, 19: 3072, 20: 3072, 21: 3072, 22: 1751, 23: 2064})])",MACs,8192.984576,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 576, 4: 576, 5: 512, 6: 768, 7: 512, 8: 512, 9: 768, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 2806, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 2760, 20: 984, 21: 1925, 22: 1132, 23: 1194})])",MACs,6820.988416,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 640, 1: 448, 2: 320, 3: 576, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2310, 17: 2794, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5849.024,top1_acc,-89.91396668497163 +"OrderedDict([(, {0: 640, 1: 448, 2: 320, 3: 768, 4: 640, 5: 704, 6: 768, 7: 448, 8: 512, 9: 448, 10: 384, 11: 448, 12: 3072, 13: 1066, 14: 2806, 15: 2281, 16: 2818, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 2568, 22: 1132, 23: 1194})])",MACs,7037.388288,top1_acc,-90.51803038623467 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2272, 13: 2787, 14: 2338, 15: 1740, 16: 1714, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 1925, 22: 3072, 23: 584})])",MACs,8698.660352,top1_acc,-91.57971810360608 +"OrderedDict([(, {0: 512, 1: 448, 2: 384, 3: 768, 4: 640, 5: 768, 6: 768, 7: 512, 8: 512, 9: 768, 10: 768, 11: 768, 12: 2810, 13: 1716, 14: 2338, 15: 3072, 16: 1714, 17: 2233, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 3072, 23: 584})])",MACs,7965.246976,top1_acc,-90.88412959912137 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 704, 6: 768, 7: 448, 8: 768, 9: 768, 10: 384, 11: 768, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 1132, 23: 1194})])",MACs,7021.528576,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 576, 4: 640, 5: 768, 6: 576, 7: 768, 8: 576, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 1716, 14: 2338, 15: 2810, 16: 1067, 17: 2233, 18: 3072, 19: 2760, 20: 3072, 21: 1925, 22: 1132, 23: 205})])",MACs,7887.717888,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 3072, 16: 1714, 17: 2233, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,6638.142976,top1_acc,-90.66447007138935 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 1740, 16: 1067, 17: 1023, 18: 3072, 19: 3072, 20: 2123, 21: 1367, 22: 1751, 23: 1194})])",MACs,7726.761472,top1_acc,-91.50649826102874 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 768, 6: 704, 7: 448, 8: 512, 9: 768, 10: 512, 11: 640, 12: 3072, 13: 2787, 14: 2338, 15: 1740, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 1925, 22: 1132, 23: 1194})])",MACs,8253.998592,top1_acc,-91.57971810360608 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 768, 6: 576, 7: 768, 8: 576, 9: 320, 10: 512, 11: 512, 12: 2810, 13: 1716, 14: 2338, 15: 1102, 16: 1714, 17: 2794, 18: 2773, 19: 3072, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,7667.058176,top1_acc,-91.36005857587406 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5300.553216,top1_acc,-89.96888156690463 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 576, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 1132, 23: 1194})])",MACs,6209.472,top1_acc,-90.38989566172432 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 448, 12: 2272, 13: 2787, 14: 1776, 15: 1740, 16: 1067, 17: 2233, 18: 2212, 19: 2760, 20: 2690, 21: 1925, 22: 1132, 23: 1194})])",MACs,7649.166848,top1_acc,-91.26853377265239 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,6847.661568,top1_acc,-91.01226432363171 +"OrderedDict([(, {0: 640, 1: 448, 2: 384, 3: 576, 4: 640, 5: 704, 6: 768, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 2281, 16: 2310, 17: 2794, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,6648.759808,top1_acc,-90.51803038623467 +"OrderedDict([(, {0: 640, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 512, 8: 768, 9: 448, 10: 768, 11: 448, 12: 1104, 13: 1066, 14: 2338, 15: 2810, 16: 2818, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1751, 23: 3072})])",MACs,6936.59392,top1_acc,-90.536335346879 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 512, 9: 768, 10: 768, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 1194})])",MACs,9065.85856,top1_acc,-91.72615778876076 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 704, 6: 768, 7: 512, 8: 512, 9: 768, 10: 384, 11: 576, 12: 3072, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2794, 18: 3072, 19: 3072, 20: 3072, 21: 2568, 22: 1132, 23: 584})])",MACs,7967.4752,top1_acc,-91.28683873329673 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 704, 4: 640, 5: 512, 6: 768, 7: 512, 8: 512, 9: 768, 10: 768, 11: 640, 12: 2810, 13: 2272, 14: 2338, 15: 1740, 16: 2818, 17: 2233, 18: 2212, 19: 2760, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8368.752128,top1_acc,-91.59802306425041 +"OrderedDict([(, {0: 640, 1: 448, 2: 384, 3: 768, 4: 640, 5: 768, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1740, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 3072, 21: 1925, 22: 3072, 23: 584})])",MACs,8142.849536,top1_acc,-91.57971810360608 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 576, 5: 704, 6: 576, 7: 448, 8: 512, 9: 768, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 1132, 23: 1194})])",MACs,6311.446016,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 704, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 3072, 13: 1716, 14: 2338, 15: 2810, 16: 2818, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 772, 22: 1132, 23: 2064})])",MACs,8594.064896,top1_acc,-91.37836353651839 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 704, 6: 448, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7766.672896,top1_acc,-91.41497345780706 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 768, 12: 1708, 13: 1716, 14: 2338, 15: 3072, 16: 1714, 17: 2794, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,7038.240256,top1_acc,-90.86582463847702 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 768, 8: 576, 9: 320, 10: 384, 11: 512, 12: 2810, 13: 1716, 14: 1776, 15: 2281, 16: 1067, 17: 1023, 18: 2773, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,6225.135104,top1_acc,-90.57294526816767 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 576, 4: 768, 5: 512, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2272, 13: 2787, 14: 2338, 15: 1740, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 2690, 21: 1925, 22: 3072, 23: 205})])",MACs,7709.525504,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 2338, 15: 2281, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6225.331712,top1_acc,-90.62786015010069 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 576, 4: 576, 5: 512, 6: 576, 7: 448, 8: 512, 9: 768, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 1132, 23: 1194})])",MACs,6100.420096,top1_acc,-90.38989566172432 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 512, 9: 768, 10: 768, 11: 640, 12: 3072, 13: 2787, 14: 2338, 15: 2281, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 205})])",MACs,8718.386688,top1_acc,-91.39666849716274 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5678.761472,top1_acc,-90.46311550430165 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5330.765312,top1_acc,-90.09701629141497 +"OrderedDict([(, {0: 768, 1: 320, 2: 512, 3: 576, 4: 576, 5: 512, 6: 704, 7: 448, 8: 448, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 2787, 14: 2338, 15: 1740, 16: 2818, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 1751, 23: 2064})])",MACs,9195.423232,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 768, 9: 448, 10: 384, 11: 768, 12: 2272, 13: 2787, 14: 2338, 15: 1740, 16: 1067, 17: 1023, 18: 1642, 19: 3072, 20: 2123, 21: 1367, 22: 1751, 23: 584})])",MACs,7387.940352,top1_acc,-91.21361889071939 +"OrderedDict([(, {0: 768, 1: 320, 2: 512, 3: 576, 4: 576, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 640, 12: 1708, 13: 2272, 14: 2338, 15: 1102, 16: 2310, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 1194})])",MACs,6702.040576,top1_acc,-90.48142046494601 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 576, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2272, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,6008.473088,top1_acc,-90.62786015010069 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 768, 7: 512, 8: 768, 9: 448, 10: 768, 11: 768, 12: 1708, 13: 1716, 14: 2338, 15: 3072, 16: 1714, 17: 2794, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1751, 23: 584})])",MACs,7296.255488,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 2281, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5494.736384,top1_acc,-90.07871133077063 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 576, 5: 512, 6: 704, 7: 512, 8: 768, 9: 448, 10: 768, 11: 768, 12: 1708, 13: 2787, 14: 2338, 15: 3072, 16: 1714, 17: 2794, 18: 1642, 19: 3072, 20: 984, 21: 3072, 22: 1751, 23: 584})])",MACs,8152.876544,top1_acc,-91.45158337909574 +"OrderedDict([(, {0: 640, 1: 448, 2: 512, 3: 576, 4: 640, 5: 512, 6: 704, 7: 448, 8: 768, 9: 448, 10: 384, 11: 768, 12: 2272, 13: 2787, 14: 1126, 15: 1102, 16: 2310, 17: 2794, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1751, 23: 584})])",MACs,6809.388544,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 768, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 3072, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,6633.031168,top1_acc,-90.71938495332235 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 1740, 16: 2310, 17: 1023, 18: 3072, 19: 3072, 20: 2123, 21: 1367, 22: 1751, 23: 1194})])",MACs,7971.145216,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 576, 4: 576, 5: 512, 6: 768, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2272, 14: 2806, 15: 1102, 16: 2310, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8272.020992,top1_acc,-91.46988833974007 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 768, 11: 768, 12: 2810, 13: 2272, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 2212, 19: 2760, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,7212.303872,top1_acc,-91.15870400878639 +"OrderedDict([(, {0: 640, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,6800.410112,top1_acc,-91.01226432363171 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 576, 4: 576, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 2760, 20: 984, 21: 1925, 22: 1132, 23: 1194})])",MACs,6701.712896,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 576, 1: 320, 2: 384, 3: 704, 4: 640, 5: 768, 6: 768, 7: 512, 8: 768, 9: 448, 10: 384, 11: 640, 12: 1708, 13: 1716, 14: 1126, 15: 3072, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 3072, 23: 584})])",MACs,6917.850624,top1_acc,-90.57294526816767 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 768, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 640, 12: 1708, 13: 1716, 14: 2338, 15: 1740, 16: 1714, 17: 2794, 18: 3072, 19: 3072, 20: 984, 21: 772, 22: 3072, 23: 584})])",MACs,8041.727488,top1_acc,-90.97565440234303 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 2787, 14: 1776, 15: 3072, 16: 1067, 17: 2233, 18: 1642, 19: 3072, 20: 2123, 21: 1925, 22: 1132, 23: 1194})])",MACs,8015.185408,top1_acc,-91.34175361522972 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 704, 6: 576, 7: 768, 8: 576, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 1716, 14: 2338, 15: 3072, 16: 1067, 17: 1023, 18: 2773, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,7174.292992,top1_acc,-90.88412959912137 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 704, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 984, 21: 772, 22: 1751, 23: 1194})])",MACs,8231.126528,top1_acc,-91.19531393007505 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6567.495168,top1_acc,-90.64616511074502 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 448, 12: 2272, 13: 2787, 14: 1776, 15: 1740, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 205})])",MACs,6910.248448,top1_acc,-91.08548416620904 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 576, 5: 512, 6: 704, 7: 448, 8: 512, 9: 448, 10: 384, 11: 640, 12: 2272, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 3072, 21: 772, 22: 609, 23: 2064})])",MACs,7059.8016,top1_acc,-90.9024345597657 +"OrderedDict([(, {0: 640, 1: 448, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2310, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6842.942976,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 704, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 1740, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 1925, 22: 1132, 23: 1194})])",MACs,8007.190016,top1_acc,-91.43327841845141 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 2338, 15: 2281, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5733.02528,top1_acc,-90.46311550430165 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 768, 7: 512, 8: 512, 9: 768, 10: 768, 11: 640, 12: 2810, 13: 2272, 14: 2338, 15: 1740, 16: 2818, 17: 2233, 18: 2212, 19: 2760, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8396.015104,top1_acc,-91.52480322167308 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 512, 9: 768, 10: 768, 11: 640, 12: 3072, 13: 2787, 14: 2338, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,9150.137856,top1_acc,-91.61632802489474 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5596.972544,top1_acc,-90.46311550430165 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 576, 5: 512, 6: 704, 7: 512, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 2787, 14: 2338, 15: 2810, 16: 2818, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 1751, 23: 2064})])",MACs,9705.686528,top1_acc,-91.72615778876076 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 3072, 19: 3072, 20: 2123, 21: 1925, 22: 609, 23: 205})])",MACs,7165.838848,top1_acc,-91.26853377265239 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2272, 13: 1716, 14: 1126, 15: 1102, 16: 2818, 17: 2233, 18: 2212, 19: 1670, 20: 3072, 21: 772, 22: 609, 23: 584})])",MACs,6722.881024,top1_acc,-90.9024345597657 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 768, 11: 768, 12: 2810, 13: 2272, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 2760, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,6973.031936,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 768, 6: 576, 7: 768, 8: 576, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,6777.9968,top1_acc,-90.79260479589969 +"OrderedDict([(, {0: 576, 1: 320, 2: 512, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 2760, 20: 984, 21: 2568, 22: 1132, 23: 1194})])",MACs,6845.302272,top1_acc,-90.71938495332235 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1716, 14: 2806, 15: 2281, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6876.366336,top1_acc,-90.88412959912137 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 768, 6: 768, 7: 768, 8: 512, 9: 768, 10: 768, 11: 640, 12: 3072, 13: 2787, 14: 2338, 15: 2281, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 3072, 21: 2568, 22: 1132, 23: 1194})])",MACs,9400.550912,top1_acc,-91.59802306425041 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 768, 5: 768, 6: 448, 7: 512, 8: 512, 9: 320, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7270.303232,top1_acc,-91.15870400878639 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,6165.497344,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 2123, 21: 772, 22: 609, 23: 584})])",MACs,5503.452672,top1_acc,-90.20684605528098 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 576, 4: 640, 5: 512, 6: 704, 7: 448, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 2760, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6141.445632,top1_acc,-90.77429983525536 +"OrderedDict([(, {0: 576, 1: 320, 2: 512, 3: 768, 4: 576, 5: 512, 6: 576, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2787, 14: 2338, 15: 2810, 16: 2818, 17: 3072, 18: 2212, 19: 1670, 20: 2123, 21: 3072, 22: 1751, 23: 205})])",MACs,8627.09504,top1_acc,-91.19531393007505 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 704, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 2806, 15: 2281, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 1367, 22: 1132, 23: 584})])",MACs,5850.793472,top1_acc,-90.22515101592532 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5273.29024,top1_acc,-90.02379644883763 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 2281, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,5987.042816,top1_acc,-90.48142046494601 +"OrderedDict([(, {0: 640, 1: 320, 2: 320, 3: 704, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1740, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,7334.856192,top1_acc,-91.15870400878639 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 768, 9: 448, 10: 768, 11: 768, 12: 2272, 13: 2787, 14: 2338, 15: 2281, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8571.520512,top1_acc,-91.57971810360608 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5382.342144,top1_acc,-90.0054914881933 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 576, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,6820.398592,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 704, 7: 512, 8: 512, 9: 768, 10: 768, 11: 640, 12: 2810, 13: 2787, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 2212, 19: 1670, 20: 2690, 21: 772, 22: 1751, 23: 1194})])",MACs,8178.107904,top1_acc,-91.08548416620904 +"OrderedDict([(, {0: 640, 1: 320, 2: 320, 3: 768, 4: 576, 5: 768, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1740, 16: 1067, 17: 2794, 18: 1642, 19: 3072, 20: 2123, 21: 1925, 22: 3072, 23: 205})])",MACs,7428.4416,top1_acc,-91.26853377265239 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1714, 17: 2233, 18: 2212, 19: 1061, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6032.131584,top1_acc,-90.35328574043567 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 704, 6: 576, 7: 512, 8: 512, 9: 320, 10: 512, 11: 512, 12: 2810, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 2773, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6148.261376,top1_acc,-90.40820062236867 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 704, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 1708, 13: 2272, 14: 2338, 15: 1740, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,6854.215168,top1_acc,-91.06717920556471 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5373.429248,top1_acc,-90.13362621270365 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 512, 11: 512, 12: 2810, 13: 1716, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7261.128192,top1_acc,-91.34175361522972 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 2281, 16: 1067, 17: 1023, 18: 3072, 19: 2760, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,6974.539264,top1_acc,-90.82921471718835 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,7301.891584,top1_acc,-91.39666849716274 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 512, 8: 768, 9: 448, 10: 768, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,8159.692288,top1_acc,-91.39666849716274 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 2281, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6748.571136,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 2281, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5247.206912,top1_acc,-90.18854109463665 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 448, 9: 448, 10: 384, 11: 448, 12: 3072, 13: 1066, 14: 2338, 15: 2281, 16: 2818, 17: 2233, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 609, 23: 1194})])",MACs,7428.4416,top1_acc,-91.25022881200805 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 704, 4: 640, 5: 512, 6: 768, 7: 512, 8: 512, 9: 448, 10: 768, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 2760, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,7360.873984,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 768, 8: 576, 9: 320, 10: 384, 11: 576, 12: 2810, 13: 1716, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 1670, 20: 984, 21: 1925, 22: 1132, 23: 584})])",MACs,7593.854464,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 704, 7: 448, 8: 512, 9: 448, 10: 384, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 2760, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6059.656704,top1_acc,-90.66447007138935 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 2272, 13: 2787, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 205})])",MACs,8099.53024,top1_acc,-91.56141314296174 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 448, 12: 3072, 13: 1066, 14: 1126, 15: 1740, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 772, 22: 609, 23: 584})])",MACs,6955.27168,top1_acc,-91.14039904814206 +"OrderedDict([(, {0: 768, 1: 320, 2: 512, 3: 768, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 3072, 13: 1716, 14: 2338, 15: 2281, 16: 3072, 17: 1023, 18: 3072, 19: 3072, 20: 3072, 21: 2568, 22: 1132, 23: 1194})])",MACs,8155.629056,top1_acc,-91.14039904814206 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5455.611392,top1_acc,-89.98718652754897 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 512, 11: 576, 12: 2810, 13: 1716, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7288.391168,top1_acc,-91.30514369394106 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 704, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 1740, 16: 1067, 17: 1023, 18: 3072, 19: 2760, 20: 2123, 21: 1925, 22: 1132, 23: 1194})])",MACs,7707.95264,top1_acc,-91.30514369394106 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 768, 12: 3072, 13: 2787, 14: 2338, 15: 1102, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 3072, 22: 1751, 23: 205})])",MACs,7819.167232,top1_acc,-91.25022881200805 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 2281, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6333.9904,top1_acc,-90.40820062236867 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 768, 6: 768, 7: 512, 8: 512, 9: 768, 10: 768, 11: 640, 12: 1708, 13: 2272, 14: 2806, 15: 1740, 16: 2818, 17: 2794, 18: 1642, 19: 2760, 20: 2123, 21: 1925, 22: 3072, 23: 584})])",MACs,8459.191808,top1_acc,-91.46988833974007 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 768, 10: 384, 11: 768, 12: 2272, 13: 2787, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 1751, 23: 205})])",MACs,6845.433344,top1_acc,-90.71938495332235 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,5993.53088,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5548.082688,top1_acc,-90.29837085850265 +"OrderedDict([(, {0: 576, 1: 320, 2: 512, 3: 768, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 768, 10: 768, 11: 640, 12: 1708, 13: 2787, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 3072, 19: 1061, 20: 2123, 21: 2568, 22: 1132, 23: 584})])",MACs,7015.106048,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 768, 1: 320, 2: 512, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 2338, 15: 1740, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6686.639616,top1_acc,-90.97565440234303 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 768, 5: 704, 6: 448, 7: 512, 8: 512, 9: 448, 10: 768, 11: 512, 12: 1708, 13: 1066, 14: 1776, 15: 2281, 16: 1067, 17: 1023, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,6397.953536,top1_acc,-90.591250228812 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 2281, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6068.831744,top1_acc,-90.31667581914698 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 768, 9: 448, 10: 768, 11: 768, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7929.398784,top1_acc,-91.37836353651839 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 640, 12: 1708, 13: 2787, 14: 1776, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 2123, 21: 1367, 22: 1751, 23: 1194})])",MACs,6274.942464,top1_acc,-90.31667581914698 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 512, 9: 768, 10: 768, 11: 640, 12: 1708, 13: 2787, 14: 2338, 15: 2281, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,7114.262016,top1_acc,-90.86582463847702 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 576, 7: 448, 8: 448, 9: 768, 10: 384, 11: 640, 12: 2272, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5853.414912,top1_acc,-90.68277503203367 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 384, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5303.502336,top1_acc,-89.93227164561596 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 512, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 2281, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6781.732352,top1_acc,-90.68277503203367 +"OrderedDict([(, {0: 768, 1: 320, 2: 512, 3: 768, 4: 576, 5: 512, 6: 704, 7: 512, 8: 768, 9: 448, 10: 768, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 2810, 16: 1067, 17: 3072, 18: 3072, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 2064})])",MACs,7565.280768,top1_acc,-90.9024345597657 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,4926.342656,top1_acc,-89.9505766062603 +"OrderedDict([(, {0: 640, 1: 448, 2: 512, 3: 704, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 576, 12: 2810, 13: 1066, 14: 2338, 15: 1740, 16: 2818, 17: 2233, 18: 2212, 19: 3072, 20: 3072, 21: 2568, 22: 1132, 23: 1194})])",MACs,8052.409856,top1_acc,-91.39666849716274 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 1716, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7547.454976,top1_acc,-91.39666849716274 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6653.085184,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 576, 1: 768, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 2760, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,6049.367552,top1_acc,-90.591250228812 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 576, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,6214.05952,top1_acc,-90.60955518945634 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 512, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6223.431168,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,6684.083712,top1_acc,-91.15870400878639 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 704, 7: 448, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5392.631296,top1_acc,-90.0604063701263 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 448, 10: 512, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2233, 18: 2212, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,7365.920256,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 512, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6475.417088,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6434.981376,top1_acc,-91.03056928427604 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 704, 6: 704, 7: 512, 8: 512, 9: 768, 10: 384, 11: 512, 12: 3072, 13: 1066, 14: 1776, 15: 1740, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 1925, 22: 1132, 23: 1194})])",MACs,7614.301696,top1_acc,-91.36005857587406 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 704, 7: 512, 8: 512, 9: 320, 10: 512, 11: 512, 12: 3072, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 3072, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6784.026112,top1_acc,-90.62786015010069 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 704, 6: 704, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 3072, 13: 2787, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 3072, 21: 772, 22: 1132, 23: 2064})])",MACs,8539.866624,top1_acc,-91.28683873329673 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 2787, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,9054.979584,top1_acc,-91.74446274940509 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7657.620992,top1_acc,-91.67124290682776 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 768, 11: 768, 12: 2810, 13: 2272, 14: 2338, 15: 1102, 16: 2818, 17: 2233, 18: 2212, 19: 2760, 20: 2123, 21: 772, 22: 1751, 23: 205})])",MACs,7653.88544,top1_acc,-91.21361889071939 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 448, 9: 320, 10: 384, 11: 640, 12: 1708, 13: 2787, 14: 1126, 15: 2810, 16: 2818, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 1925, 22: 1751, 23: 584})])",MACs,6756.632064,top1_acc,-90.71938495332235 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 704, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 512, 11: 640, 12: 2810, 13: 2272, 14: 2338, 15: 1740, 16: 2818, 17: 2233, 18: 2212, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 584})])",MACs,8119.322112,top1_acc,-91.50649826102874 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 768, 8: 576, 9: 768, 10: 512, 11: 640, 12: 2810, 13: 2787, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2123, 21: 1925, 22: 1132, 23: 1194})])",MACs,8172.733952,top1_acc,-91.39666849716274 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 768, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,6223.56224,top1_acc,-90.88412959912137 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 512, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5376.706048,top1_acc,-90.28006589785832 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 704, 7: 448, 8: 512, 9: 768, 10: 768, 11: 640, 12: 3072, 13: 2787, 14: 2338, 15: 1740, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 1925, 22: 1132, 23: 1194})])",MACs,8253.998592,top1_acc,-91.46988833974007 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,7473.202688,top1_acc,-91.45158337909574 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2272, 14: 2338, 15: 1102, 16: 1067, 17: 2794, 18: 3072, 19: 3072, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,7699.76064,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 640, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 2212, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,6202.197504,top1_acc,-90.40820062236867 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 576, 7: 448, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5355.079168,top1_acc,-89.69430715723962 +"OrderedDict([(, {0: 576, 1: 320, 2: 512, 3: 576, 4: 640, 5: 512, 6: 704, 7: 448, 8: 512, 9: 448, 10: 384, 11: 640, 12: 1708, 13: 2787, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 2760, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6452.545024,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 768, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1740, 16: 1067, 17: 1023, 18: 3072, 19: 3072, 20: 2123, 21: 772, 22: 609, 23: 584})])",MACs,6394.676736,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 576, 5: 512, 6: 448, 7: 512, 8: 768, 9: 448, 10: 768, 11: 768, 12: 1708, 13: 1066, 14: 2338, 15: 2810, 16: 2818, 17: 3072, 18: 3072, 19: 3072, 20: 2690, 21: 3072, 22: 1751, 23: 205})])",MACs,8467.711488,top1_acc,-91.46988833974007 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 512, 9: 768, 10: 768, 11: 640, 12: 2272, 13: 2787, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 1194})])",MACs,8737.916416,top1_acc,-91.52480322167308 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5706.024448,top1_acc,-90.46311550430165 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 576, 5: 512, 6: 704, 7: 512, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 2787, 14: 2338, 15: 2810, 16: 1714, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 609, 23: 2064})])",MACs,9264.10496,top1_acc,-91.67124290682776 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 448, 12: 3072, 13: 1066, 14: 1776, 15: 1740, 16: 1067, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 1194})])",MACs,7309.49376,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 512, 12: 2810, 13: 1716, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 2773, 19: 2760, 20: 2123, 21: 772, 22: 1132, 23: 1194})])",MACs,7510.558208,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 768, 1: 320, 2: 512, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 576, 12: 3072, 13: 1716, 14: 1776, 15: 1740, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7122.847232,top1_acc,-90.68277503203367 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2272, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5907.940864,top1_acc,-90.73768991396669 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6220.154368,top1_acc,-90.55464030752334 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 2281, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8720.549376,top1_acc,-91.43327841845141 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5101.979136,top1_acc,-89.96888156690463 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5459.609088,top1_acc,-90.426505583013 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5088.675328,top1_acc,-89.8407468423943 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5447.550464,top1_acc,-90.31667581914698 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 2281, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,7147.357696,top1_acc,-91.14039904814206 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 512, 11: 576, 12: 2272, 13: 1716, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7042.041344,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 512, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 2281, 16: 1067, 17: 1023, 18: 3072, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6381.962752,top1_acc,-90.79260479589969 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5779.293696,top1_acc,-90.426505583013 +"OrderedDict([(, {0: 768, 1: 320, 2: 512, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 512, 9: 768, 10: 768, 11: 640, 12: 3072, 13: 2787, 14: 2338, 15: 2281, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 2568, 22: 1132, 23: 1194})])",MACs,8595.834368,top1_acc,-91.36005857587406 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 576, 9: 448, 10: 768, 11: 768, 12: 2810, 13: 2787, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8973.387264,top1_acc,-91.76276771004942 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7522.944512,top1_acc,-91.50649826102874 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 768, 4: 768, 5: 704, 6: 448, 7: 512, 8: 768, 9: 320, 10: 768, 11: 512, 12: 1708, 13: 1716, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1751, 23: 205})])",MACs,7885.161984,top1_acc,-91.19531393007505 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 448, 12: 2272, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,5882.906112,top1_acc,-90.49972542559034 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 448, 10: 768, 11: 768, 12: 1708, 13: 2787, 14: 2338, 15: 2281, 16: 1067, 17: 1023, 18: 2773, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,7250.773504,top1_acc,-90.97565440234303 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 768, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 3072, 19: 2760, 20: 3072, 21: 1925, 22: 1132, 23: 205})])",MACs,6878.856704,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 2281, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5552.932352,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 512, 8: 512, 9: 768, 10: 512, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 3072, 16: 1067, 17: 1023, 18: 3072, 19: 3072, 20: 2123, 21: 1367, 22: 1751, 23: 1194})])",MACs,8070.432256,top1_acc,-91.37836353651839 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 704, 7: 448, 8: 512, 9: 768, 10: 768, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 3072, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 1925, 22: 1751, 23: 1194})])",MACs,8527.087104,top1_acc,-91.61632802489474 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 704, 6: 704, 7: 448, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 2787, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,9136.768512,top1_acc,-91.54310818231741 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 512, 11: 576, 12: 2272, 13: 1716, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7865.763328,top1_acc,-91.67124290682776 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 512, 8: 768, 9: 320, 10: 384, 11: 512, 12: 2272, 13: 1066, 14: 1126, 15: 2281, 16: 1067, 17: 2794, 18: 1642, 19: 3072, 20: 984, 21: 1925, 22: 1751, 23: 584})])",MACs,6769.935872,top1_acc,-90.82921471718835 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5279.51616,top1_acc,-89.93227164561596 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 768, 10: 384, 11: 640, 12: 2272, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 584})])",MACs,5843.12576,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,6141.773312,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,6569.657856,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 704, 7: 448, 8: 512, 9: 448, 10: 384, 11: 768, 12: 3072, 13: 2787, 14: 1776, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7163.34848,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 576, 7: 448, 8: 448, 9: 768, 10: 384, 11: 640, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5518.591488,top1_acc,-90.37159070108 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 512, 12: 2810, 13: 1716, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 205})])",MACs,7709.656576,top1_acc,-91.37836353651839 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 640, 5: 704, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 2212, 19: 1670, 20: 3072, 21: 772, 22: 609, 23: 584})])",MACs,6055.921152,top1_acc,-90.40820062236867 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 1740, 16: 1067, 17: 1023, 18: 3072, 19: 3072, 20: 984, 21: 1367, 22: 1751, 23: 1194})])",MACs,7421.036032,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 704, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1740, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,6958.2208,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 576, 9: 448, 10: 384, 11: 768, 12: 2810, 13: 2787, 14: 2338, 15: 1740, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,8426.2272,top1_acc,-91.56141314296174 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,6602.294784,top1_acc,-91.14039904814206 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 320, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 1642, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,6649.480704,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 576, 4: 640, 5: 512, 6: 704, 7: 448, 8: 512, 9: 448, 10: 768, 11: 768, 12: 1708, 13: 2787, 14: 2338, 15: 3072, 16: 2818, 17: 1023, 18: 1642, 19: 1061, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,7204.30848,top1_acc,-90.48142046494601 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,5802.690048,top1_acc,-90.35328574043567 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5558.37184,top1_acc,-90.13362621270365 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 768, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5409.60512,top1_acc,-89.96888156690463 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 704, 7: 448, 8: 448, 9: 768, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,6722.815488,top1_acc,-90.79260479589969 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 512, 11: 512, 12: 2810, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5784.208896,top1_acc,-90.426505583013 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 3072, 19: 3072, 20: 2123, 21: 1925, 22: 609, 23: 584})])",MACs,7240.35328,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 768, 8: 576, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 2787, 14: 2338, 15: 3072, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,8360.756736,top1_acc,-91.63463298553907 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 704, 7: 448, 8: 512, 9: 768, 10: 512, 11: 640, 12: 3072, 13: 2787, 14: 1776, 15: 1740, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 1925, 22: 1132, 23: 1194})])",MACs,8034.452992,top1_acc,-91.52480322167308 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 768, 10: 384, 11: 448, 12: 3072, 13: 1066, 14: 1126, 15: 1740, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 584})])",MACs,6456.018432,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 640, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5870.585344,top1_acc,-90.79260479589969 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5198.775808,top1_acc,-90.0054914881933 +"OrderedDict([(, {0: 768, 1: 320, 2: 512, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 576, 9: 448, 10: 768, 11: 768, 12: 2810, 13: 1716, 14: 2338, 15: 2281, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 2123, 21: 772, 22: 1751, 23: 584})])",MACs,8160.085504,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6168.905216,top1_acc,-91.03056928427604 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5008.131584,top1_acc,-90.20684605528098 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5377.82016,top1_acc,-90.24345597656965 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 576, 5: 512, 6: 576, 7: 448, 8: 448, 9: 768, 10: 384, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 3072, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,6196.102656,top1_acc,-90.79260479589969 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5163.18976,top1_acc,-89.74922203917262 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 512, 11: 576, 12: 2810, 13: 1716, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7297.828352,top1_acc,-91.15870400878639 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 704, 7: 512, 8: 512, 9: 448, 10: 384, 11: 768, 12: 3072, 13: 2787, 14: 1126, 15: 3072, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 772, 22: 1751, 23: 205})])",MACs,7626.163712,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2272, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 2212, 19: 1670, 20: 2123, 21: 1925, 22: 1132, 23: 584})])",MACs,6422.267392,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 2760, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6920.930816,top1_acc,-91.06717920556471 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 576, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 2787, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8891.598336,top1_acc,-91.72615778876076 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 512, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 3072, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6535.84128,top1_acc,-90.97565440234303 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2810, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 2212, 19: 1061, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,5860.689408,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 2272, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 2212, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6382.15936,top1_acc,-90.66447007138935 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 512, 9: 768, 10: 384, 11: 640, 12: 3072, 13: 2787, 14: 1126, 15: 1740, 16: 1067, 17: 1023, 18: 3072, 19: 3072, 20: 2123, 21: 772, 22: 1751, 23: 1194})])",MACs,7400.195584,top1_acc,-91.25022881200805 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 512, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 2787, 14: 2806, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 772, 22: 1751, 23: 584})])",MACs,8976.270848,top1_acc,-91.4881933003844 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 3072, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6195.119616,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 768, 10: 384, 11: 640, 12: 2272, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5907.940864,top1_acc,-90.51803038623467 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5115.938304,top1_acc,-90.0054914881933 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 768, 8: 576, 9: 448, 10: 384, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 2281, 16: 1067, 17: 2233, 18: 2773, 19: 1061, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6176.769536,top1_acc,-90.35328574043567 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 2272, 13: 1716, 14: 2338, 15: 3072, 16: 1714, 17: 2233, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7620.199936,top1_acc,-91.21361889071939 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 512, 11: 576, 12: 2272, 13: 1716, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7188.25216,top1_acc,-90.9024345597657 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,4933.617152,top1_acc,-90.20684605528098 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 512, 11: 512, 12: 2272, 13: 1716, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7291.667968,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 768, 9: 448, 10: 768, 11: 448, 12: 1708, 13: 1066, 14: 1776, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 2123, 21: 1925, 22: 1132, 23: 584})])",MACs,7025.788416,top1_acc,-91.19531393007505 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 609, 23: 205})])",MACs,6055.331328,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 3072, 20: 984, 21: 1925, 22: 1132, 23: 205})])",MACs,6113.396224,top1_acc,-90.51803038623467 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 512, 11: 768, 12: 2810, 13: 1716, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7370.180096,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 1637, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6132.991488,top1_acc,-90.79260479589969 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5343.74144,top1_acc,-90.426505583013 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 1925, 22: 609, 23: 205})])",MACs,6095.43936,top1_acc,-91.01226432363171 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1776, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 1367, 22: 1132, 23: 205})])",MACs,6005.32736,top1_acc,-90.86582463847702 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 768, 11: 576, 12: 2272, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7658.014208,top1_acc,-91.65293794618341 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 1023, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,6922.110464,top1_acc,-91.14039904814206 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5542.446592,top1_acc,-90.33498077979132 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 448, 12: 2272, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1637, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,5765.727744,top1_acc,-90.40820062236867 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 512, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 2760, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5349.443072,top1_acc,-90.1702361339923 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 512, 11: 512, 12: 2810, 13: 1716, 14: 2338, 15: 2281, 16: 1714, 17: 1023, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,6617.892352,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 576, 9: 448, 10: 512, 11: 576, 12: 2810, 13: 2787, 14: 2338, 15: 1102, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8395.228672,top1_acc,-91.41497345780706 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5942.674944,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 384, 11: 576, 12: 2272, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 3072, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6489.114112,top1_acc,-90.73768991396669 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,5691.08224,top1_acc,-90.33498077979132 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 320, 10: 512, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 2760, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7545.554432,top1_acc,-91.15870400878639 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 2760, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5900.535296,top1_acc,-90.68277503203367 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6216.156672,top1_acc,-90.77429983525536 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 512, 9: 448, 10: 768, 11: 576, 12: 2272, 13: 2787, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,8105.42848,top1_acc,-91.50649826102874 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 512, 11: 512, 12: 2272, 13: 1716, 14: 2338, 15: 2281, 16: 2818, 17: 2233, 18: 2773, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7795.049984,top1_acc,-91.39666849716274 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 640, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5678.761472,top1_acc,-90.55464030752334 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 768, 7: 768, 8: 512, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 1716, 14: 2338, 15: 1102, 16: 1714, 17: 2794, 18: 2773, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,7527.72864,top1_acc,-91.46988833974007 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5246.027264,top1_acc,-90.15193117334798 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 576, 9: 768, 10: 768, 11: 640, 12: 2810, 13: 2787, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,9055.176192,top1_acc,-91.81768259198243 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7684.883968,top1_acc,-91.67124290682776 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 768, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,5806.75328,top1_acc,-90.49972542559034 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 704, 6: 704, 7: 512, 8: 576, 9: 448, 10: 768, 11: 768, 12: 2810, 13: 2787, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8743.290368,top1_acc,-91.41497345780706 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6749.685248,top1_acc,-91.25022881200805 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 2272, 14: 2338, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,6060.508672,top1_acc,-90.60955518945634 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 2281, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5416.617472,top1_acc,-90.38989566172432 +"OrderedDict([(, {0: 768, 1: 320, 2: 512, 3: 768, 4: 640, 5: 512, 6: 704, 7: 448, 8: 768, 9: 448, 10: 768, 11: 448, 12: 3072, 13: 2787, 14: 1126, 15: 1102, 16: 2818, 17: 1023, 18: 1642, 19: 1061, 20: 2690, 21: 772, 22: 1751, 23: 584})])",MACs,7043.08992,top1_acc,-90.77429983525536 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 512, 8: 576, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 2787, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8918.861312,top1_acc,-91.72615778876076 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 768, 11: 576, 12: 2272, 13: 1716, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2123, 21: 1925, 22: 1132, 23: 584})])",MACs,7756.1216,top1_acc,-91.30514369394106 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,4933.617152,top1_acc,-90.09701629141497 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8607.565312,top1_acc,-91.78107267069376 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 448, 10: 512, 11: 576, 12: 2810, 13: 1716, 14: 2338, 15: 3072, 16: 1714, 17: 2794, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7618.16832,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 448, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,6196.299264,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 2760, 20: 2123, 21: 1925, 22: 1132, 23: 1194})])",MACs,6552.487424,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5105.84576,top1_acc,-90.24345597656965 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 576, 7: 448, 8: 448, 9: 448, 10: 384, 11: 576, 12: 2272, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5689.837056,top1_acc,-90.64616511074502 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,6575.031808,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 768, 9: 320, 10: 512, 11: 576, 12: 2272, 13: 1716, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6694.897152,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,7531.98848,top1_acc,-91.26853377265239 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 1067, 17: 2794, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6452.020736,top1_acc,-90.9024345597657 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,5852.890624,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 2760, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6036.850176,top1_acc,-90.62786015010069 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 768, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 1067, 17: 2794, 18: 3072, 19: 3072, 20: 984, 21: 1925, 22: 1132, 23: 584})])",MACs,7020.021248,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7630.358016,top1_acc,-91.50649826102874 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7449.347584,top1_acc,-91.45158337909574 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 704, 6: 448, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 3072, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,8049.788416,top1_acc,-91.34175361522972 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 512, 11: 512, 12: 2810, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6440.093184,top1_acc,-90.77429983525536 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 2272, 14: 2806, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6352.209408,top1_acc,-90.9024345597657 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 512, 11: 576, 12: 2272, 13: 1716, 14: 2338, 15: 1102, 16: 1714, 17: 2794, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7261.390336,top1_acc,-91.19531393007505 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 768, 9: 448, 10: 768, 11: 768, 12: 1708, 13: 2787, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8307.082752,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 768, 10: 384, 11: 640, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,6061.426176,top1_acc,-90.88412959912137 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 584})])",MACs,5426.513408,top1_acc,-90.26176093721399 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 512, 11: 576, 12: 2272, 13: 1716, 14: 2338, 15: 3072, 16: 2818, 17: 2233, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7646.414336,top1_acc,-91.39666849716274 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5651.498496,top1_acc,-90.46311550430165 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 576, 9: 448, 10: 768, 11: 768, 12: 2810, 13: 2787, 14: 2338, 15: 2810, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,9055.766016,top1_acc,-91.7993776313381 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5398.267392,top1_acc,-90.46311550430165 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 2123, 21: 1925, 22: 1751, 23: 584})])",MACs,7065.69984,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 448, 9: 448, 10: 768, 11: 576, 12: 2272, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 1925, 22: 1132, 23: 584})])",MACs,6339.23328,top1_acc,-90.79260479589969 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6649.284096,top1_acc,-91.06717920556471 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 704, 6: 704, 7: 448, 8: 576, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1751, 23: 205})])",MACs,7778.010624,top1_acc,-91.41497345780706 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6703.810048,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,5733.156352,top1_acc,-90.426505583013 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 576, 7: 448, 8: 448, 9: 768, 10: 384, 11: 640, 12: 2272, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,6090.52416,top1_acc,-90.77429983525536 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7801.66912,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 2787, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,9000.453632,top1_acc,-91.72615778876076 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,4879.0912,top1_acc,-90.0054914881933 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 512, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1740, 16: 1067, 17: 1023, 18: 2773, 19: 2760, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,6214.977024,top1_acc,-90.68277503203367 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,5798.364672,top1_acc,-91.01226432363171 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 1067, 17: 1023, 18: 3072, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7348.618752,top1_acc,-91.06717920556471 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 576, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 609, 23: 205})])",MACs,7035.487744,top1_acc,-91.25022881200805 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 512, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5162.403328,top1_acc,-90.28006589785832 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 512, 11: 768, 12: 2810, 13: 2787, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,8497.268224,top1_acc,-91.37836353651839 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5107.877376,top1_acc,-90.11532125205932 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5053.351424,top1_acc,-90.28006589785832 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4868.736512,top1_acc,-90.09701629141497 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 640, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5561.97632,top1_acc,-90.31667581914698 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 576, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8498.710016,top1_acc,-91.70785282811642 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8743.880192,top1_acc,-91.89090243455976 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 448, 10: 384, 11: 576, 12: 2272, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5717.100032,top1_acc,-90.68277503203367 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 512, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 3072, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6598.886912,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 1067, 17: 2794, 18: 1642, 19: 3072, 20: 3072, 21: 1925, 22: 1132, 23: 205})])",MACs,6838.027776,top1_acc,-91.08548416620904 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4977.788416,top1_acc,-90.13362621270365 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,7849.5104,top1_acc,-91.56141314296174 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 640, 12: 2272, 13: 1716, 14: 1126, 15: 1102, 16: 1714, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6483.871232,top1_acc,-90.73768991396669 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 1067, 17: 2794, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5723.653632,top1_acc,-90.37159070108 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 576, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7313.032704,top1_acc,-91.45158337909574 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,4899.07968,top1_acc,-89.78583196046128 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,6194.202112,top1_acc,-90.68277503203367 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 640, 5: 704, 6: 576, 7: 512, 8: 512, 9: 320, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 205})])",MACs,6488.065536,top1_acc,-91.01226432363171 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 320, 10: 384, 11: 640, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5806.818816,top1_acc,-90.536335346879 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2794, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6243.091968,top1_acc,-90.97565440234303 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 448, 9: 320, 10: 512, 11: 576, 12: 2810, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 2773, 19: 3072, 20: 2123, 21: 772, 22: 609, 23: 584})])",MACs,6657.934848,top1_acc,-91.08548416620904 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 768, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 1023, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,6894.847488,top1_acc,-91.03056928427604 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 2281, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5607.458304,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7712.146944,top1_acc,-91.4881933003844 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 768, 9: 448, 10: 512, 11: 576, 12: 2272, 13: 1716, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6749.423104,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 576, 9: 320, 10: 512, 11: 576, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 3072, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,6488.196608,top1_acc,-90.77429983525536 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 1132, 23: 205})])",MACs,5654.644224,top1_acc,-90.33498077979132 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1714, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 584})])",MACs,5362.877952,top1_acc,-90.40820062236867 +"OrderedDict([(, {0: 576, 1: 320, 2: 384, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 1023, 18: 3072, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,6371.608064,top1_acc,-90.57294526816767 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 576, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 2787, 14: 2806, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8983.61088,top1_acc,-91.67124290682776 +"OrderedDict([(, {0: 576, 1: 320, 2: 384, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 768, 12: 2272, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,7176.259072,top1_acc,-90.79260479589969 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 576, 9: 768, 10: 768, 11: 640, 12: 1708, 13: 2787, 14: 2338, 15: 3072, 16: 2818, 17: 2233, 18: 1642, 19: 3072, 20: 2690, 21: 772, 22: 1751, 23: 584})])",MACs,8279.164416,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7639.729664,top1_acc,-91.45158337909574 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 768, 11: 576, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 3072, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6842.942976,top1_acc,-91.06717920556471 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 640, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5861.344768,top1_acc,-90.62786015010069 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,6545.540608,top1_acc,-91.19531393007505 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8524.5312,top1_acc,-91.89090243455976 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 2272, 13: 1066, 14: 2338, 15: 1102, 16: 1714, 17: 1023, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6165.628416,top1_acc,-90.51803038623467 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,8682.669568,top1_acc,-91.63463298553907 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 704, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 2787, 14: 2338, 15: 3072, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 205})])",MACs,7304.119808,top1_acc,-91.26853377265239 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 512, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,4960.880128,top1_acc,-90.15193117334798 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 512, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5107.877376,top1_acc,-90.09701629141497 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 768, 11: 576, 12: 2272, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7630.751232,top1_acc,-91.59802306425041 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 640, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5624.23552,top1_acc,-90.51803038623467 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 448, 9: 320, 10: 384, 11: 576, 12: 2810, 13: 1066, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 2773, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,6598.559232,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1061, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,5794.104832,top1_acc,-90.48142046494601 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 512, 11: 448, 12: 2272, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6547.899904,top1_acc,-91.03056928427604 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 1067, 17: 2794, 18: 1642, 19: 1061, 20: 984, 21: 1925, 22: 1751, 23: 584})])",MACs,7169.5744,top1_acc,-91.15870400878639 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7430.931968,top1_acc,-91.30514369394106 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 448, 10: 384, 11: 576, 12: 3072, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,7284.721152,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 320, 10: 384, 11: 640, 12: 2810, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 2773, 19: 1670, 20: 2123, 21: 1925, 22: 1132, 23: 205})])",MACs,6582.830592,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4751.95136,top1_acc,-89.82244188174995 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 2760, 20: 2690, 21: 1925, 22: 1132, 23: 205})])",MACs,7038.109184,top1_acc,-91.28683873329673 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 448, 9: 320, 10: 768, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 1067, 17: 2233, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 205})])",MACs,6937.708032,top1_acc,-90.88412959912137 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 448, 10: 512, 11: 768, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2794, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7668.696576,top1_acc,-91.46988833974007 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 320, 10: 512, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5408.359936,top1_acc,-89.96888156690463 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 205})])",MACs,5777.786368,top1_acc,-90.73768991396669 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 576, 9: 768, 10: 768, 11: 640, 12: 2810, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2794, 18: 2773, 19: 3072, 20: 2123, 21: 1925, 22: 1751, 23: 584})])",MACs,7846.495744,top1_acc,-91.56141314296174 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 512, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5135.140352,top1_acc,-90.28006589785832 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,7504.725504,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 576, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2794, 18: 2773, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7563.642368,top1_acc,-91.4881933003844 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 512, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7250.773504,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 768, 8: 576, 9: 448, 10: 512, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 3072, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,6953.108992,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 768, 11: 576, 12: 2272, 13: 1066, 14: 2338, 15: 3072, 16: 1714, 17: 2233, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7332.10368,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 2123, 21: 1925, 22: 609, 23: 205})])",MACs,5940.184576,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,7677.412864,top1_acc,-91.43327841845141 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 640, 12: 3072, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7953.05728,top1_acc,-91.41497345780706 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 205})])",MACs,5935.138304,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 704, 7: 448, 8: 576, 9: 320, 10: 384, 11: 448, 12: 2810, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,6229.067264,top1_acc,-90.28006589785832 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 609, 23: 205})])",MACs,6189.8112,top1_acc,-90.77429983525536 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 448, 10: 768, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7558.399488,top1_acc,-91.4881933003844 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,7012.746752,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6942.81984,top1_acc,-91.19531393007505 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 768, 9: 320, 10: 768, 11: 768, 12: 1104, 13: 2272, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 1670, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8127.579648,top1_acc,-91.08548416620904 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 704, 7: 448, 8: 576, 9: 320, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 2773, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 205})])",MACs,6171.198976,top1_acc,-90.97565440234303 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 512, 11: 576, 12: 2272, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,6669.469184,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1132, 23: 205})])",MACs,6010.24256,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 2760, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7514.490368,top1_acc,-91.41497345780706 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4912.580096,top1_acc,-90.11532125205932 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 2810, 13: 1066, 14: 1126, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 205})])",MACs,6294.603264,top1_acc,-90.88412959912137 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,7367.558656,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 320, 10: 384, 11: 640, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6412.174848,top1_acc,-90.82921471718835 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1751, 23: 205})])",MACs,6919.357952,top1_acc,-90.97565440234303 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 512, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8256.357888,top1_acc,-91.54310818231741 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4895.999488,top1_acc,-90.04210140948197 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 448, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,7278.36416,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 609, 23: 584})])",MACs,5224.46592,top1_acc,-90.22515101592532 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6640.633344,top1_acc,-91.39666849716274 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 448, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 1126, 15: 1102, 16: 1714, 17: 2233, 18: 1642, 19: 3072, 20: 984, 21: 1925, 22: 1751, 23: 584})])",MACs,7094.011392,top1_acc,-90.73768991396669 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 1067, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7149.782528,top1_acc,-91.08548416620904 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 448, 10: 384, 11: 448, 12: 3072, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5704.975872,top1_acc,-90.57294526816767 +"OrderedDict([(, {0: 576, 1: 320, 2: 384, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 448, 9: 448, 10: 384, 11: 448, 12: 2810, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 984, 21: 772, 22: 1751, 23: 584})])",MACs,7079.4624,top1_acc,-90.86582463847702 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 320, 10: 512, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1714, 17: 1023, 18: 3072, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6596.003328,top1_acc,-90.88412959912137 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 512, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4977.788416,top1_acc,-90.04210140948197 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 205})])",MACs,7208.502784,top1_acc,-91.34175361522972 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 1925, 22: 1132, 23: 205})])",MACs,6061.950464,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 576, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,8573.814272,top1_acc,-91.78107267069376 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5724.702208,top1_acc,-90.86582463847702 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 576, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,5825.627648,top1_acc,-90.9024345597657 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,6470.436352,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 609, 23: 205})])",MACs,5122.688512,top1_acc,-90.24345597656965 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 768, 8: 576, 9: 320, 10: 512, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,5523.441152,top1_acc,-90.20684605528098 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 768, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 1751, 23: 584})])",MACs,5639.833088,top1_acc,-90.18854109463665 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1751, 23: 584})])",MACs,7625.573888,top1_acc,-91.41497345780706 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 576, 4: 640, 5: 512, 6: 704, 7: 448, 8: 576, 9: 320, 10: 768, 11: 448, 12: 2810, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2794, 18: 2773, 19: 3072, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,6578.832896,top1_acc,-91.01226432363171 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 1925, 22: 1132, 23: 584})])",MACs,6272.779776,top1_acc,-91.06717920556471 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7774.406144,top1_acc,-91.46988833974007 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 768, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7657.620992,top1_acc,-91.50649826102874 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 576, 9: 448, 10: 768, 11: 512, 12: 1708, 13: 1066, 14: 2338, 15: 2281, 16: 1067, 17: 1023, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,6173.492736,top1_acc,-90.66447007138935 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 768, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1740, 16: 1067, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6422.922752,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 704, 7: 448, 8: 576, 9: 320, 10: 768, 11: 576, 12: 2810, 13: 1066, 14: 2338, 15: 3072, 16: 1067, 17: 2794, 18: 2773, 19: 3072, 20: 3072, 21: 1925, 22: 1751, 23: 205})])",MACs,7991.461376,top1_acc,-91.57971810360608 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 768, 11: 576, 12: 3072, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8183.809536,top1_acc,-91.52480322167308 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5171.512832,top1_acc,-89.98718652754897 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7558.399488,top1_acc,-91.34175361522972 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5161.158144,top1_acc,-90.09701629141497 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 512, 6: 704, 7: 448, 8: 576, 9: 448, 10: 512, 11: 576, 12: 2810, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,7987.332608,top1_acc,-91.61632802489474 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 768, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,8211.990016,top1_acc,-91.45158337909574 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 448, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 1023, 18: 1642, 19: 1670, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,6788.613632,top1_acc,-90.60955518945634 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,6392.31744,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 984, 21: 1925, 22: 609, 23: 205})])",MACs,5005.90336,top1_acc,-90.04210140948197 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 2272, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7658.014208,top1_acc,-91.70785282811642 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 320, 10: 384, 11: 448, 12: 2810, 13: 1066, 14: 1126, 15: 1102, 16: 1714, 17: 2233, 18: 2773, 19: 1061, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,6263.997952,top1_acc,-90.68277503203367 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 2810, 16: 2818, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,6069.945856,top1_acc,-90.40820062236867 +"OrderedDict([(, {0: 576, 1: 320, 2: 384, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 3072, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5685.642752,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 768, 11: 512, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7998.342656,top1_acc,-91.28683873329673 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1714, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 584})])",MACs,5070.45632,top1_acc,-90.28006589785832 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 576, 9: 448, 10: 768, 11: 512, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6749.685248,top1_acc,-91.30514369394106 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 3072, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 3072, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5295.769088,top1_acc,-90.37159070108 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5751.965184,top1_acc,-90.79260479589969 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7749.633536,top1_acc,-91.63463298553907 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 576, 9: 448, 10: 768, 11: 512, 12: 2810, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2773, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5954.602496,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 576, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 1066, 14: 1126, 15: 3072, 16: 1067, 17: 2233, 18: 1642, 19: 3072, 20: 984, 21: 1925, 22: 1751, 23: 584})])",MACs,7084.508672,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4950.52544,top1_acc,-89.96888156690463 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6613.370368,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7430.931968,top1_acc,-91.30514369394106 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 768, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 1023, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6355.748352,top1_acc,-90.68277503203367 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 704, 7: 448, 8: 448, 9: 448, 10: 384, 11: 448, 12: 3072, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 3072, 21: 772, 22: 609, 23: 205})])",MACs,7194.281472,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 512, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6114.379264,top1_acc,-90.62786015010069 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5412.357632,top1_acc,-90.591250228812 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 448, 9: 320, 10: 384, 11: 640, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,4963.829248,top1_acc,-89.73091707852828 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 704, 7: 448, 8: 768, 9: 320, 10: 768, 11: 576, 12: 2272, 13: 1716, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 1642, 19: 3072, 20: 2123, 21: 1925, 22: 1751, 23: 205})])",MACs,7343.179264,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 576, 1: 320, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 576, 9: 448, 10: 512, 11: 576, 12: 2810, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7850.427904,top1_acc,-91.25022881200805 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 576, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7872.841216,top1_acc,-91.61632802489474 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,6171.657728,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 1776, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 3072, 20: 984, 21: 1925, 22: 609, 23: 584})])",MACs,6870.07488,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 2272, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5982.651904,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,6139.0208,top1_acc,-90.86582463847702 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 2818, 17: 2233, 18: 1642, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7280.461312,top1_acc,-91.37836353651839 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,7287.473664,top1_acc,-91.34175361522972 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 3072, 21: 772, 22: 609, 23: 205})])",MACs,5295.834624,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 1067, 17: 2233, 18: 1642, 19: 3072, 20: 2123, 21: 1925, 22: 1132, 23: 584})])",MACs,7235.634688,top1_acc,-91.26853377265239 +"OrderedDict([(, {0: 576, 1: 320, 2: 384, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 2773, 19: 1670, 20: 3072, 21: 1925, 22: 1751, 23: 205})])",MACs,6510.806528,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 448, 9: 320, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1714, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 584})])",MACs,5744.559616,top1_acc,-90.33498077979132 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 576, 12: 2272, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5982.651904,top1_acc,-90.82921471718835 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5188.42112,top1_acc,-90.1702361339923 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5006.8864,top1_acc,-89.82244188174995 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 576, 12: 3072, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8754.300416,top1_acc,-91.67124290682776 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 320, 10: 512, 11: 576, 12: 1708, 13: 1716, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5479.794176,top1_acc,-90.22515101592532 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 512, 9: 448, 10: 768, 11: 576, 12: 2272, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,8358.987264,top1_acc,-91.68954786747209 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 512, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,6785.53344,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1714, 17: 1023, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 584})])",MACs,4953.671168,top1_acc,-89.93227164561596 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 1023, 18: 3072, 19: 1670, 20: 2690, 21: 772, 22: 1751, 23: 205})])",MACs,6550.455808,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5459.150336,top1_acc,-90.46311550430165 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6253.577728,top1_acc,-90.88412959912137 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 576, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1714, 17: 2794, 18: 2773, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,6578.112,top1_acc,-90.73768991396669 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,6789.727744,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 1132, 23: 205})])",MACs,5436.1472,top1_acc,-90.28006589785832 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2794, 18: 1048, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 205})])",MACs,6544.68864,top1_acc,-90.93904448105437 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 576, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,7861.372416,top1_acc,-91.36005857587406 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 576, 9: 448, 10: 384, 11: 512, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6368.003584,top1_acc,-91.19531393007505 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5486.413312,top1_acc,-90.426505583013 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5119.936,top1_acc,-90.28006589785832 +"OrderedDict([(, {0: 512, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 2760, 20: 3072, 21: 772, 22: 1132, 23: 205})])",MACs,6041.110016,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 512, 11: 512, 12: 1708, 13: 1066, 14: 1776, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6383.601152,top1_acc,-91.03056928427604 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 2272, 13: 1066, 14: 2338, 15: 1102, 16: 1714, 17: 1023, 18: 1048, 19: 3072, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5967.054336,top1_acc,-90.60955518945634 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 584})])",MACs,5682.955776,top1_acc,-90.48142046494601 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 704, 7: 448, 8: 576, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,6132.13952,top1_acc,-90.38989566172432 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 512, 12: 2272, 13: 1066, 14: 1776, 15: 3072, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,7489.979904,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5431.88736,top1_acc,-90.46311550430165 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 576, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,7337.67424,top1_acc,-91.06717920556471 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 448, 10: 384, 11: 576, 12: 3072, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 1925, 22: 1751, 23: 205})])",MACs,6751.651328,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 512, 11: 576, 12: 2272, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,6175.72096,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6613.370368,top1_acc,-91.34175361522972 +"OrderedDict([(, {0: 576, 1: 320, 2: 384, 3: 576, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 448, 10: 768, 11: 448, 12: 3072, 13: 2272, 14: 1126, 15: 3072, 16: 1067, 17: 2233, 18: 1642, 19: 3072, 20: 984, 21: 1925, 22: 609, 23: 584})])",MACs,7094.076928,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 512, 12: 2272, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7300.580864,top1_acc,-91.21361889071939 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5877.925376,top1_acc,-90.66447007138935 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1714, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5023.204864,top1_acc,-90.04210140948197 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,6416.500224,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 576, 1: 320, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 1066, 14: 2338, 15: 3072, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1751, 23: 584})])",MACs,7890.14272,top1_acc,-91.43327841845141 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5535.76192,top1_acc,-90.73768991396669 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5337.8432,top1_acc,-90.51803038623467 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 768, 8: 576, 9: 448, 10: 768, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1067, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 609, 23: 205})])",MACs,7063.012864,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,8404.076032,top1_acc,-91.52480322167308 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1067, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7376.66816,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8635.024896,top1_acc,-91.78107267069376 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4776.265216,top1_acc,-89.96888156690463 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4779.214336,top1_acc,-89.8407468423943 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 2272, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,6009.91488,top1_acc,-90.57294526816767 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 448, 9: 320, 10: 384, 11: 768, 12: 1708, 13: 1066, 14: 1776, 15: 1102, 16: 2818, 17: 2794, 18: 3072, 19: 1670, 20: 2690, 21: 772, 22: 1751, 23: 205})])",MACs,6993.544704,top1_acc,-91.01226432363171 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 448, 8: 576, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6725.436928,top1_acc,-91.08548416620904 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 3072, 21: 1925, 22: 1132, 23: 205})])",MACs,5570.82368,top1_acc,-90.07871133077063 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 584})])",MACs,4943.250944,top1_acc,-90.04210140948197 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,5927.405056,top1_acc,-90.82921471718835 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 512, 9: 448, 10: 768, 11: 512, 12: 2272, 13: 1066, 14: 2338, 15: 2281, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,8027.244032,top1_acc,-91.63463298553907 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 584})])",MACs,5871.896064,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7053.837824,top1_acc,-91.34175361522972 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 448, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1714, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,6293.751296,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 768, 11: 576, 12: 2272, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,7997.818368,top1_acc,-91.59802306425041 +"OrderedDict([(, {0: 576, 1: 320, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 768, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 1776, 15: 1102, 16: 1714, 17: 2233, 18: 1642, 19: 3072, 20: 984, 21: 1925, 22: 609, 23: 584})])",MACs,6806.439424,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 1066, 14: 1776, 15: 2281, 16: 2818, 17: 2233, 18: 1642, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7169.967616,top1_acc,-91.30514369394106 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1714, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5173.282304,top1_acc,-90.09701629141497 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 448, 10: 768, 11: 448, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6951.33952,top1_acc,-90.93904448105437 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 576, 4: 768, 5: 512, 6: 448, 7: 768, 8: 768, 9: 448, 10: 768, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 1067, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1751, 23: 205})])",MACs,7031.883264,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5375.919616,top1_acc,-90.31667581914698 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 984, 21: 1925, 22: 1132, 23: 584})])",MACs,6771.312128,top1_acc,-91.08548416620904 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1714, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5525.472768,top1_acc,-90.426505583013 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 2773, 19: 3072, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,6019.4176,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1066, 14: 1776, 15: 1102, 16: 2818, 17: 1023, 18: 3072, 19: 1670, 20: 984, 21: 1925, 22: 609, 23: 584})])",MACs,6463.948288,top1_acc,-90.73768991396669 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2233, 18: 1642, 19: 1061, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6143.804928,top1_acc,-90.591250228812 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 1714, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,6596.527616,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 2272, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5862.852096,top1_acc,-90.71938495332235 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5871.764992,top1_acc,-90.82921471718835 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 512, 12: 2810, 13: 1066, 14: 1126, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 1061, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,6331.172352,top1_acc,-90.77429983525536 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 768, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 205})])",MACs,5951.784448,top1_acc,-90.71938495332235 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5670.176256,top1_acc,-90.55464030752334 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 984, 21: 1925, 22: 609, 23: 205})])",MACs,5087.692288,top1_acc,-90.0604063701263 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,6728.058368,top1_acc,-91.39666849716274 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 2818, 17: 2233, 18: 1642, 19: 3072, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,7123.109376,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8498.710016,top1_acc,-91.65293794618341 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,6783.829504,top1_acc,-91.34175361522972 +"OrderedDict([(, {0: 512, 1: 448, 2: 384, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 384, 11: 512, 12: 1708, 13: 1716, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 3072, 20: 3072, 21: 772, 22: 1751, 23: 205})])",MACs,6862.86592,top1_acc,-91.08548416620904 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 640, 12: 3072, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7953.05728,top1_acc,-91.41497345780706 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 2272, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7860.520448,top1_acc,-91.65293794618341 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 576, 9: 448, 10: 768, 11: 576, 12: 2810, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7763.789312,top1_acc,-91.54310818231741 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5841.48736,top1_acc,-91.03056928427604 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 609, 23: 205})])",MACs,5951.456768,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 576, 9: 448, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5758.125568,top1_acc,-90.64616511074502 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 576, 9: 448, 10: 768, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,6950.35648,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5926.290944,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 448, 9: 448, 10: 768, 11: 576, 12: 2272, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7322.27328,top1_acc,-91.19531393007505 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5353.24416,top1_acc,-90.13362621270365 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 1925, 22: 1132, 23: 205})])",MACs,6252.791296,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 768, 11: 640, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7710.705152,top1_acc,-91.46988833974007 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 1925, 22: 609, 23: 205})])",MACs,5857.150464,top1_acc,-90.66447007138935 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 320, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 2760, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7941.064192,top1_acc,-91.57971810360608 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 3072, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5027.595776,top1_acc,-90.0604063701263 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7320.438272,top1_acc,-91.41497345780706 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 512, 11: 512, 12: 2272, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7179.994624,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1714, 17: 1023, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 609, 23: 584})])",MACs,5535.499776,top1_acc,-90.20684605528098 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5226.956288,top1_acc,-90.57294526816767 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 384, 11: 512, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 1067, 17: 2233, 18: 1642, 19: 3072, 20: 984, 21: 1925, 22: 609, 23: 584})])",MACs,7121.07776,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4861.003264,top1_acc,-89.8407468423943 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 3072, 17: 1637, 18: 1642, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6690.17856,top1_acc,-91.01226432363171 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 512, 9: 448, 10: 768, 11: 448, 12: 2272, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 984, 21: 772, 22: 609, 23: 584})])",MACs,7442.728448,top1_acc,-91.25022881200805 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 1023, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,8089.37216,top1_acc,-91.37836353651839 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2233, 18: 3072, 19: 1670, 20: 2690, 21: 772, 22: 1751, 23: 205})])",MACs,6939.21536,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,6334.711296,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1637, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5057.283584,top1_acc,-90.26176093721399 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1714, 17: 1023, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,5986.715136,top1_acc,-90.57294526816767 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 1751, 23: 205})])",MACs,5430.773248,top1_acc,-90.29837085850265 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5861.017088,top1_acc,-90.77429983525536 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,6847.79264,top1_acc,-91.03056928427604 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 2272, 13: 1066, 14: 1776, 15: 1740, 16: 1067, 17: 2233, 18: 1048, 19: 3072, 20: 2123, 21: 1925, 22: 1132, 23: 205})])",MACs,6482.953728,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 1067, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,7019.890176,top1_acc,-91.19531393007505 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5357.83168,top1_acc,-90.51803038623467 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,7334.72512,top1_acc,-91.36005857587406 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5391.779328,top1_acc,-90.426505583013 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8501.724672,top1_acc,-91.54310818231741 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 576, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1751, 23: 584})])",MACs,7516.521984,top1_acc,-91.45158337909574 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,7191.397888,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 609, 23: 205})])",MACs,6162.548224,top1_acc,-90.88412959912137 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 768, 11: 576, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8442.742272,top1_acc,-91.76276771004942 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,4882.04032,top1_acc,-89.69430715723962 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 1023, 18: 1642, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 205})])",MACs,6262.621696,top1_acc,-90.55464030752334 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 576, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 2818, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7811.302912,top1_acc,-91.57971810360608 +"OrderedDict([(, {0: 768, 1: 320, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 768, 12: 3072, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2794, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 1751, 23: 205})])",MACs,6573.065728,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 2810, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,7344.424448,top1_acc,-91.41497345780706 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1776, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 584})])",MACs,5716.575744,top1_acc,-90.29837085850265 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5107.877376,top1_acc,-90.24345597656965 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,6895.699456,top1_acc,-91.01226432363171 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,6169.888256,top1_acc,-90.88412959912137 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7691.699712,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 512, 9: 448, 10: 768, 11: 576, 12: 2272, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,8155.497984,top1_acc,-91.4881933003844 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 584})])",MACs,5664.802304,top1_acc,-90.591250228812 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,6812.796416,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 768, 11: 512, 12: 2272, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7739.803136,top1_acc,-91.76276771004942 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 448, 10: 768, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,7455.573504,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 768, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 1067, 17: 2794, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,6475.613696,top1_acc,-90.426505583013 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1714, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 609, 23: 584})])",MACs,6229.78816,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,7895.516672,top1_acc,-91.45158337909574 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 1023, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,6435.636736,top1_acc,-90.93904448105437 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7468.41856,top1_acc,-91.15870400878639 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2212, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7913.73568,top1_acc,-91.54310818231741 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 205})])",MACs,6406.276608,top1_acc,-90.88412959912137 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5071.635968,top1_acc,-90.15193117334798 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 448, 10: 768, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7612.92544,top1_acc,-91.36005857587406 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5642.91328,top1_acc,-90.66447007138935 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5770.118656,top1_acc,-90.35328574043567 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 576, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8553.03936,top1_acc,-91.67124290682776 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6304.105984,top1_acc,-90.93904448105437 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 768, 12: 2272, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7848.85504,top1_acc,-91.57971810360608 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 1023, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5674.37056,top1_acc,-90.29837085850265 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5135.140352,top1_acc,-90.09701629141497 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 576, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1067, 17: 2233, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,6772.164096,top1_acc,-91.01226432363171 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 3072, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7347.045888,top1_acc,-91.54310818231741 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 1925, 22: 1132, 23: 205})])",MACs,6252.791296,top1_acc,-90.99395936298737 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 3072, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 1751, 23: 584})])",MACs,5455.48032,top1_acc,-90.1702361339923 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,6803.817984,top1_acc,-91.15870400878639 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 640, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,6524.175872,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 320, 10: 512, 11: 448, 12: 2272, 13: 1066, 14: 1776, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5537.40032,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5053.351424,top1_acc,-90.24345597656965 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 576, 9: 448, 10: 384, 11: 448, 12: 2810, 13: 2272, 14: 2338, 15: 2281, 16: 1067, 17: 2233, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,6790.12096,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8507.033088,top1_acc,-91.7993776313381 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 640, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,6981.1584,top1_acc,-91.06717920556471 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 1023, 18: 1048, 19: 3072, 20: 984, 21: 772, 22: 1751, 23: 205})])",MACs,5814.486528,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5620.565504,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,7283.803648,top1_acc,-91.26853377265239 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1714, 17: 2233, 18: 2773, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 584})])",MACs,5767.824896,top1_acc,-90.64616511074502 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1751, 23: 584})])",MACs,7818.118656,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4950.52544,top1_acc,-90.02379644883763 +"OrderedDict([(, {0: 576, 1: 320, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 768, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 609, 23: 205})])",MACs,8040.351232,top1_acc,-91.41497345780706 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4950.52544,top1_acc,-89.96888156690463 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 768, 11: 448, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5936.973312,top1_acc,-90.536335346879 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 1925, 22: 609, 23: 205})])",MACs,5978.654208,top1_acc,-90.97565440234303 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 768, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7310.280192,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4632.217088,top1_acc,-89.73091707852828 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 448, 9: 320, 10: 512, 11: 512, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1714, 17: 2233, 18: 2773, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5749.868032,top1_acc,-90.15193117334798 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1776, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5649.204736,top1_acc,-90.62786015010069 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 609, 23: 205})])",MACs,7038.436864,top1_acc,-91.34175361522972 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 1067, 17: 2233, 18: 3072, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,7489.259008,top1_acc,-91.52480322167308 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5589.042688,top1_acc,-90.591250228812 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 609, 23: 205})])",MACs,5951.456768,top1_acc,-90.77429983525536 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,6722.487808,top1_acc,-90.93904448105437 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 1925, 22: 609, 23: 584})])",MACs,6514.2144,top1_acc,-90.93904448105437 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 384, 11: 768, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 2690, 21: 772, 22: 1751, 23: 584})])",MACs,8072.463872,top1_acc,-91.59802306425041 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 1023, 18: 1642, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 205})])",MACs,6153.831936,top1_acc,-90.71938495332235 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 3072, 21: 772, 22: 609, 23: 205})])",MACs,5377.623552,top1_acc,-90.35328574043567 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 384, 11: 512, 12: 2272, 13: 1066, 14: 1776, 15: 3072, 16: 1067, 17: 2794, 18: 1048, 19: 1670, 20: 2123, 21: 1925, 22: 609, 23: 584})])",MACs,6660.228608,top1_acc,-91.15870400878639 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,6126.765568,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 768, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 1061, 20: 984, 21: 1925, 22: 609, 23: 205})])",MACs,5447.681536,top1_acc,-90.24345597656965 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5824.644608,top1_acc,-90.73768991396669 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,6783.829504,top1_acc,-91.34175361522972 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5617.550848,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,6420.235776,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 2338, 15: 3072, 16: 1067, 17: 2794, 18: 3072, 19: 3072, 20: 2123, 21: 1925, 22: 609, 23: 584})])",MACs,7928.743424,top1_acc,-91.45158337909574 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8561.55904,top1_acc,-91.87259747391543 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 576, 9: 448, 10: 768, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7422.084608,top1_acc,-91.37836353651839 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 704, 7: 768, 8: 768, 9: 448, 10: 768, 11: 576, 12: 3072, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,8902.215168,top1_acc,-91.87259747391543 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 512, 11: 768, 12: 1708, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8322.549248,top1_acc,-91.76276771004942 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 576, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5467.93216,top1_acc,-90.51803038623467 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 3072, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7128.94208,top1_acc,-91.45158337909574 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 1714, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,8076.723712,top1_acc,-91.4881933003844 +"OrderedDict([(, {0: 576, 1: 320, 2: 384, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,6584.927744,top1_acc,-91.03056928427604 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 448, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,8109.164032,top1_acc,-91.50649826102874 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,4971.562496,top1_acc,-89.98718652754897 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 2818, 17: 2233, 18: 3072, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,6153.7664,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 448, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1776, 15: 1102, 16: 2818, 17: 2233, 18: 2212, 19: 1670, 20: 2690, 21: 772, 22: 1751, 23: 205})])",MACs,6686.90176,top1_acc,-91.01226432363171 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 1067, 17: 2233, 18: 3072, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,7434.733056,top1_acc,-91.45158337909574 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7101.08928,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 768, 11: 512, 12: 2272, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,7981.303296,top1_acc,-91.34175361522972 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 448, 9: 320, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2794, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6770.591232,top1_acc,-90.88412959912137 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4997.318144,top1_acc,-89.85905180303862 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 576, 9: 448, 10: 512, 11: 512, 12: 2810, 13: 1066, 14: 2338, 15: 2281, 16: 1067, 17: 2233, 18: 2773, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,6725.568,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 704, 7: 448, 8: 576, 9: 448, 10: 768, 11: 576, 12: 2272, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 2773, 19: 3072, 20: 2123, 21: 772, 22: 1751, 23: 584})])",MACs,7945.717248,top1_acc,-91.39666849716274 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 768, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 2212, 19: 1670, 20: 2123, 21: 772, 22: 1751, 23: 205})])",MACs,6341.658112,top1_acc,-91.06717920556471 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 1670, 20: 984, 21: 1925, 22: 609, 23: 205})])",MACs,5730.993664,top1_acc,-90.46311550430165 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 448, 7: 768, 8: 768, 9: 448, 10: 768, 11: 576, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8525.776384,top1_acc,-91.59802306425041 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 1067, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 205})])",MACs,7073.826304,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 609, 23: 584})])",MACs,6275.728896,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 512, 9: 320, 10: 512, 11: 448, 12: 2272, 13: 1066, 14: 1776, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5590.025728,top1_acc,-90.49972542559034 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5779.22816,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6094.12864,top1_acc,-90.9024345597657 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1751, 23: 584})])",MACs,7555.25376,top1_acc,-91.28683873329673 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 768, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,6344.869376,top1_acc,-91.06717920556471 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 448, 10: 384, 11: 448, 12: 2272, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 1023, 18: 1048, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 584})])",MACs,5216.404992,top1_acc,-89.85905180303862 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 609, 23: 205})])",MACs,5790.172672,top1_acc,-90.62786015010069 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5672.0768,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6675.629568,top1_acc,-91.14039904814206 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5773.460992,top1_acc,-90.71938495332235 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 512, 11: 768, 12: 1708, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2233, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,7870.088704,top1_acc,-91.43327841845141 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4659.480064,top1_acc,-89.78583196046128 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 448, 9: 448, 10: 768, 11: 576, 12: 3072, 13: 1066, 14: 1776, 15: 1102, 16: 2818, 17: 2794, 18: 3072, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7487.161856,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5838.21056,top1_acc,-90.591250228812 +"OrderedDict([(, {0: 768, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 576, 9: 448, 10: 512, 11: 768, 12: 2810, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8375.633408,top1_acc,-91.65293794618341 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 384, 11: 576, 12: 2272, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,7748.519424,top1_acc,-91.59802306425041 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 2272, 13: 1066, 14: 1776, 15: 1102, 16: 2818, 17: 2233, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,6210.586112,top1_acc,-90.73768991396669 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 512, 8: 768, 9: 448, 10: 768, 11: 576, 12: 3072, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8012.563968,top1_acc,-91.57971810360608 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 768, 11: 768, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8395.359744,top1_acc,-91.4881933003844 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 2272, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,6282.085888,top1_acc,-90.97565440234303 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 768, 11: 448, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1751, 23: 205})])",MACs,6310.987264,top1_acc,-90.86582463847702 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 584})])",MACs,6447.36768,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 768, 11: 512, 12: 2272, 13: 1066, 14: 1776, 15: 1102, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 609, 23: 584})])",MACs,6422.660608,top1_acc,-90.68277503203367 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 448, 9: 320, 10: 512, 11: 448, 12: 2272, 13: 1066, 14: 1776, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5557.3888,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,8818.984448,top1_acc,-91.61632802489474 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4830.791168,top1_acc,-90.07871133077063 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 3072, 19: 1670, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,7332.43136,top1_acc,-91.50649826102874 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5174.461952,top1_acc,-90.46311550430165 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2233, 18: 1642, 19: 3072, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,7751.86176,top1_acc,-91.57971810360608 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 609, 23: 584})])",MACs,5306.254848,top1_acc,-90.13362621270365 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 512, 11: 512, 12: 1708, 13: 1066, 14: 2338, 15: 2281, 16: 1714, 17: 2233, 18: 2773, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7259.948544,top1_acc,-91.06717920556471 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 768, 11: 512, 12: 1708, 13: 1066, 14: 1776, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,6719.34208,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 1067, 17: 2794, 18: 1048, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,6955.92704,top1_acc,-91.1220940874977 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 512, 11: 512, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7640.909312,top1_acc,-91.23192385136372 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 640, 12: 3072, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7796.557312,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5071.635968,top1_acc,-90.13362621270365 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 1023, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,7770.736128,top1_acc,-91.34175361522972 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 205})])",MACs,5945.230848,top1_acc,-90.97565440234303 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 205})])",MACs,6213.142016,top1_acc,-90.86582463847702 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 205})])",MACs,6593.381888,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 205})])",MACs,5723.260416,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 768, 11: 640, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7657.620992,top1_acc,-91.61632802489474 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4861.003264,top1_acc,-89.8407468423943 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 768, 9: 448, 10: 384, 11: 768, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 1067, 17: 2794, 18: 1642, 19: 3072, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,7116.883456,top1_acc,-91.39666849716274 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5888.083456,top1_acc,-90.79260479589969 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 1776, 15: 1102, 16: 2818, 17: 2233, 18: 3072, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,7500.727808,top1_acc,-91.28683873329673 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 768, 9: 448, 10: 384, 11: 512, 12: 3072, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2123, 21: 1925, 22: 609, 23: 584})])",MACs,7760.840192,top1_acc,-91.74446274940509 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 1776, 15: 2810, 16: 1067, 17: 2233, 18: 3072, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7540.573696,top1_acc,-91.46988833974007 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 512, 9: 320, 10: 768, 11: 448, 12: 1708, 13: 1066, 14: 1776, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 772, 22: 1751, 23: 205})])",MACs,6176.04864,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 320, 10: 512, 11: 448, 12: 2272, 13: 1066, 14: 1776, 15: 1740, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5560.01024,top1_acc,-90.46311550430165 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5889.787392,top1_acc,-90.77429983525536 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 448, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5005.051392,top1_acc,-90.09701629141497 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 768, 11: 576, 12: 3072, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 3072, 21: 1925, 22: 609, 23: 584})])",MACs,8045.004288,top1_acc,-91.43327841845141 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 768, 11: 768, 12: 3072, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8452.507136,top1_acc,-91.76276771004942 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4895.999488,top1_acc,-90.04210140948197 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 512, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 772, 22: 1751, 23: 584})])",MACs,8029.668864,top1_acc,-91.4881933003844 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 3072, 19: 1670, 20: 3072, 21: 1925, 22: 1132, 23: 584})])",MACs,6776.096256,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 609, 23: 205})])",MACs,5149.951488,top1_acc,-90.22515101592532 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,7246.054912,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5575.73888,top1_acc,-90.71938495332235 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 3072, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7047.153152,top1_acc,-91.36005857587406 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 3072, 19: 1061, 20: 984, 21: 772, 22: 1751, 23: 584})])",MACs,5648.877056,top1_acc,-90.26176093721399 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 1670, 20: 984, 21: 1925, 22: 1751, 23: 205})])",MACs,7757.170176,top1_acc,-91.14039904814206 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2233, 18: 3072, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,7009.0112,top1_acc,-91.28683873329673 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 512, 11: 448, 12: 2272, 13: 1066, 14: 1776, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 772, 22: 1132, 23: 584})])",MACs,6314.853888,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 512, 11: 768, 12: 1708, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,8377.0752,top1_acc,-91.72615778876076 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5331.813888,top1_acc,-90.60955518945634 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 3072, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7135.49568,top1_acc,-91.25022881200805 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 205})])",MACs,6697.7152,top1_acc,-91.30514369394106 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1061, 20: 3072, 21: 772, 22: 609, 23: 205})])",MACs,5280.630272,top1_acc,-90.44481054365733 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 448, 9: 448, 10: 512, 11: 512, 12: 2272, 13: 1066, 14: 1776, 15: 1102, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7107.118592,top1_acc,-91.19531393007505 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 205})])",MACs,5707.335168,top1_acc,-90.8475196778327 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 512, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5494.14656,top1_acc,-90.37159070108 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 1023, 18: 1642, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 205})])",MACs,6459.81952,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 320, 10: 512, 11: 448, 12: 2272, 13: 1066, 14: 1776, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 3072, 20: 2690, 21: 772, 22: 1132, 23: 584})])",MACs,6304.761344,top1_acc,-90.81090975654402 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 448, 8: 448, 9: 448, 10: 384, 11: 768, 12: 1708, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2233, 18: 1048, 19: 3072, 20: 2690, 21: 772, 22: 1751, 23: 205})])",MACs,7231.50592,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 609, 23: 584})])",MACs,5970.59328,top1_acc,-90.66447007138935 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,5585.110528,top1_acc,-90.49972542559034 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 768, 9: 448, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2233, 18: 3072, 19: 3072, 20: 984, 21: 1925, 22: 609, 23: 584})])",MACs,6649.349632,top1_acc,-90.9024345597657 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1061, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5453.51424,top1_acc,-90.66447007138935 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 1925, 22: 609, 23: 205})])",MACs,5854.26688,top1_acc,-90.66447007138935 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 512, 9: 320, 10: 384, 11: 768, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 1023, 18: 1642, 19: 1061, 20: 2690, 21: 772, 22: 1751, 23: 205})])",MACs,6503.990784,top1_acc,-90.92073952041004 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 1023, 18: 3072, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,6451.693056,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,5515.183616,top1_acc,-90.60955518945634 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 768, 11: 768, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 1642, 19: 3072, 20: 984, 21: 1925, 22: 1751, 23: 584})])",MACs,7322.404352,top1_acc,-90.79260479589969 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 512, 8: 448, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 205})])",MACs,5553.980928,top1_acc,-90.51803038623467 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 512, 12: 3072, 13: 1066, 14: 2338, 15: 3072, 16: 2818, 17: 2233, 18: 1642, 19: 3072, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,8129.34912,top1_acc,-91.57971810360608 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,5961.942528,top1_acc,-90.9573494416987 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,4950.52544,top1_acc,-90.15193117334798 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 320, 10: 384, 11: 576, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,7697.204736,top1_acc,-91.46988833974007 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2233, 18: 3072, 19: 1061, 20: 984, 21: 1925, 22: 1132, 23: 584})])",MACs,6207.17824,top1_acc,-90.49972542559034 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1776, 15: 1102, 16: 2818, 17: 2233, 18: 3072, 19: 1670, 20: 3072, 21: 1925, 22: 1751, 23: 584})])",MACs,7123.240448,top1_acc,-91.26853377265239 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,5963.187712,top1_acc,-91.21361889071939 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,4991.092224,top1_acc,-89.76752699981695 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 768, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 3072, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 584})])",MACs,6306.203136,top1_acc,-91.04887424492037 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 1023, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,5901.12512,top1_acc,-90.64616511074502 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 512, 11: 512, 12: 2272, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1751, 23: 584})])",MACs,7752.451584,top1_acc,-91.52480322167308 +"OrderedDict([(, {0: 576, 1: 448, 2: 384, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 768, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 2818, 17: 2233, 18: 3072, 19: 1670, 20: 2690, 21: 772, 22: 1751, 23: 584})])",MACs,7296.583168,top1_acc,-91.32344865458539 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2794, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5713.495552,top1_acc,-90.68277503203367 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 448, 10: 512, 11: 576, 12: 3072, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,7713.654272,top1_acc,-91.52480322167308 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 448, 10: 512, 11: 576, 12: 1708, 13: 1066, 14: 2806, 15: 1102, 16: 1067, 17: 2233, 18: 3072, 19: 1670, 20: 2123, 21: 772, 22: 1132, 23: 205})])",MACs,6344.738304,top1_acc,-91.17700896943072 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 576, 4: 768, 5: 512, 6: 448, 7: 512, 8: 448, 9: 320, 10: 384, 11: 768, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 3072, 19: 3072, 20: 984, 21: 1925, 22: 609, 23: 205})])",MACs,6006.63808,top1_acc,-90.79260479589969 +"OrderedDict([(, {0: 768, 1: 448, 2: 384, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 768, 11: 768, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,7670.9248,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 2272, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5601.560064,top1_acc,-90.62786015010069 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 1023, 18: 1642, 19: 1670, 20: 984, 21: 772, 22: 609, 23: 205})])",MACs,5294.786048,top1_acc,-90.29837085850265 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 448, 10: 768, 11: 448, 12: 1708, 13: 1066, 14: 1776, 15: 3072, 16: 1067, 17: 2794, 18: 1642, 19: 3072, 20: 984, 21: 772, 22: 1132, 23: 584})])",MACs,6566.708736,top1_acc,-90.97565440234303 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 1642, 19: 1670, 20: 2123, 21: 772, 22: 609, 23: 205})])",MACs,5786.961408,top1_acc,-90.75599487461102 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 768, 8: 448, 9: 320, 10: 384, 11: 576, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2233, 18: 1642, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 205})])",MACs,7205.225984,top1_acc,-91.19531393007505 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 984, 21: 772, 22: 1132, 23: 205})])",MACs,5491.459584,top1_acc,-90.49972542559034 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 512, 9: 448, 10: 768, 11: 768, 12: 1708, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2233, 18: 3072, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,8309.9008,top1_acc,-91.63463298553907 +"OrderedDict([(, {0: 768, 1: 448, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 448, 10: 512, 11: 768, 12: 3072, 13: 1066, 14: 1776, 15: 3072, 16: 2818, 17: 2794, 18: 1048, 19: 3072, 20: 2690, 21: 1925, 22: 1132, 23: 584})])",MACs,8087.930368,top1_acc,-91.57971810360608 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 1023, 18: 1642, 19: 1670, 20: 3072, 21: 1925, 22: 609, 23: 205})])",MACs,5587.731968,top1_acc,-90.57294526816767 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 768, 8: 512, 9: 320, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1776, 15: 1102, 16: 2818, 17: 2233, 18: 3072, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 584})])",MACs,6624.183808,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 2338, 15: 1102, 16: 2818, 17: 2233, 18: 2212, 19: 1670, 20: 2690, 21: 1925, 22: 609, 23: 584})])",MACs,6710.49472,top1_acc,-91.14039904814206 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 768, 9: 448, 10: 512, 11: 448, 12: 1708, 13: 1066, 14: 2806, 15: 3072, 16: 2818, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 1751, 23: 584})])",MACs,7067.862528,top1_acc,-91.15870400878639 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 640, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 384, 11: 576, 12: 3072, 13: 1066, 14: 2338, 15: 1102, 16: 1067, 17: 2233, 18: 3072, 19: 1670, 20: 2123, 21: 772, 22: 1751, 23: 205})])",MACs,6560.810496,top1_acc,-91.10378912685337 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 448, 10: 384, 11: 576, 12: 1708, 13: 1066, 14: 1126, 15: 1102, 16: 1067, 17: 2233, 18: 1048, 19: 1670, 20: 2690, 21: 772, 22: 609, 23: 205})])",MACs,5570.627072,top1_acc,-90.62786015010069 +"OrderedDict([(, {0: 576, 1: 448, 2: 320, 3: 576, 4: 640, 5: 512, 6: 448, 7: 448, 8: 448, 9: 320, 10: 384, 11: 448, 12: 1708, 13: 1066, 14: 1126, 15: 3072, 16: 1067, 17: 2233, 18: 1048, 19: 1061, 20: 984, 21: 1925, 22: 609, 23: 584})])",MACs,5613.159936,top1_acc,-90.71938495332235 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 576, 4: 768, 5: 512, 6: 576, 7: 448, 8: 512, 9: 320, 10: 512, 11: 576, 12: 2272, 13: 1066, 14: 1126, 15: 1102, 16: 2818, 17: 1023, 18: 1048, 19: 1670, 20: 2690, 21: 1925, 22: 1132, 23: 205})])",MACs,6117.39392,top1_acc,-90.70107999267802 +"OrderedDict([(, {0: 576, 1: 320, 2: 320, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 512, 9: 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apache-2.0 +tags: +- generated_from_trainer +datasets: +- glue +metrics: +- accuracy +- f1 +model-index: +- name: first_try + results: + - task: + name: Text Classification + type: text-classification + dataset: + name: GLUE QQP + type: glue + config: qqp + split: validation + args: qqp + metrics: + - name: Accuracy + type: accuracy + value: 0.9094978976007915 + - name: F1 + type: f1 + value: 0.8781916841439461 +--- + + + +# first_try + +This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE QQP dataset. +It achieves the following results on the evaluation set: +- Loss: 0.2975 +- Accuracy: 0.9095 +- F1: 0.8782 +- Combined Score: 0.8938 + +## Model description + +More information needed + +## Intended uses & limitations + +More information needed + +## Training and evaluation data + +More information needed + +## Training procedure + +### Training hyperparameters + +The following hyperparameters were used during training: +- learning_rate: 2e-05 +- train_batch_size: 32 +- eval_batch_size: 128 +- seed: 42 +- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 +- lr_scheduler_type: linear +- num_epochs: 6 +- mixed_precision_training: Native AMP + +### Training results + +| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score | | +|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| +| 0.3347 | 1.0 | 11371 | 0.2781 | 0.8986 | 0.8645 | 0.8816 | OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 256, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 1590, 20: 1320, 21: 762, 22: 348, 23: 115})]) | +| 0.3347 | 1.0 | 11371 | 0.2633 | 0.9022 | 0.8709 | 0.8865 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.1664 | 2.0 | 22742 | 0.2724 | 0.9048 | 0.8736 | 0.8892 | OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 256, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 1590, 20: 1320, 21: 762, 22: 348, 23: 115})]) | +| 0.1664 | 2.0 | 22742 | 0.2665 | 0.9106 | 0.8809 | 0.8958 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.092 | 3.0 | 34113 | 0.2872 | 0.9094 | 0.8786 | 0.8940 | OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 256, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 1590, 20: 1320, 21: 762, 22: 348, 23: 115})]) | +| 0.092 | 3.0 | 34113 | 0.2708 | 0.9141 | 0.8846 | 0.8994 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0693 | 4.0 | 45484 | 0.2966 | 0.9088 | 0.8771 | 0.8930 | OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 256, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 1590, 20: 1320, 21: 762, 22: 348, 23: 115})]) | +| 0.0693 | 4.0 | 45484 | 0.2779 | 0.9144 | 0.8846 | 0.8995 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | + + +### Framework versions + +- Transformers 4.29.1 +- Pytorch 1.12.1 +- Datasets 2.13.1 +- Tokenizers 0.13.3 diff --git a/eftnas-s1-bert-base-qqp/all_results.json b/eftnas-s1-bert-base-qqp/all_results.json new file mode 100644 index 0000000000000000000000000000000000000000..034bde00d7413117ea9dd135030b22b18f5cdb6b --- /dev/null +++ b/eftnas-s1-bert-base-qqp/all_results.json @@ -0,0 +1,16 @@ +{ + "epoch": 4.0, + "eval_accuracy": 0.9094978976007915, + "eval_combined_score": 0.8938447908723688, + "eval_f1": 0.8781916841439461, + "eval_loss": 0.29752635955810547, + "eval_runtime": 25.8057, + "eval_samples": 40430, + "eval_samples_per_second": 1566.709, + "eval_steps_per_second": 12.245, + "train_loss": 0.20403898293818326, + "train_runtime": 74603.6038, + "train_samples": 363846, + "train_samples_per_second": 19.508, + "train_steps_per_second": 0.61 +} \ No newline at end of file diff --git a/eftnas-s1-bert-base-qqp/cache_MACs.csv b/eftnas-s1-bert-base-qqp/cache_MACs.csv new file mode 100644 index 0000000000000000000000000000000000000000..8875c5f3af6921240490803e04083bc20d522945 --- /dev/null +++ b/eftnas-s1-bert-base-qqp/cache_MACs.csv @@ -0,0 +1,991 @@ +"(0, 0, 2, 0, 0, 1, 0, 2, 1, 1, 1, 0, 3, 3, 0, 3, 1, 2, 3, 2, 2, 2, 2, 2)",7351.174656 +"(3, 1, 0, 2, 2, 1, 2, 2, 1, 0, 1, 0, 3, 0, 1, 2, 2, 3, 3, 0, 0, 0, 1, 3)",7609.386496 +"(1, 0, 1, 0, 2, 0, 3, 2, 1, 1, 0, 1, 1, 2, 3, 1, 1, 0, 0, 1, 3, 0, 2, 0)",8618.968576 +"(0, 1, 1, 1, 0, 0, 2, 0, 2, 1, 0, 0, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 0, 3)",8511.424 +"(3, 1, 1, 3, 2, 0, 2, 1, 1, 2, 1, 1, 3, 0, 1, 3, 2, 1, 1, 3, 0, 1, 0, 1)",7527.859712 +"(3, 1, 1, 2, 0, 1, 1, 2, 1, 0, 0, 0, 1, 3, 1, 2, 3, 2, 3, 1, 0, 2, 1, 2)",7640.77824 +"(3, 1, 2, 2, 0, 1, 1, 1, 0, 2, 0, 1, 3, 3, 1, 3, 1, 2, 3, 3, 2, 0, 1, 0)",7687.046656 +"(3, 1, 2, 1, 2, 2, 3, 1, 1, 0, 1, 0, 3, 3, 3, 3, 2, 0, 0, 1, 1, 3, 0, 2)",6987.449856 +"(1, 0, 2, 0, 0, 1, 3, 1, 2, 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2)",6882.52672 +"(1, 0, 2, 3, 2, 0, 3, 1, 3, 2, 0, 0, 0, 0, 3, 3, 3, 3, 3, 1, 2, 3, 2, 2)",6457.656832 +"(0, 1, 0, 1, 2, 1, 3, 0, 1, 0, 1, 0, 2, 1, 3, 0, 2, 1, 0, 1, 1, 1, 0, 2)",8682.407424 +"(1, 1, 1, 3, 0, 0, 3, 0, 1, 0, 1, 1, 0, 3, 3, 1, 2, 0, 3, 1, 2, 2, 1, 2)",7517.439488 +"(3, 0, 0, 3, 2, 2, 3, 0, 2, 2, 2, 0, 3, 1, 3, 3, 2, 2, 0, 1, 2, 1, 1, 3)",7236.486656 +"(0, 0, 0, 1, 0, 0, 2, 0, 2, 0, 1, 0, 0, 1, 0, 1, 2, 0, 0, 2, 1, 1, 0, 2)",9437.578752 +"(1, 1, 0, 3, 0, 1, 3, 1, 1, 0, 1, 1, 3, 3, 3, 3, 2, 0, 1, 1, 1, 3, 1, 2)",7130.646016 +"(1, 0, 1, 3, 2, 2, 3, 0, 2, 0, 1, 0, 0, 3, 0, 0, 0, 0, 3, 2, 2, 0, 2, 2)",7650.805248 +"(0, 1, 0, 3, 0, 2, 0, 2, 2, 0, 1, 1, 1, 2, 0, 0, 0, 0, 1, 2, 3, 3, 1, 1)",7926.18752 +"(1, 0, 1, 3, 0, 1, 3, 1, 2, 1, 1, 1, 0, 3, 3, 3, 2, 2, 1, 1, 3, 3, 1, 1)",6922.307072 +"(1, 1, 2, 3, 2, 1, 3, 1, 3, 2, 1, 0, 0, 3, 3, 3, 3, 3, 3, 2, 2, 3, 2, 2)",5549.786624 +"(3, 1, 0, 1, 0, 0, 2, 0, 2, 0, 1, 1, 2, 1, 3, 1, 2, 1, 0, 2, 1, 1, 0, 2)",8528.922112 +"(3, 1, 1, 3, 0, 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2)",6971.786752 +"(2, 1, 2, 3, 2, 1, 3, 1, 2, 2, 2, 0, 3, 3, 3, 3, 2, 1, 3, 2, 2, 3, 3, 3)",5545.133568 +"(2, 0, 2, 3, 2, 2, 3, 1, 2, 2, 2, 1, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3)",4998.170112 +"(2, 0, 2, 1, 1, 1, 3, 1, 2, 0, 2, 0, 3, 0, 3, 3, 2, 1, 0, 2, 2, 1, 1, 1)",7517.701632 +"(0, 0, 1, 3, 2, 0, 0, 1, 1, 0, 2, 0, 0, 1, 3, 0, 0, 1, 3, 1, 2, 2, 1, 2)",8156.153344 +"(0, 0, 0, 3, 2, 2, 3, 1, 2, 0, 1, 1, 0, 1, 0, 3, 0, 0, 0, 2, 1, 3, 0, 2)",8099.464704 +"(0, 1, 2, 3, 0, 1, 3, 1, 3, 2, 2, 1, 0, 0, 3, 3, 0, 3, 1, 2, 1, 3, 2, 3)",6669.600256 +"(3, 1, 2, 3, 2, 0, 3, 1, 2, 0, 2, 1, 0, 1, 3, 3, 2, 2, 3, 2, 3, 3, 3, 3)",6056.77312 +"(1, 1, 2, 3, 0, 2, 3, 1, 1, 0, 1, 0, 3, 3, 3, 3, 2, 1, 1, 2, 3, 3, 1, 3)",6474.827264 +"(2, 0, 0, 1, 2, 2, 3, 0, 2, 2, 2, 0, 3, 3, 3, 3, 2, 3, 3, 2, 3, 3, 2, 3)",5775.230464 +"(2, 1, 2, 3, 2, 1, 0, 1, 2, 0, 2, 1, 3, 3, 3, 3, 2, 1, 3, 2, 3, 3, 2, 3)",5853.677056 +"(0, 0, 2, 3, 2, 1, 3, 0, 3, 2, 1, 0, 3, 3, 3, 1, 0, 1, 0, 2, 1, 3, 0, 3)",7401.375232 +"(3, 1, 2, 3, 0, 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"52 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"53 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"56 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"324 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"330 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"333 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"334 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"339 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"340 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"342 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"343 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"347 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"348 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "359 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"359 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "361 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"361 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "362 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"362 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "363 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"363 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"364 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"365 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "367 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"367 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"370 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"371 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "373 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"373 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"374 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"375 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "377 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"377 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"380 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"381 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "393 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"383 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"384 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "386 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"386 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "387 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"387 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "395 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"388 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"389 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "391 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"391 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "392 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"392 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"393 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "394 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"394 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"395 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "397 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"397 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "398 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"398 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "399 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"399 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "400 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"400 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "402 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"402 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "403 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"403 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "404 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"404 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"405 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"406 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "408 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"408 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"411 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"412 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "414 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"414 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"415 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"416 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "418 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"418 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"421 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"422 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "434 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"424 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"425 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "427 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"427 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "428 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"428 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "436 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"429 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"430 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "432 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"432 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "433 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"433 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"434 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "435 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"435 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"436 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "438 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"438 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "439 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"439 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "440 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"440 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "441 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"441 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "443 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"443 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "444 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"444 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "445 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"445 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"446 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"447 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "449 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"449 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"452 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"453 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "455 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"455 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"456 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"457 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "459 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"459 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" -> "461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "491 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"462 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"463 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "475 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"465 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"466 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "468 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"468 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "469 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"469 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "477 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"470 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"471 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "473 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"473 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "474 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"474 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "483 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"475 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "476 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"476 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "478 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"42 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "43 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"43 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"44 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "46 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"46 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"47 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "52 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"52 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "53 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"53 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "56 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"56 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "311 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0000000000000000000000000000000000000000..99897125ff19348e4636f68c926809734a95f715 --- /dev/null +++ b/eftnas-s1-bert-base-qqp/search_progression.csv @@ -0,0 +1,1000 @@ +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 768, 4: 768, 5: 512, 6: 768, 7: 256, 8: 384, 9: 512, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 3072, 15: 1791, 16: 3018, 17: 2500, 18: 1709, 19: 2403, 20: 2100, 21: 1524, 22: 756, 23: 197})])",MACs,7351.174656,top1_acc,-91.02646549591887 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 256, 5: 512, 6: 256, 7: 256, 8: 384, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 3072, 14: 3020, 15: 2549, 16: 2543, 17: 1751, 18: 1709, 19: 3072, 20: 3072, 21: 3072, 22: 1957, 23: 115})])",MACs,7609.386496,top1_acc,-90.99925797674993 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 768, 4: 256, 5: 768, 6: 192, 7: 256, 8: 384, 9: 512, 10: 768, 11: 512, 12: 3018, 13: 2488, 14: 1787, 15: 3007, 16: 3018, 17: 3072, 18: 3072, 19: 2980, 20: 1320, 21: 3072, 22: 756, 23: 3072})])",MACs,8618.968576,top1_acc,-91.13529557259461 +"OrderedDict([(, {0: 768, 1: 256, 2: 448, 3: 384, 4: 768, 5: 768, 6: 256, 7: 768, 8: 192, 9: 512, 10: 768, 11: 768, 12: 3018, 13: 3024, 14: 3020, 15: 2549, 16: 1772, 17: 2982, 18: 2452, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 115})])",MACs,8511.424,top1_acc,-91.15508285926293 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 192, 4: 256, 5: 768, 6: 256, 7: 384, 8: 384, 9: 192, 10: 320, 11: 512, 12: 1675, 13: 3072, 14: 3020, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 1590, 20: 3072, 21: 2721, 22: 3072, 23: 483})])",MACs,7527.859712,top1_acc,-91.01904526341825 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 256, 4: 768, 5: 512, 6: 448, 7: 256, 8: 384, 9: 768, 10: 768, 11: 768, 12: 3018, 13: 1666, 14: 3020, 15: 2549, 16: 1772, 17: 2500, 18: 1709, 19: 2980, 20: 3072, 21: 1524, 22: 1957, 23: 197})])",MACs,7640.77824,top1_acc,-91.1476626267623 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 256, 4: 768, 5: 512, 6: 448, 7: 384, 8: 768, 9: 192, 10: 768, 11: 512, 12: 1675, 13: 1666, 14: 3020, 15: 1791, 16: 3018, 17: 2500, 18: 1709, 19: 1590, 20: 2100, 21: 3072, 22: 1957, 23: 3072})])",MACs,7687.046656,top1_acc,-91.10561464259213 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 384, 4: 256, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 3072, 19: 2980, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,6987.449856,top1_acc,-91.04625278258719 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 768, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 2460, 13: 1666, 14: 3020, 15: 3072, 16: 1772, 17: 2500, 18: 2452, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,7078.741504,top1_acc,-90.99431115508287 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 3072, 21: 3072, 22: 3072, 23: 197})])",MACs,8432.059904,top1_acc,-91.17487014593124 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 384, 4: 256, 5: 768, 6: 192, 7: 768, 8: 384, 9: 192, 10: 768, 11: 768, 12: 1675, 13: 2488, 14: 3072, 15: 2549, 16: 2543, 17: 1751, 18: 2452, 19: 3072, 20: 2936, 21: 3072, 22: 756, 23: 115})])",MACs,7769.687552,top1_acc,-91.03883255008657 +"OrderedDict([(, {0: 384, 1: 256, 2: 448, 3: 384, 4: 256, 5: 512, 6: 768, 7: 256, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3018, 13: 3024, 14: 2530, 15: 2549, 16: 2543, 17: 2500, 18: 3072, 19: 2403, 20: 2100, 21: 2721, 22: 3072, 23: 115})])",MACs,8174.044672,top1_acc,-91.15260944842939 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 256, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3018, 13: 2488, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2403, 20: 2936, 21: 3072, 22: 1957, 23: 483})])",MACs,8694.728192,top1_acc,-91.25154588177095 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 768, 4: 768, 5: 512, 6: 256, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3018, 13: 2488, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 2452, 19: 1590, 20: 2100, 21: 2721, 22: 756, 23: 197})])",MACs,7108.167168,top1_acc,-91.07098689092258 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 256, 4: 768, 5: 512, 6: 256, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3024, 14: 1787, 15: 2549, 16: 2543, 17: 2982, 18: 2452, 19: 2403, 20: 2936, 21: 3072, 22: 3072, 23: 115})])",MACs,7906.395648,top1_acc,-91.17487014593124 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 512, 5: 512, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 3020, 15: 3007, 16: 2543, 17: 2500, 18: 3072, 19: 2403, 20: 1320, 21: 2721, 22: 3072, 23: 197})])",MACs,8157.660672,top1_acc,-91.10066782092505 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 448, 7: 768, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 1957, 23: 197})])",MACs,7150.24128,top1_acc,-91.08335394509028 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 256, 4: 768, 5: 768, 6: 448, 7: 768, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 1791, 16: 2543, 17: 2500, 18: 2452, 19: 3072, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,7801.34144,top1_acc,-91.04625278258719 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 2974, 19: 1590, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,8243.119616,top1_acc,-91.1847637892654 +"OrderedDict([(, {0: 448, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 192, 7: 256, 8: 64, 9: 512, 10: 192, 11: 512, 12: 3018, 13: 2488, 14: 2530, 15: 2549, 16: 3072, 17: 2500, 18: 1709, 19: 2980, 20: 3072, 21: 762, 22: 3072, 23: 3072})])",MACs,7832.929792,top1_acc,-91.0091516200841 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 192, 10: 768, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 3018, 17: 2982, 18: 2974, 19: 2980, 20: 3072, 21: 1524, 22: 756, 23: 115})])",MACs,7973.176832,top1_acc,-91.09324758842445 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 256, 5: 512, 6: 256, 7: 256, 8: 64, 9: 512, 10: 768, 11: 768, 12: 3018, 13: 3024, 14: 1787, 15: 3007, 16: 3072, 17: 3072, 18: 2974, 19: 1590, 20: 1320, 21: 2721, 22: 1957, 23: 197})])",MACs,7798.916608,top1_acc,-91.08335394509028 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 512, 5: 512, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 1772, 17: 3072, 18: 2974, 19: 1590, 20: 2936, 21: 1524, 22: 756, 23: 3072})])",MACs,7878.608384,top1_acc,-91.13776898342815 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 256, 4: 768, 5: 768, 6: 192, 7: 256, 8: 192, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 348, 23: 3072})])",MACs,8191.804928,top1_acc,-91.1155082859263 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 256, 4: 768, 5: 768, 6: 448, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 2460, 13: 3072, 14: 3072, 15: 3007, 16: 3072, 17: 3072, 18: 2452, 19: 1590, 20: 2936, 21: 762, 22: 1957, 23: 483})])",MACs,8300.922368,top1_acc,-91.15508285926293 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 192, 7: 256, 8: 192, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 2488, 14: 3020, 15: 1791, 16: 3072, 17: 2500, 18: 2974, 19: 2403, 20: 3072, 21: 1524, 22: 756, 23: 483})])",MACs,7591.036416,top1_acc,-91.09572099925798 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 256, 4: 768, 5: 256, 6: 448, 7: 768, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3018, 13: 3072, 14: 1787, 15: 3007, 16: 2543, 17: 3072, 18: 2974, 19: 2403, 20: 2100, 21: 3072, 22: 3072, 23: 197})])",MACs,8333.035008,top1_acc,-91.14518921592877 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 756, 23: 483})])",MACs,6441.79712,top1_acc,-91.08582735592383 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 256, 6: 256, 7: 384, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3024, 14: 2530, 15: 2549, 16: 3018, 17: 2982, 18: 1709, 19: 1590, 20: 2100, 21: 2721, 22: 3072, 23: 3072})])",MACs,8771.732992,top1_acc,-91.11798169675983 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 256, 4: 768, 5: 256, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 768, 12: 3072, 13: 2488, 14: 3020, 15: 3072, 16: 1772, 17: 2500, 18: 2974, 19: 2980, 20: 3072, 21: 762, 22: 756, 23: 115})])",MACs,7626.163712,top1_acc,-91.10561464259213 +"OrderedDict([(, {0: 448, 1: 256, 2: 768, 3: 256, 4: 768, 5: 512, 6: 448, 7: 768, 8: 64, 9: 192, 10: 768, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 3007, 16: 2543, 17: 3072, 18: 1709, 19: 1590, 20: 2100, 21: 3072, 22: 3072, 23: 197})])",MACs,7849.5104,top1_acc,-91.1723967350977 +"OrderedDict([(, {0: 768, 1: 256, 2: 448, 3: 192, 4: 768, 5: 512, 6: 448, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 2488, 14: 1787, 15: 3007, 16: 2543, 17: 2500, 18: 2974, 19: 2980, 20: 1320, 21: 3072, 22: 3072, 23: 483})])",MACs,8078.165504,top1_acc,-91.15013603759584 +"OrderedDict([(, {0: 320, 1: 768, 2: 448, 3: 768, 4: 512, 5: 512, 6: 192, 7: 768, 8: 384, 9: 768, 10: 768, 11: 512, 12: 1675, 13: 3024, 14: 3020, 15: 1791, 16: 3018, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 1524, 22: 756, 23: 115})])",MACs,7209.420288,top1_acc,-90.94484293841208 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 384, 4: 256, 5: 256, 6: 192, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 2460, 13: 3072, 14: 3020, 15: 1791, 16: 3018, 17: 3072, 18: 2452, 19: 2403, 20: 3072, 21: 1524, 22: 1957, 23: 3072})])",MACs,8613.791232,top1_acc,-91.16744991343062 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 768, 5: 768, 6: 192, 7: 768, 8: 192, 9: 192, 10: 320, 11: 768, 12: 3018, 13: 3072, 14: 3072, 15: 3072, 16: 2543, 17: 3072, 18: 3072, 19: 2980, 20: 2936, 21: 3072, 22: 3072, 23: 483})])",MACs,9169.864192,top1_acc,-91.20455107593372 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 768, 5: 768, 6: 448, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 1772, 17: 2982, 18: 2452, 19: 2403, 20: 2100, 21: 1524, 22: 348, 23: 197})])",MACs,7638.615552,top1_acc,-91.16744991343062 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 256, 4: 512, 5: 512, 6: 448, 7: 384, 8: 384, 9: 192, 10: 320, 11: 768, 12: 2460, 13: 3072, 14: 1787, 15: 2549, 16: 3018, 17: 3072, 18: 2974, 19: 3072, 20: 2100, 21: 762, 22: 756, 23: 483})])",MACs,7150.503424,top1_acc,-91.07593371258966 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 384, 4: 768, 5: 768, 6: 448, 7: 768, 8: 384, 9: 192, 10: 768, 11: 512, 12: 1675, 13: 3072, 14: 2530, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2980, 20: 1320, 21: 3072, 22: 348, 23: 197})])",MACs,8179.942912,top1_acc,-91.16002968093 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 256, 4: 256, 5: 256, 6: 192, 7: 256, 8: 192, 9: 768, 10: 320, 11: 512, 12: 1675, 13: 2488, 14: 3072, 15: 3007, 16: 3018, 17: 3072, 18: 2974, 19: 2980, 20: 3072, 21: 3072, 22: 3072, 23: 197})])",MACs,7950.43584,top1_acc,-91.05367301508781 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 384, 4: 512, 5: 256, 6: 192, 7: 256, 8: 768, 9: 512, 10: 320, 11: 512, 12: 1675, 13: 3072, 14: 3072, 15: 2549, 16: 1772, 17: 2500, 18: 2974, 19: 1590, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,7723.943424,top1_acc,-91.01657185258472 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 384, 4: 256, 5: 512, 6: 192, 7: 768, 8: 384, 9: 768, 10: 768, 11: 768, 12: 2460, 13: 3072, 14: 3020, 15: 1791, 16: 3018, 17: 3072, 18: 2452, 19: 2403, 20: 3072, 21: 1524, 22: 1957, 23: 3072})])",MACs,8968.20992,top1_acc,-91.16497650259709 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 512, 5: 768, 6: 256, 7: 768, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3020, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9191.556608,top1_acc,-91.29359386594113 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 768, 5: 768, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 3072, 20: 2100, 21: 1524, 22: 756, 23: 483})])",MACs,7365.789184,top1_acc,-91.06851348008904 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 768, 4: 256, 5: 768, 6: 256, 7: 384, 8: 384, 9: 192, 10: 320, 11: 768, 12: 2460, 13: 3072, 14: 3020, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 1590, 20: 3072, 21: 2721, 22: 3072, 23: 483})])",MACs,8288.470528,top1_acc,-91.13776898342815 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 768, 4: 768, 5: 512, 6: 768, 7: 256, 8: 384, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 2488, 14: 3072, 15: 1791, 16: 3018, 17: 3072, 18: 1709, 19: 2403, 20: 3072, 21: 3072, 22: 3072, 23: 197})])",MACs,8685.0944,top1_acc,-91.14024239426169 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 256, 5: 512, 6: 256, 7: 256, 8: 64, 9: 512, 10: 768, 11: 768, 12: 3018, 13: 3024, 14: 1787, 15: 3007, 16: 3072, 17: 3072, 18: 1709, 19: 1590, 20: 1320, 21: 2721, 22: 1957, 23: 197})])",MACs,7550.207488,top1_acc,-91.00420479841702 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 256, 4: 768, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 3018, 13: 2488, 14: 3020, 15: 3072, 16: 1772, 17: 3072, 18: 2974, 19: 2980, 20: 3072, 21: 762, 22: 756, 23: 115})])",MACs,7782.532608,top1_acc,-91.127875340094 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 2460, 13: 3072, 14: 2530, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 3072, 21: 3072, 22: 3072, 23: 197})])",MACs,8998.290944,top1_acc,-91.27627999010636 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 384, 4: 512, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 2974, 19: 1590, 20: 2100, 21: 1524, 22: 756, 23: 197})])",MACs,8060.732928,top1_acc,-91.16497650259709 +"OrderedDict([(, {0: 320, 1: 768, 2: 448, 3: 768, 4: 768, 5: 512, 6: 192, 7: 768, 8: 384, 9: 768, 10: 768, 11: 768, 12: 3018, 13: 3072, 14: 3072, 15: 3072, 16: 3018, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 1524, 22: 3072, 23: 483})])",MACs,8604.222976,top1_acc,-91.17487014593124 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 3072, 21: 3072, 22: 3072, 23: 197})])",MACs,8763.606528,top1_acc,-91.12540192926045 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 256, 4: 768, 5: 512, 6: 448, 7: 256, 8: 384, 9: 768, 10: 768, 11: 768, 12: 3018, 13: 1666, 14: 3020, 15: 1791, 16: 1772, 17: 2500, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,7246.120448,top1_acc,-91.02399208508534 +"OrderedDict([(, {0: 448, 1: 256, 2: 768, 3: 256, 4: 256, 5: 512, 6: 192, 7: 256, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3018, 13: 3072, 14: 2530, 15: 2549, 16: 3072, 17: 2500, 18: 1709, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})])",MACs,8801.682944,top1_acc,-91.13034875092752 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 768, 5: 768, 6: 448, 7: 768, 8: 384, 9: 768, 10: 768, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 2543, 17: 2982, 18: 2452, 19: 2403, 20: 2100, 21: 3072, 22: 3072, 23: 197})])",MACs,8875.47648,top1_acc,-91.20949789760078 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 384, 4: 256, 5: 256, 6: 448, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 2460, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 2452, 19: 2403, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,7630.685696,top1_acc,-91.17734355676478 +"OrderedDict([(, {0: 768, 1: 256, 2: 448, 3: 384, 4: 768, 5: 768, 6: 256, 7: 768, 8: 192, 9: 512, 10: 768, 11: 768, 12: 3072, 13: 3024, 14: 3020, 15: 2549, 16: 1772, 17: 2982, 18: 2452, 19: 2980, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,8707.835392,top1_acc,-91.21197130843434 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 384, 4: 512, 5: 512, 6: 448, 7: 256, 8: 384, 9: 192, 10: 320, 11: 768, 12: 2460, 13: 3072, 14: 1787, 15: 2549, 16: 3018, 17: 3072, 18: 2974, 19: 3072, 20: 2100, 21: 762, 22: 756, 23: 483})])",MACs,7314.08128,top1_acc,-91.05614642592134 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 768, 5: 256, 6: 768, 7: 256, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3018, 13: 2488, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 3072, 22: 3072, 23: 483})])",MACs,9372.763648,top1_acc,-91.24412564927034 +"OrderedDict([(, {0: 320, 1: 768, 2: 448, 3: 768, 4: 512, 5: 256, 6: 192, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 3024, 14: 3020, 15: 1791, 16: 3018, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 1524, 22: 756, 23: 115})])",MACs,6855.0016,top1_acc,-90.96957704674746 +"OrderedDict([(, {0: 768, 1: 256, 2: 448, 3: 256, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 512, 10: 768, 11: 768, 12: 3018, 13: 1666, 14: 3020, 15: 2549, 16: 1772, 17: 2500, 18: 2452, 19: 2403, 20: 1320, 21: 1524, 22: 3072, 23: 115})])",MACs,7477.528064,top1_acc,-91.03141231758595 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 256, 4: 256, 5: 768, 6: 448, 7: 768, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 2452, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,6877.349376,top1_acc,-90.91021518674252 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 3020, 15: 1791, 16: 1772, 17: 2500, 18: 2452, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,6318.130688,top1_acc,-90.97699727924808 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 256, 4: 256, 5: 256, 6: 192, 7: 256, 8: 192, 9: 512, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 3072, 15: 3007, 16: 3018, 17: 2500, 18: 2974, 19: 2980, 20: 2100, 21: 1524, 22: 756, 23: 197})])",MACs,6616.516096,top1_acc,-90.972050457581 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 256, 5: 512, 6: 256, 7: 256, 8: 384, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 3072, 14: 3020, 15: 2549, 16: 2543, 17: 1751, 18: 2974, 19: 3072, 20: 3072, 21: 3072, 22: 1957, 23: 115})])",MACs,7858.095616,top1_acc,-90.98936433341578 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 768, 5: 768, 6: 192, 7: 768, 8: 64, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2936, 21: 3072, 22: 3072, 23: 483})])",MACs,9013.495296,top1_acc,-91.12045510759337 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 1590, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7676.888576,top1_acc,-91.18723720009893 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 512, 5: 768, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 1772, 17: 3072, 18: 2974, 19: 1590, 20: 2936, 21: 2721, 22: 348, 23: 3072})])",MACs,8060.995072,top1_acc,-91.15755627009646 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 512, 5: 768, 6: 192, 7: 768, 8: 192, 9: 192, 10: 320, 11: 512, 12: 1675, 13: 3024, 14: 3020, 15: 1791, 16: 2543, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 3072, 22: 756, 23: 115})])",MACs,7775.061504,top1_acc,-91.09077417759089 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 768, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 2460, 13: 1666, 14: 3020, 15: 3072, 16: 1772, 17: 2500, 18: 2452, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,6747.19488,top1_acc,-90.95720999257976 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 768, 4: 768, 5: 512, 6: 768, 7: 256, 8: 384, 9: 512, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 3072, 15: 2549, 16: 3018, 17: 2500, 18: 1709, 19: 2403, 20: 3072, 21: 1524, 22: 756, 23: 197})])",MACs,7745.832448,top1_acc,-91.12045510759337 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 256, 7: 256, 8: 64, 9: 512, 10: 320, 11: 512, 12: 1675, 13: 2488, 14: 3020, 15: 2549, 16: 2543, 17: 1751, 18: 1709, 19: 2980, 20: 3072, 21: 762, 22: 1957, 23: 115})])",MACs,6640.633344,top1_acc,-91.01904526341825 +"OrderedDict([(, {0: 448, 1: 256, 2: 768, 3: 256, 4: 768, 5: 512, 6: 448, 7: 768, 8: 64, 9: 192, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 3007, 16: 1772, 17: 3072, 18: 1709, 19: 1590, 20: 2100, 21: 1524, 22: 348, 23: 197})])",MACs,6612.649472,top1_acc,-91.07346030175613 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 256, 4: 768, 5: 256, 6: 192, 7: 768, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3018, 13: 3072, 14: 3020, 15: 3007, 16: 3018, 17: 3072, 18: 2974, 19: 2403, 20: 3072, 21: 3072, 22: 3072, 23: 3072})])",MACs,9316.140544,top1_acc,-91.18229037843186 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3018, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 1524, 22: 756, 23: 115})])",MACs,6245.385728,top1_acc,-90.98936433341578 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 256, 4: 512, 5: 256, 6: 192, 7: 384, 8: 768, 9: 512, 10: 320, 11: 512, 12: 1675, 13: 3072, 14: 3072, 15: 2549, 16: 1772, 17: 2500, 18: 2974, 19: 1590, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,7560.365568,top1_acc,-91.10066782092505 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 1709, 19: 2980, 20: 2936, 21: 762, 22: 1957, 23: 197})])",MACs,6309.4144,top1_acc,-91.03635913925304 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 256, 4: 768, 5: 768, 6: 448, 7: 768, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3007, 16: 2543, 17: 3072, 18: 2452, 19: 3072, 20: 1320, 21: 2721, 22: 1957, 23: 197})])",MACs,8538.031616,top1_acc,-91.1847637892654 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 768, 4: 768, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 3020, 15: 1791, 16: 1772, 17: 3072, 18: 2452, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,6730.4832,top1_acc,-90.97947069008163 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 256, 5: 512, 6: 256, 7: 256, 8: 64, 9: 512, 10: 768, 11: 768, 12: 3018, 13: 3024, 14: 1787, 15: 1791, 16: 3072, 17: 2500, 18: 2974, 19: 1590, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,7062.226432,top1_acc,-90.98936433341578 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 384, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 2460, 13: 1666, 14: 1787, 15: 3072, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,7335.70816,top1_acc,-91.16002968093 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 1524, 22: 756, 23: 197})])",MACs,6151.80032,top1_acc,-90.972050457581 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 768, 5: 768, 6: 256, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9419.884032,top1_acc,-91.27133316843927 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 256, 5: 768, 6: 448, 7: 256, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3018, 13: 2488, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 3072, 22: 1957, 23: 483})])",MACs,8908.178944,top1_acc,-91.1971308434331 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 768, 5: 768, 6: 448, 7: 768, 8: 384, 9: 768, 10: 768, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 1772, 17: 2982, 18: 2452, 19: 2980, 20: 2100, 21: 1524, 22: 348, 23: 197})])",MACs,8228.30848,top1_acc,-91.18229037843186 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 256, 4: 512, 5: 256, 6: 192, 7: 384, 8: 768, 9: 768, 10: 320, 11: 512, 12: 1675, 13: 3072, 14: 3072, 15: 2549, 16: 2543, 17: 2500, 18: 2974, 19: 1590, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,7821.00224,top1_acc,-91.1031412317586 +"OrderedDict([(, {0: 320, 1: 768, 2: 448, 3: 384, 4: 256, 5: 768, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 2460, 13: 1666, 14: 1787, 15: 3072, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,7923.435008,top1_acc,-91.16002968093 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3020, 15: 3007, 16: 1772, 17: 2982, 18: 2452, 19: 1590, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,8231.323136,top1_acc,-91.14518921592877 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 256, 4: 256, 5: 256, 6: 192, 7: 768, 8: 192, 9: 768, 10: 320, 11: 512, 12: 1675, 13: 3072, 14: 3072, 15: 3007, 16: 3018, 17: 2982, 18: 2974, 19: 2980, 20: 2100, 21: 3072, 22: 3072, 23: 197})])",MACs,8074.561024,top1_acc,-91.03883255008657 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 384, 4: 512, 5: 512, 6: 448, 7: 256, 8: 192, 9: 192, 10: 320, 11: 768, 12: 2460, 13: 1666, 14: 1787, 15: 2549, 16: 3018, 17: 3072, 18: 2974, 19: 3072, 20: 2100, 21: 762, 22: 756, 23: 483})])",MACs,6819.546624,top1_acc,-91.04872619342072 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 256, 4: 768, 5: 512, 6: 448, 7: 768, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 3007, 16: 1772, 17: 3072, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 756, 23: 483})])",MACs,7485.851136,top1_acc,-91.02399208508534 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 384, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3020, 15: 3007, 16: 2543, 17: 2982, 18: 2974, 19: 1590, 20: 2936, 21: 1524, 22: 756, 23: 197})])",MACs,8576.566784,top1_acc,-91.20455107593372 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 256, 4: 768, 5: 512, 6: 448, 7: 384, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3018, 13: 1666, 14: 3020, 15: 2549, 16: 1772, 17: 2500, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,7613.25312,top1_acc,-91.13282216176107 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 384, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 1590, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,7534.675456,top1_acc,-91.16744991343062 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 768, 4: 768, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 320, 11: 768, 12: 1675, 13: 2488, 14: 3020, 15: 1791, 16: 1772, 17: 3072, 18: 2452, 19: 2980, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,7111.312896,top1_acc,-91.01162503091763 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 768, 11: 768, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 1772, 17: 2982, 18: 3072, 19: 2403, 20: 3072, 21: 3072, 22: 3072, 23: 197})])",MACs,8907.523584,top1_acc,-91.17981696759831 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 768, 4: 768, 5: 768, 6: 448, 7: 768, 8: 384, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3018, 17: 1751, 18: 2452, 19: 2980, 20: 2100, 21: 1524, 22: 3072, 23: 483})])",MACs,9186.903552,top1_acc,-91.27875340093989 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3018, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 3072, 21: 3072, 22: 3072, 23: 115})])",MACs,8525.645312,top1_acc,-91.20207766510018 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 512, 5: 768, 6: 448, 7: 768, 8: 384, 9: 512, 10: 768, 11: 512, 12: 3072, 13: 3024, 14: 3020, 15: 3007, 16: 2543, 17: 2982, 18: 2452, 19: 2403, 20: 2100, 21: 3072, 22: 3072, 23: 197})])",MACs,8647.149056,top1_acc,-91.18971061093248 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 64, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,7614.825984,top1_acc,-91.05614642592134 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 768, 4: 768, 5: 512, 6: 192, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3018, 13: 3072, 14: 3072, 15: 3007, 16: 3018, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 1524, 22: 3072, 23: 483})])",MACs,8014.530048,top1_acc,-91.06851348008904 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 384, 9: 512, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 3072, 18: 1709, 19: 2980, 20: 2936, 21: 762, 22: 1957, 23: 197})])",MACs,6048.777728,top1_acc,-90.99925797674993 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,5854.070272,top1_acc,-91.01657185258472 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,6329.927168,top1_acc,-91.11303487509275 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 512, 5: 768, 6: 768, 7: 256, 8: 384, 9: 512, 10: 320, 11: 768, 12: 2460, 13: 1666, 14: 2530, 15: 3007, 16: 2543, 17: 2500, 18: 3072, 19: 2403, 20: 3072, 21: 1524, 22: 756, 23: 197})])",MACs,7540.246016,top1_acc,-91.07098689092258 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 384, 9: 512, 10: 320, 11: 768, 12: 3018, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 1524, 22: 756, 23: 115})])",MACs,6739.920384,top1_acc,-91.05119960425426 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 1590, 20: 2100, 21: 1524, 22: 348, 23: 197})])",MACs,5568.595456,top1_acc,-90.93247588424437 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 512, 5: 512, 6: 256, 7: 768, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 2721, 22: 3072, 23: 197})])",MACs,8675.722752,top1_acc,-91.29359386594113 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 256, 4: 768, 5: 512, 6: 448, 7: 256, 8: 384, 9: 192, 10: 768, 11: 512, 12: 1675, 13: 1666, 14: 3020, 15: 1791, 16: 3018, 17: 2500, 18: 1709, 19: 1590, 20: 3072, 21: 3072, 22: 1957, 23: 3072})])",MACs,7714.571776,top1_acc,-91.07098689092258 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7477.92128,top1_acc,-91.12540192926045 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 768, 5: 256, 6: 768, 7: 256, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3018, 13: 1666, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 3072, 22: 1957, 23: 483})])",MACs,8991.933952,top1_acc,-91.23423200593619 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 256, 4: 512, 5: 512, 6: 448, 7: 256, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3018, 13: 1666, 14: 3020, 15: 3007, 16: 2543, 17: 2500, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,7336.887808,top1_acc,-91.09324758842445 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 192, 4: 768, 5: 512, 6: 192, 7: 768, 8: 384, 9: 768, 10: 768, 11: 512, 12: 3018, 13: 3024, 14: 3072, 15: 3007, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 3072, 22: 3072, 23: 197})])",MACs,8292.795904,top1_acc,-91.13776898342815 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 768, 4: 768, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 320, 11: 768, 12: 3018, 13: 1666, 14: 3020, 15: 1791, 16: 1772, 17: 3072, 18: 2452, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,7147.881984,top1_acc,-90.97699727924808 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 256, 5: 768, 6: 448, 7: 384, 8: 384, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 2543, 17: 2982, 18: 2452, 19: 1590, 20: 2100, 21: 3072, 22: 3072, 23: 197})])",MACs,8443.004416,top1_acc,-91.20455107593372 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 256, 4: 768, 5: 512, 6: 448, 7: 384, 8: 384, 9: 768, 10: 768, 11: 768, 12: 3018, 13: 1666, 14: 3020, 15: 1791, 16: 1772, 17: 3072, 18: 1709, 19: 2980, 20: 2936, 21: 1524, 22: 1957, 23: 197})])",MACs,7577.470464,top1_acc,-91.05367301508781 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 1524, 22: 756, 23: 115})])",MACs,5827.986944,top1_acc,-90.98194410091516 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,8109.36064,top1_acc,-91.28122681177344 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 384, 4: 256, 5: 256, 6: 192, 7: 256, 8: 384, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 3072, 23: 197})])",MACs,6656.09984,top1_acc,-90.99431115508287 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 384, 4: 256, 5: 256, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2460, 13: 3072, 14: 3072, 15: 1791, 16: 2543, 17: 3072, 18: 2452, 19: 2403, 20: 2936, 21: 3072, 22: 1957, 23: 483})])",MACs,8571.848192,top1_acc,-91.21444471926787 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 768, 5: 256, 6: 768, 7: 256, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3018, 13: 2488, 14: 1787, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2100, 21: 1524, 22: 3072, 23: 197})])",MACs,8431.601152,top1_acc,-91.23175859510265 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9759.688192,top1_acc,-91.33811526094485 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 256, 4: 768, 5: 256, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 768, 12: 3072, 13: 2488, 14: 3020, 15: 3072, 16: 1772, 17: 3072, 18: 2974, 19: 2980, 20: 3072, 21: 1524, 22: 756, 23: 115})])",MACs,7888.438784,top1_acc,-91.08830076675736 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 384, 4: 512, 5: 768, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 3007, 16: 2543, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 1524, 22: 3072, 23: 115})])",MACs,7139.493376,top1_acc,-91.01904526341825 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 512, 5: 256, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 756, 23: 197})])",MACs,7567.312384,top1_acc,-91.1971308434331 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 2460, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2403, 20: 2100, 21: 3072, 22: 756, 23: 197})])",MACs,7005.210112,top1_acc,-91.1105614642592 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 768, 5: 768, 6: 448, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 2543, 17: 2982, 18: 2452, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,8219.985408,top1_acc,-91.24907247093742 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 768, 5: 512, 6: 256, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 2549, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 3072, 22: 3072, 23: 115})])",MACs,9048.294912,top1_acc,-91.28864704427406 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 384, 4: 256, 5: 256, 6: 192, 7: 384, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3018, 13: 1666, 14: 1787, 15: 3072, 16: 2543, 17: 2500, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,7577.339392,top1_acc,-91.16002968093 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 256, 5: 768, 6: 256, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 1772, 17: 1751, 18: 3072, 19: 2980, 20: 2936, 21: 2721, 22: 756, 23: 197})])",MACs,7722.894848,top1_acc,-91.06356665842196 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 256, 8: 768, 9: 768, 10: 320, 11: 768, 12: 2460, 13: 2488, 14: 3072, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 2936, 21: 1524, 22: 756, 23: 483})])",MACs,7860.127232,top1_acc,-91.05861983675489 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 512, 5: 512, 6: 256, 7: 768, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,8058.373632,top1_acc,-91.2416522384368 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 512, 5: 512, 6: 256, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 1524, 22: 756, 23: 197})])",MACs,8156.612096,top1_acc,-91.22186495176848 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 384, 9: 768, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 2974, 19: 2980, 20: 2936, 21: 762, 22: 1957, 23: 197})])",MACs,6939.805184,top1_acc,-91.14271580509524 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 2530, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 3072, 21: 3072, 22: 3072, 23: 197})])",MACs,9473.033728,top1_acc,-91.30843433094236 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 384, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3018, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2936, 21: 1524, 22: 756, 23: 115})])",MACs,6658.917888,top1_acc,-90.972050457581 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 768, 5: 256, 6: 256, 7: 256, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3018, 13: 2488, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 1524, 22: 3072, 23: 197})])",MACs,8091.796992,top1_acc,-91.20207766510018 +"OrderedDict([(, {0: 448, 1: 256, 2: 768, 3: 256, 4: 768, 5: 512, 6: 448, 7: 768, 8: 64, 9: 192, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 3007, 16: 1772, 17: 2500, 18: 1709, 19: 1590, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6350.3744,top1_acc,-90.95720999257976 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 512, 6: 256, 7: 768, 8: 192, 9: 512, 10: 320, 11: 768, 12: 1675, 13: 3024, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 2721, 22: 756, 23: 197})])",MACs,7364.21632,top1_acc,-91.09819441009151 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 384, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 512, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 3072, 18: 2974, 19: 1590, 20: 2936, 21: 762, 22: 1957, 23: 197})])",MACs,6542.198272,top1_acc,-90.91021518674252 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 256, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3018, 13: 2488, 14: 3072, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2936, 21: 1524, 22: 1957, 23: 483})])",MACs,7841.3184,top1_acc,-91.05861983675489 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 256, 4: 512, 5: 512, 6: 448, 7: 256, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3018, 13: 1666, 14: 3020, 15: 3007, 16: 1772, 17: 2500, 18: 1709, 19: 2403, 20: 2100, 21: 1524, 22: 348, 23: 197})])",MACs,6755.517952,top1_acc,-91.01162503091763 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 384, 4: 512, 5: 768, 6: 256, 7: 384, 8: 192, 9: 512, 10: 192, 11: 512, 12: 2460, 13: 3024, 14: 3020, 15: 3007, 16: 2543, 17: 2982, 18: 2452, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,8049.657344,top1_acc,-91.09324758842445 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 768, 5: 512, 6: 768, 7: 256, 8: 384, 9: 768, 10: 320, 11: 768, 12: 2460, 13: 2488, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2936, 21: 3072, 22: 3072, 23: 483})])",MACs,9131.132416,top1_acc,-91.30596092010883 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 197})])",MACs,7551.059456,top1_acc,-91.16250309176354 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 512, 12: 3018, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 3072, 18: 1709, 19: 2403, 20: 2100, 21: 3072, 22: 1957, 23: 197})])",MACs,6986.40128,top1_acc,-90.98194410091516 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 384, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 3072, 23: 483})])",MACs,6978.930176,top1_acc,-91.01904526341825 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 384, 4: 512, 5: 768, 6: 768, 7: 768, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3020, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 1590, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9095.67744,top1_acc,-91.2169181301014 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,5699.536384,top1_acc,-91.00420479841702 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7634.617856,top1_acc,-91.24412564927034 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 448, 7: 768, 8: 768, 9: 512, 10: 192, 11: 768, 12: 2460, 13: 1666, 14: 3072, 15: 1791, 16: 2543, 17: 3072, 18: 2452, 19: 2403, 20: 2100, 21: 3072, 22: 1957, 23: 483})])",MACs,8158.316032,top1_acc,-91.20455107593372 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 192, 9: 768, 10: 320, 11: 768, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 1524, 22: 756, 23: 197})])",MACs,6833.37472,top1_acc,-90.96957704674746 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 512, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 1590, 20: 2100, 21: 1524, 22: 348, 23: 197})])",MACs,5759.436288,top1_acc,-90.95226317091269 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 768, 5: 256, 6: 768, 7: 256, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3018, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2100, 21: 1524, 22: 3072, 23: 197})])",MACs,8546.420224,top1_acc,-91.22186495176848 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 384, 4: 512, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 2974, 19: 2980, 20: 2100, 21: 1524, 22: 756, 23: 197})])",MACs,8361.281024,top1_acc,-91.21444471926787 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 384, 4: 256, 5: 256, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2460, 13: 3072, 14: 3072, 15: 1791, 16: 2543, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 3072, 22: 1957, 23: 483})])",MACs,8830.060032,top1_acc,-91.14271580509524 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 768, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7427.78624,top1_acc,-91.24907247093742 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,5663.22944,top1_acc,-91.00420479841702 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 2460, 13: 2488, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 3072, 21: 3072, 22: 3072, 23: 197})])",MACs,8317.240832,top1_acc,-91.18971061093248 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 1590, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,6029.379072,top1_acc,-91.06851348008904 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 448, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2452, 19: 2980, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7219.70944,top1_acc,-91.03635913925304 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 756, 23: 197})])",MACs,6265.243136,top1_acc,-91.00173138758348 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,8525.579776,top1_acc,-91.20702448676725 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 384, 4: 256, 5: 512, 6: 192, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 3072, 15: 3072, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,7926.777344,top1_acc,-91.19960425426663 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,5944.903168,top1_acc,-91.03635913925304 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 512, 5: 256, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3007, 16: 2543, 17: 3072, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,7821.133312,top1_acc,-91.23917882760327 +"OrderedDict([(, {0: 384, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 512, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 1590, 20: 2100, 21: 2721, 22: 348, 23: 483})])",MACs,7239.04256,top1_acc,-91.15013603759584 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 384, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3020, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 2721, 22: 348, 23: 197})])",MACs,8597.93152,top1_acc,-91.19960425426663 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 384, 9: 512, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,6882.52672,top1_acc,-91.08088053425674 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 64, 9: 192, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,6457.656832,top1_acc,-90.95226317091269 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 256, 5: 512, 6: 192, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 2460, 13: 3024, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,8682.407424,top1_acc,-91.19465743259956 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 768, 5: 768, 6: 192, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3007, 16: 2543, 17: 3072, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,7517.439488,top1_acc,-91.16744991343062 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 192, 7: 768, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2100, 21: 2721, 22: 1957, 23: 115})])",MACs,7236.486656,top1_acc,-91.02646549591887 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 768, 5: 768, 6: 256, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 2543, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9437.578752,top1_acc,-91.27875340093989 +"OrderedDict([(, {0: 448, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 384, 9: 768, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 2974, 19: 2980, 20: 2936, 21: 762, 22: 1957, 23: 197})])",MACs,7130.646016,top1_acc,-91.10066782092505 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 256, 6: 192, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2403, 20: 2100, 21: 3072, 22: 756, 23: 197})])",MACs,7650.805248,top1_acc,-91.08830076675736 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 256, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3018, 13: 2488, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 483})])",MACs,7926.18752,top1_acc,-91.10066782092505 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 483})])",MACs,6922.307072,top1_acc,-91.10561464259213 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,5549.786624,top1_acc,-91.00420479841702 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 768, 5: 768, 6: 256, 7: 768, 8: 192, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,8528.922112,top1_acc,-91.15755627009646 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 192, 4: 768, 5: 768, 6: 448, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 2452, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,7628.916224,top1_acc,-91.1971308434331 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 1590, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,5784.012288,top1_acc,-90.97947069008163 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 384, 9: 512, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2980, 20: 2936, 21: 762, 22: 756, 23: 197})])",MACs,5794.9568,top1_acc,-91.01657185258472 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 2974, 19: 2980, 20: 2100, 21: 1524, 22: 756, 23: 197})])",MACs,6879.643136,top1_acc,-91.02399208508534 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 512, 5: 768, 6: 256, 7: 768, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 2721, 22: 3072, 23: 197})])",MACs,8702.985728,top1_acc,-91.27627999010636 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 768, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 2974, 19: 1590, 20: 2100, 21: 1524, 22: 348, 23: 197})])",MACs,6113.854976,top1_acc,-90.94978976007914 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 768, 4: 768, 5: 512, 6: 448, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 3072, 15: 3072, 16: 3018, 17: 1751, 18: 2452, 19: 2980, 20: 2100, 21: 1524, 22: 3072, 23: 483})])",MACs,8392.47616,top1_acc,-91.22681177343557 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 256, 7: 384, 8: 192, 9: 512, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2500, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,6017.517056,top1_acc,-91.02646549591887 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 448, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 3024, 14: 3072, 15: 1791, 16: 2543, 17: 2982, 18: 2452, 19: 2980, 20: 2936, 21: 762, 22: 1957, 23: 197})])",MACs,7011.96032,top1_acc,-91.0784071234232 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 256, 7: 384, 8: 192, 9: 512, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6521.42336,top1_acc,-91.02893890675242 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9741.993472,top1_acc,-91.36284936928024 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 448, 7: 768, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 1957, 23: 197})])",MACs,6959.400448,top1_acc,-90.99925797674993 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 197})])",MACs,6905.46432,top1_acc,-91.08088053425674 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 768, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 1590, 20: 2936, 21: 3072, 22: 1957, 23: 115})])",MACs,6797.919744,top1_acc,-91.07346030175613 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 756, 23: 115})])",MACs,5849.417216,top1_acc,-91.02646549591887 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 384, 9: 512, 10: 320, 11: 512, 12: 1675, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 3072, 18: 1709, 19: 2980, 20: 2936, 21: 762, 22: 348, 23: 197})])",MACs,6008.866304,top1_acc,-90.97699727924808 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 768, 5: 512, 6: 256, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 2549, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2936, 21: 3072, 22: 3072, 23: 115})])",MACs,9161.737728,top1_acc,-91.2663863467722 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 768, 4: 768, 5: 256, 6: 448, 7: 256, 8: 384, 9: 768, 10: 768, 11: 768, 12: 3018, 13: 3072, 14: 3072, 15: 3072, 16: 3018, 17: 1751, 18: 2452, 19: 2980, 20: 2100, 21: 3072, 22: 1957, 23: 483})])",MACs,8825.210368,top1_acc,-91.12540192926045 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 768, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 1957, 23: 197})])",MACs,7467.697664,top1_acc,-91.19465743259956 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,5586.093568,top1_acc,-90.97947069008163 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 2488, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9056.421376,top1_acc,-91.30843433094236 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7809.467904,top1_acc,-91.16497650259709 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2980, 20: 2936, 21: 762, 22: 1957, 23: 197})])",MACs,6828.852736,top1_acc,-91.0784071234232 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 768, 5: 512, 6: 448, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 2452, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,7574.390272,top1_acc,-91.2292851842691 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 483})])",MACs,7186.94144,top1_acc,-91.10561464259213 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 256, 7: 768, 8: 192, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7182.484992,top1_acc,-91.1971308434331 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 256, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3018, 13: 2488, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2980, 20: 2936, 21: 3072, 22: 1957, 23: 483})])",MACs,8808.171008,top1_acc,-91.23917882760327 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 192, 7: 768, 8: 192, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,7766.672896,top1_acc,-91.09572099925798 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3007, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 1524, 22: 348, 23: 197})])",MACs,5858.461184,top1_acc,-90.9151620084096 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,6784.288256,top1_acc,-91.14024239426169 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 192, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 2543, 17: 3072, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 3072, 23: 197})])",MACs,8720.614912,top1_acc,-91.21197130843434 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 768, 5: 512, 6: 256, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 2530, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 3072, 21: 3072, 22: 3072, 23: 115})])",MACs,9320.596992,top1_acc,-91.28864704427406 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2980, 20: 2936, 21: 762, 22: 1957, 23: 197})])",MACs,7091.521024,top1_acc,-91.08830076675736 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,6660.490752,top1_acc,-91.1476626267623 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 384, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,6619.792896,top1_acc,-91.06604006925551 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 512, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7723.222528,top1_acc,-91.26143952510512 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 384, 4: 256, 5: 768, 6: 192, 7: 768, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3020, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7751.992832,top1_acc,-91.19218402176602 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 512, 5: 512, 6: 256, 7: 768, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 2721, 22: 1957, 23: 197})])",MACs,8374.715904,top1_acc,-91.26143952510512 +"OrderedDict([(, {0: 384, 1: 768, 2: 448, 3: 192, 4: 768, 5: 768, 6: 192, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7727.678976,top1_acc,-91.20455107593372 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 1709, 19: 2403, 20: 2100, 21: 3072, 22: 756, 23: 197})])",MACs,6485.771776,top1_acc,-91.05614642592134 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,6384.45312,top1_acc,-91.04625278258719 +"OrderedDict([(, {0: 384, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 512, 10: 192, 11: 768, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2980, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7213.286912,top1_acc,-91.12292851842692 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 512, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 1590, 20: 1320, 21: 2721, 22: 1957, 23: 115})])",MACs,6905.267712,top1_acc,-90.98689092258225 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 384, 4: 512, 5: 256, 6: 256, 7: 384, 8: 192, 9: 512, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 3020, 15: 3007, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 2721, 22: 1957, 23: 115})])",MACs,7010.97728,top1_acc,-90.99925797674993 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 256, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 1590, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6231.557632,top1_acc,-91.0215186742518 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,5095.425536,top1_acc,-90.95226317091269 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 384, 4: 256, 5: 768, 6: 768, 7: 768, 8: 192, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 1957, 23: 197})])",MACs,8506.770944,top1_acc,-91.26885975760574 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 2549, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 3072, 22: 3072, 23: 197})])",MACs,9200.731648,top1_acc,-91.27380657927282 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 1709, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7327.254016,top1_acc,-91.0091516200841 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2980, 20: 2936, 21: 762, 22: 1957, 23: 197})])",MACs,5978.850816,top1_acc,-91.01162503091763 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 3072, 16: 2543, 17: 2500, 18: 3072, 19: 1590, 20: 2936, 21: 762, 22: 1957, 23: 115})])",MACs,6745.294336,top1_acc,-91.05367301508781 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 768, 5: 768, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 3007, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 3072, 21: 3072, 22: 1957, 23: 483})])",MACs,8197.375488,top1_acc,-91.17487014593124 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 512, 5: 768, 6: 256, 7: 768, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,8867.350016,top1_acc,-91.29112045510759 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5269.751296,top1_acc,-90.98936433341578 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 2452, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,8276.674048,top1_acc,-91.21939154093495 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 768, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2980, 20: 2100, 21: 2721, 22: 1957, 23: 197})])",MACs,7857.571328,top1_acc,-91.23917882760327 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 192, 7: 768, 8: 384, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 756, 23: 197})])",MACs,7647.65952,top1_acc,-91.11798169675983 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 512, 5: 256, 6: 448, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 2543, 17: 2982, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 756, 23: 197})])",MACs,7510.623744,top1_acc,-91.12540192926045 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6011.487744,top1_acc,-91.06109324758842 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 2488, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2980, 20: 2936, 21: 1524, 22: 756, 23: 483})])",MACs,8414.627328,top1_acc,-91.18971061093248 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 512, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 1524, 22: 3072, 23: 483})])",MACs,7083.591168,top1_acc,-91.03141231758595 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 256, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6574.769664,top1_acc,-91.12045510759337 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 512, 5: 512, 6: 256, 7: 768, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 2452, 19: 2403, 20: 2100, 21: 1524, 22: 3072, 23: 197})])",MACs,8236.697088,top1_acc,-91.25896611427157 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9766.372864,top1_acc,-91.40984417511748 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 256, 7: 768, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 115})])",MACs,5893.195264,top1_acc,-90.9967845659164 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 3072, 15: 3007, 16: 3072, 17: 2500, 18: 3072, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,7615.350272,top1_acc,-91.18229037843186 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,5726.79936,top1_acc,-91.06356665842196 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,6654.723584,top1_acc,-91.08088053425674 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3007, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 348, 23: 197})])",MACs,8626.505216,top1_acc,-91.30101409844174 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 768, 5: 512, 6: 448, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 2452, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,8021.87008,top1_acc,-91.29112045510759 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,6824.068608,top1_acc,-91.15013603759584 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 192, 7: 384, 8: 384, 9: 512, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 1957, 23: 197})])",MACs,6780.61824,top1_acc,-91.1031412317586 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,5292.754432,top1_acc,-90.93000247341084 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 256, 7: 768, 8: 192, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7191.922176,top1_acc,-91.21197130843434 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 2488, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9165.47328,top1_acc,-91.28370022260698 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 448, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 2974, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 197})])",MACs,7454.656,top1_acc,-91.17487014593124 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,8165.590528,top1_acc,-91.19465743259956 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 768, 5: 512, 6: 448, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,8761.247232,top1_acc,-91.31585456344298 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 384, 4: 768, 5: 768, 6: 448, 7: 768, 8: 384, 9: 512, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 2721, 22: 1957, 23: 197})])",MACs,8659.011072,top1_acc,-91.2169181301014 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 2488, 14: 2530, 15: 3007, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 3072, 21: 3072, 22: 3072, 23: 197})])",MACs,8763.08224,top1_acc,-91.2292851842691 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 512, 5: 768, 6: 192, 7: 384, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 1772, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 756, 23: 197})])",MACs,8069.580288,top1_acc,-91.20949789760078 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 384, 4: 768, 5: 768, 6: 192, 7: 384, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 115})])",MACs,8456.570368,top1_acc,-91.13282216176107 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 1709, 19: 2980, 20: 2936, 21: 762, 22: 1957, 23: 197})])",MACs,6527.518208,top1_acc,-91.00667820925055 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,5715.65824,top1_acc,-91.01409844175117 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3024, 14: 3072, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 3072, 23: 197})])",MACs,8767.800832,top1_acc,-91.16497650259709 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 320, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,6336.808448,top1_acc,-91.02646549591887 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,5499.651584,top1_acc,-91.01162503091763 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 512, 6: 192, 7: 768, 8: 192, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 1590, 20: 1320, 21: 2721, 22: 348, 23: 115})])",MACs,6676.547072,top1_acc,-91.09077417759089 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 384, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,7138.379264,top1_acc,-91.09819441009151 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,8099.923456,top1_acc,-91.25154588177095 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,5440.73472,top1_acc,-90.972050457581 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 768, 5: 768, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 2543, 17: 2500, 18: 2452, 19: 2980, 20: 1320, 21: 1524, 22: 1957, 23: 115})])",MACs,7095.256576,top1_acc,-91.1105614642592 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 512, 5: 512, 6: 256, 7: 768, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 3072, 23: 197})])",MACs,8144.75008,top1_acc,-91.1476626267623 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,6564.152832,top1_acc,-91.1031412317586 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 512, 5: 768, 6: 192, 7: 768, 8: 384, 9: 512, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7665.157632,top1_acc,-91.21939154093495 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2500, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5216.994816,top1_acc,-90.95226317091269 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 2488, 14: 3072, 15: 1791, 16: 3072, 17: 3072, 18: 2974, 19: 1590, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,8866.170368,top1_acc,-91.19960425426663 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 1590, 20: 2100, 21: 1524, 22: 348, 23: 115})])",MACs,5388.895744,top1_acc,-90.91763541924314 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 256, 7: 768, 8: 192, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6945.1136,top1_acc,-91.15755627009646 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6064.244224,top1_acc,-91.13529557259461 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 768, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,6219.63008,top1_acc,-91.04872619342072 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7832.274432,top1_acc,-91.29112045510759 +"OrderedDict([(, {0: 384, 1: 256, 2: 448, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6591.153664,top1_acc,-91.08830076675736 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3007, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 483})])",MACs,10070.722048,top1_acc,-91.39747712094979 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 448, 7: 384, 8: 384, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 1524, 22: 348, 23: 115})])",MACs,6206.653952,top1_acc,-91.09324758842445 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,6570.051072,top1_acc,-91.22681177343557 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,7204.63616,top1_acc,-91.16992332426416 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,6483.281408,top1_acc,-91.11303487509275 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9487.058432,top1_acc,-91.27627999010636 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,6206.260736,top1_acc,-91.15508285926293 +"OrderedDict([(, {0: 448, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 2488, 14: 3072, 15: 3007, 16: 2543, 17: 3072, 18: 1709, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,8557.95456,top1_acc,-91.27875340093989 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 64, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 3072, 19: 2980, 20: 2936, 21: 2721, 22: 756, 23: 197})])",MACs,7862.158848,top1_acc,-91.06356665842196 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 512, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 3007, 16: 2543, 17: 3072, 18: 1709, 19: 2403, 20: 2936, 21: 762, 22: 348, 23: 197})])",MACs,6856.836608,top1_acc,-91.16992332426416 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6233.982464,top1_acc,-91.09324758842445 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2500, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,5460.788736,top1_acc,-90.94731634924561 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 2488, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,8947.369472,top1_acc,-91.30101409844174 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 768, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,6848.12032,top1_acc,-91.18971061093248 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,9455.339008,top1_acc,-91.3727430126144 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 1772, 17: 2500, 18: 2452, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 197})])",MACs,7032.210944,top1_acc,-91.05367301508781 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 256, 7: 768, 8: 192, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6339.23328,top1_acc,-91.09819441009151 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,5870.716416,top1_acc,-90.95968340341331 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,4942.071296,top1_acc,-90.92505565174376 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3007, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 348, 23: 197})])",MACs,8881.440256,top1_acc,-91.2663863467722 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 1957, 23: 197})])",MACs,5894.964736,top1_acc,-90.99183774424931 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2452, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,8520.336896,top1_acc,-91.31585456344298 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 384, 4: 256, 5: 512, 6: 192, 7: 768, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 3072, 15: 3007, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 197})])",MACs,7379.486208,top1_acc,-91.13034875092752 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 1320, 21: 2721, 22: 348, 23: 197})])",MACs,7833.912832,top1_acc,-91.17981696759831 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,5493.16352,top1_acc,-90.95720999257976 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,4851.631616,top1_acc,-90.96710363591393 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 256, 6: 192, 7: 768, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5911.545344,top1_acc,-90.95720999257976 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6913.197568,top1_acc,-91.21939154093495 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3007, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 756, 23: 197})])",MACs,8761.247232,top1_acc,-91.26143952510512 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 384, 4: 256, 5: 512, 6: 256, 7: 768, 8: 192, 9: 512, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7599.556096,top1_acc,-91.17734355676478 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9873.131008,top1_acc,-91.35790254761315 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7414.810112,top1_acc,-91.20702448676725 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 256, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,5673.05984,top1_acc,-90.95473658174623 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,5305.992704,top1_acc,-90.96215681424684 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 512, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7140.41088,top1_acc,-91.1847637892654 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,5602.215424,top1_acc,-90.97947069008163 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 256, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7437.28896,top1_acc,-91.20949789760078 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,5766.12096,top1_acc,-90.99431115508287 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9848.161792,top1_acc,-91.37026960178085 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 192, 4: 768, 5: 512, 6: 448, 7: 384, 8: 64, 9: 192, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 1524, 22: 1957, 23: 115})])",MACs,6701.254144,top1_acc,-90.95968340341331 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 768, 5: 512, 6: 448, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 2721, 22: 3072, 23: 197})])",MACs,8191.673856,top1_acc,-91.16992332426416 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,5477.041664,top1_acc,-90.98689092258225 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 448, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9554.363904,top1_acc,-91.34553549344547 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 384, 4: 512, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,7833.060864,top1_acc,-91.1105614642592 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 1957, 23: 197})])",MACs,6677.595648,top1_acc,-91.07593371258966 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6274.876928,top1_acc,-91.13529557259461 +"OrderedDict([(, {0: 448, 1: 256, 2: 768, 3: 384, 4: 768, 5: 512, 6: 768, 7: 768, 8: 64, 9: 768, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 3007, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,7865.173504,top1_acc,-91.07098689092258 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 768, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3007, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2936, 21: 762, 22: 756, 23: 483})])",MACs,8553.03936,top1_acc,-91.25154588177095 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6504.252928,top1_acc,-91.19960425426663 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 512, 5: 768, 6: 192, 7: 384, 8: 384, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,5848.172032,top1_acc,-90.99925797674993 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6284.117504,top1_acc,-91.08582735592383 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,6042.813952,top1_acc,-91.06356665842196 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9660.204544,top1_acc,-91.38263665594856 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3007, 16: 2543, 17: 1751, 18: 2452, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6172.247552,top1_acc,-91.08088053425674 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8401.847808,top1_acc,-91.3034875092753 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5191.828992,top1_acc,-91.05861983675489 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 256, 7: 768, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 1524, 22: 348, 23: 197})])",MACs,7219.70944,top1_acc,-91.22186495176848 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 3024, 14: 3072, 15: 3007, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,8610.121216,top1_acc,-91.21939154093495 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5658.576384,top1_acc,-91.07346030175613 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 192, 9: 192, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,8450.213376,top1_acc,-91.13282216176107 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 1791, 16: 1772, 17: 2982, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,6818.891264,top1_acc,-91.06604006925551 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 512, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,7312.639488,top1_acc,-91.07593371258966 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,6987.777536,top1_acc,-91.20455107593372 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 64, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 115})])",MACs,7003.44064,top1_acc,-90.99431115508287 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 384, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5480.71168,top1_acc,-90.96710363591393 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5879.105024,top1_acc,-91.06109324758842 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5691.08224,top1_acc,-91.02646549591887 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,8423.998976,top1_acc,-91.18723720009893 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 448, 7: 768, 8: 384, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 1524, 22: 348, 23: 115})])",MACs,6370.231808,top1_acc,-91.09819441009151 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 768, 5: 512, 6: 448, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,7273.973248,top1_acc,-91.17981696759831 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 512, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2936, 21: 762, 22: 756, 23: 197})])",MACs,5877.728768,top1_acc,-91.07098689092258 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 3072, 19: 2403, 20: 1320, 21: 1524, 22: 3072, 23: 197})])",MACs,8211.400192,top1_acc,-91.17734355676478 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6491.866624,top1_acc,-91.17487014593124 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5973.411328,top1_acc,-90.92505565174376 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,6684.542464,top1_acc,-91.14518921592877 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2452, 19: 2980, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,6463.555072,top1_acc,-91.05367301508781 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,5357.962752,top1_acc,-90.87558743507297 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 2936, 21: 762, 22: 348, 23: 483})])",MACs,7619.216896,top1_acc,-91.20455107593372 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 3072, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 483})])",MACs,6280.119808,top1_acc,-91.05614642592134 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 192, 7: 384, 8: 384, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,6651.84,top1_acc,-91.18971061093248 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 192, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 1772, 17: 3072, 18: 1709, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8318.486016,top1_acc,-91.19218402176602 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8014.267904,top1_acc,-91.28370022260698 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 384, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2452, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 115})])",MACs,7657.031168,top1_acc,-91.2169181301014 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 3072, 17: 3072, 18: 1709, 19: 2403, 20: 2936, 21: 2721, 22: 348, 23: 483})])",MACs,8066.631168,top1_acc,-91.1847637892654 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,6315.31264,top1_acc,-91.1847637892654 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 2452, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 197})])",MACs,7114.327552,top1_acc,-91.18723720009893 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 256, 7: 768, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2980, 20: 2100, 21: 1524, 22: 348, 23: 197})])",MACs,7333.152256,top1_acc,-91.26885975760574 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5463.410176,top1_acc,-91.00173138758348 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 3072, 15: 3007, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2936, 21: 762, 22: 3072, 23: 115})])",MACs,9123.071488,top1_acc,-91.3109077417759 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2452, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6856.050176,top1_acc,-91.16250309176354 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 768, 6: 448, 7: 768, 8: 64, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 115})])",MACs,6306.530816,top1_acc,-90.90774177590897 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 3072, 15: 3072, 16: 1772, 17: 3072, 18: 2452, 19: 2403, 20: 2100, 21: 1524, 22: 3072, 23: 483})])",MACs,8319.010304,top1_acc,-91.20702448676725 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 512, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7941.326336,top1_acc,-91.20207766510018 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 3072, 16: 2543, 17: 3072, 18: 2974, 19: 2980, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8751.089152,top1_acc,-91.24659906010389 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 768, 5: 768, 6: 192, 7: 384, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 115})])",MACs,8837.79328,top1_acc,-91.25401929260451 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7552.828928,top1_acc,-91.2416522384368 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 3072, 19: 2980, 20: 1320, 21: 1524, 22: 756, 23: 115})])",MACs,6328.681984,top1_acc,-91.17487014593124 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7300.777472,top1_acc,-91.2663863467722 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 64, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,5714.937344,top1_acc,-90.93000247341084 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 384, 4: 768, 5: 768, 6: 192, 7: 768, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 2543, 17: 2500, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,8278.967808,top1_acc,-91.21197130843434 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,4986.373632,top1_acc,-90.95226317091269 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 448, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 1524, 22: 348, 23: 197})])",MACs,6971.786752,top1_acc,-91.1476626267623 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5545.133568,top1_acc,-91.03388572841949 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,4998.170112,top1_acc,-91.01409844175117 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 384, 4: 512, 5: 512, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 768, 12: 1675, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 2721, 22: 1957, 23: 483})])",MACs,7517.701632,top1_acc,-91.09324758842445 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,8156.153344,top1_acc,-91.25896611427157 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 1791, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8099.464704,top1_acc,-91.15508285926293 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 756, 23: 115})])",MACs,6669.600256,top1_acc,-90.98194410091516 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6056.77312,top1_acc,-91.08582735592383 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 768, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,6474.827264,top1_acc,-91.10066782092505 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 384, 4: 256, 5: 256, 6: 192, 7: 768, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5775.230464,top1_acc,-90.98194410091516 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5853.677056,top1_acc,-91.15013603759584 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 768, 8: 64, 9: 192, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 3007, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 115})])",MACs,7401.375232,top1_acc,-91.08582735592383 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 448, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 1772, 17: 2982, 18: 2974, 19: 2980, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,8177.84576,top1_acc,-91.22433836260203 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5152.638464,top1_acc,-90.94978976007914 +"OrderedDict([(, {0: 448, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 2721, 22: 756, 23: 197})])",MACs,7354.254848,top1_acc,-91.04377937175366 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 448, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 1957, 23: 197})])",MACs,9335.145984,top1_acc,-91.3356418501113 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,4931.84768,top1_acc,-90.96957704674746 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 192, 10: 320, 11: 512, 12: 2460, 13: 1666, 14: 2530, 15: 3072, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7313.622528,top1_acc,-91.2292851842691 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3007, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2936, 21: 2721, 22: 3072, 23: 483})])",MACs,10184.164864,top1_acc,-91.37768983428147 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 448, 7: 384, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 115})])",MACs,7671.90784,top1_acc,-91.15260944842939 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 197})])",MACs,7985.628672,top1_acc,-91.23423200593619 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9756.93568,top1_acc,-91.4296314617858 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 3072, 15: 1791, 16: 3072, 17: 1751, 18: 3072, 19: 2980, 20: 2936, 21: 1524, 22: 756, 23: 115})])",MACs,7471.564288,top1_acc,-91.10561464259213 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3007, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2100, 21: 1524, 22: 348, 23: 197})])",MACs,8172.2752,top1_acc,-91.28122681177344 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,5345.183232,top1_acc,-91.03883255008657 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 448, 7: 768, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9029.092864,top1_acc,-91.28864704427406 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9231.99232,top1_acc,-91.26885975760574 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2452, 19: 2980, 20: 1320, 21: 1524, 22: 1957, 23: 197})])",MACs,8257.930752,top1_acc,-91.26391293593866 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 192, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 1957, 23: 483})])",MACs,8481.146368,top1_acc,-91.14271580509524 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 1772, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6344.279552,top1_acc,-90.90032154340835 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5313.332736,top1_acc,-91.0784071234232 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9773.64736,top1_acc,-91.38511006678209 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 756, 23: 115})])",MACs,6030.296576,top1_acc,-91.04625278258719 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,6456.608256,top1_acc,-91.13282216176107 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 384, 4: 768, 5: 512, 6: 192, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 2721, 22: 348, 23: 197})])",MACs,7146.112512,top1_acc,-91.09819441009151 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,7147.423232,top1_acc,-91.21939154093495 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 2488, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5706.745344,top1_acc,-90.98689092258225 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 1320, 21: 2721, 22: 3072, 23: 197})])",MACs,8517.32224,top1_acc,-91.28864704427406 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2452, 19: 2980, 20: 2936, 21: 2721, 22: 1957, 23: 197})])",MACs,8974.566912,top1_acc,-91.348008904279 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,4698.277376,top1_acc,-90.94978976007914 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7438.468608,top1_acc,-91.17734355676478 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 448, 7: 768, 8: 192, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3024, 14: 2530, 15: 1791, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,7935.428096,top1_acc,-91.17734355676478 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 756, 23: 115})])",MACs,6591.088128,top1_acc,-91.17981696759831 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 3072, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 3072, 23: 115})])",MACs,7937.066496,top1_acc,-91.20949789760078 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 512, 5: 256, 6: 768, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,6230.574592,top1_acc,-91.09819441009151 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 197})])",MACs,5692.982784,top1_acc,-90.94731634924561 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5947.98336,top1_acc,-91.0091516200841 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 256, 5: 256, 6: 448, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 2543, 17: 1751, 18: 2974, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 115})])",MACs,6970.541568,top1_acc,-91.04872619342072 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 384, 4: 256, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2980, 20: 2100, 21: 2721, 22: 348, 23: 483})])",MACs,7119.76704,top1_acc,-91.09324758842445 +"OrderedDict([(, {0: 384, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 768, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 2721, 22: 348, 23: 197})])",MACs,6477.972992,top1_acc,-91.12045510759337 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6642.33728,top1_acc,-91.0784071234232 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 768, 9: 192, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3007, 16: 2543, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 115})])",MACs,8609.531392,top1_acc,-91.25896611427157 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 256, 6: 448, 7: 384, 8: 192, 9: 192, 10: 320, 11: 512, 12: 1675, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,6569.461248,top1_acc,-91.13529557259461 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,5738.792448,top1_acc,-91.09572099925798 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 384, 4: 512, 5: 768, 6: 768, 7: 768, 8: 768, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 3072, 15: 3007, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 483})])",MACs,9249.03168,top1_acc,-91.32822161761068 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 768, 8: 64, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 1772, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 348, 23: 197})])",MACs,7617.316352,top1_acc,-91.10066782092505 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,4861.855232,top1_acc,-90.96215681424684 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 192, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 3072, 19: 2980, 20: 2936, 21: 2721, 22: 756, 23: 115})])",MACs,7865.23904,top1_acc,-91.09324758842445 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 2452, 19: 2403, 20: 2100, 21: 762, 22: 1957, 23: 197})])",MACs,7471.498752,top1_acc,-91.21939154093495 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 256, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 348, 23: 115})])",MACs,7145.457152,top1_acc,-91.13776898342815 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7191.725568,top1_acc,-91.12045510759337 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,6560.679424,top1_acc,-91.127875340094 +"OrderedDict([(, {0: 448, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 192, 7: 384, 8: 64, 9: 192, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 3072, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,6485.247488,top1_acc,-90.9844175117487 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,9373.55008,top1_acc,-91.35542913677962 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 115})])",MACs,7134.774784,top1_acc,-91.15260944842939 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 348, 23: 483})])",MACs,6720.062976,top1_acc,-90.9967845659164 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9773.64736,top1_acc,-91.38511006678209 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 197})])",MACs,7295.141376,top1_acc,-91.15508285926293 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5285.873152,top1_acc,-90.97699727924808 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,5251.401216,top1_acc,-91.01904526341825 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 256, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2452, 19: 2980, 20: 1320, 21: 1524, 22: 1957, 23: 197})])",MACs,7438.009856,top1_acc,-91.19960425426663 +"OrderedDict([(, {0: 384, 1: 768, 2: 448, 3: 192, 4: 768, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2980, 20: 1320, 21: 1524, 22: 348, 23: 197})])",MACs,7113.082368,top1_acc,-91.20455107593372 +"OrderedDict([(, {0: 384, 1: 768, 2: 448, 3: 192, 4: 512, 5: 512, 6: 192, 7: 384, 8: 192, 9: 512, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 197})])",MACs,6757.746176,top1_acc,-91.15013603759584 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5378.8032,top1_acc,-90.9844175117487 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8047.42912,top1_acc,-91.2169181301014 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 1772, 17: 1751, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 348, 23: 197})])",MACs,7831.946752,top1_acc,-91.09077417759089 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 483})])",MACs,6447.629824,top1_acc,-91.11798169675983 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 448, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 3072, 15: 3072, 16: 1772, 17: 3072, 18: 1709, 19: 2403, 20: 1320, 21: 2721, 22: 348, 23: 197})])",MACs,7417.759232,top1_acc,-90.98689092258225 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 768, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,7744.587264,top1_acc,-91.127875340094 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,6456.608256,top1_acc,-91.13282216176107 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 512, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,5619.910144,top1_acc,-90.99431115508287 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6897.075712,top1_acc,-91.23423200593619 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 1772, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6150.555136,top1_acc,-91.05861983675489 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 768, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,6975.653376,top1_acc,-91.14024239426169 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,9710.142976,top1_acc,-91.39995053178332 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 512, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 3072, 15: 3072, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,8568.44032,top1_acc,-91.28864704427406 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5544.216064,top1_acc,-91.05119960425426 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 2721, 22: 3072, 23: 197})])",MACs,9141.421568,top1_acc,-91.37521642344794 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,6309.021184,top1_acc,-91.12292851842692 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5651.170816,top1_acc,-91.06604006925551 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9511.568896,top1_acc,-91.38758347761564 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 2530, 15: 1791, 16: 3072, 17: 3072, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 483})])",MACs,8911.717888,top1_acc,-91.25401929260451 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5218.305536,top1_acc,-91.05119960425426 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2936, 21: 762, 22: 348, 23: 197})])",MACs,7431.980544,top1_acc,-91.1971308434331 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 197})])",MACs,7376.930304,top1_acc,-91.23175859510265 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6849.824256,top1_acc,-91.17981696759831 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 2543, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,8669.758976,top1_acc,-91.25154588177095 +"OrderedDict([(, {0: 448, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5543.429632,top1_acc,-90.90526836507544 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,6621.431296,top1_acc,-91.06851348008904 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 192, 7: 384, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2500, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 348, 23: 483})])",MACs,8147.437056,top1_acc,-91.26143952510512 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 384, 4: 512, 5: 256, 6: 768, 7: 768, 8: 192, 9: 192, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 3072, 15: 3007, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 483})])",MACs,7808.026112,top1_acc,-91.10066782092505 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 64, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 1751, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7263.094272,top1_acc,-91.09819441009151 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 2452, 19: 2980, 20: 2936, 21: 2721, 22: 3072, 23: 483})])",MACs,9921.037824,top1_acc,-91.38758347761564 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,7209.944576,top1_acc,-91.22433836260203 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 1524, 22: 1957, 23: 483})])",MACs,9310.569984,top1_acc,-91.38758347761564 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 3072, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5503.256064,top1_acc,-91.06851348008904 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 192, 7: 384, 8: 384, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6335.497728,top1_acc,-91.19960425426663 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,6210.12736,top1_acc,-91.127875340094 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 384, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 197})])",MACs,9152.628224,top1_acc,-91.23423200593619 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 3072, 16: 2543, 17: 1751, 18: 1709, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,7720.273408,top1_acc,-91.16250309176354 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6024.66048,top1_acc,-91.04625278258719 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 1791, 16: 2543, 17: 3072, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,7666.271744,top1_acc,-91.11798169675983 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 768, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2936, 21: 2721, 22: 756, 23: 115})])",MACs,6632.83456,top1_acc,-91.09077417759089 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 384, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5267.457536,top1_acc,-90.96957704674746 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5955.19232,top1_acc,-91.16497650259709 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 1957, 23: 197})])",MACs,8819.901952,top1_acc,-91.27380657927282 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,6338.971136,top1_acc,-91.19465743259956 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 3072, 18: 2452, 19: 2980, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,8976.139776,top1_acc,-91.32822161761068 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5810.226688,top1_acc,-91.08335394509028 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,6380.586496,top1_acc,-91.16002968093 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 768, 12: 1675, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2452, 19: 2980, 20: 2936, 21: 2721, 22: 1957, 23: 197})])",MACs,8618.116608,top1_acc,-91.25154588177095 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 384, 4: 512, 5: 768, 6: 448, 7: 768, 8: 768, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 3072, 15: 3007, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 2721, 22: 3072, 23: 483})])",MACs,8857.650688,top1_acc,-91.27875340093989 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,6424.364544,top1_acc,-91.16992332426416 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5243.536896,top1_acc,-91.1105614642592 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 768, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 3072, 23: 197})])",MACs,7205.094912,top1_acc,-91.1155082859263 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 3072, 15: 1791, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 1320, 21: 1524, 22: 3072, 23: 115})])",MACs,7782.729216,top1_acc,-91.14271580509524 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 2721, 22: 756, 23: 115})])",MACs,6811.354624,top1_acc,-91.08582735592383 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5838.669312,top1_acc,-91.07346030175613 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,4972.938752,top1_acc,-90.98936433341578 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 512, 5: 512, 6: 768, 7: 768, 8: 384, 9: 192, 10: 320, 11: 512, 12: 1675, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,7241.532928,top1_acc,-91.16497650259709 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 2543, 17: 1751, 18: 1709, 19: 2403, 20: 2936, 21: 762, 22: 348, 23: 483})])",MACs,7287.5392,top1_acc,-91.13282216176107 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3007, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 348, 23: 197})])",MACs,7668.827648,top1_acc,-91.25401929260451 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 3007, 16: 2543, 17: 3072, 18: 2974, 19: 2980, 20: 1320, 21: 2721, 22: 756, 23: 115})])",MACs,7568.623104,top1_acc,-91.20949789760078 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,6185.22368,top1_acc,-91.15260944842939 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3007, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 1320, 21: 2721, 22: 348, 23: 197})])",MACs,8090.68288,top1_acc,-91.25649270343804 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 192, 7: 768, 8: 192, 9: 768, 10: 320, 11: 512, 12: 1675, 13: 3024, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8406.89408,top1_acc,-91.1476626267623 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,4860.282368,top1_acc,-91.03388572841949 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5993.661952,top1_acc,-91.10066782092505 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 483})])",MACs,9424.0128,top1_acc,-91.41231758595103 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 3072, 15: 3007, 16: 2543, 17: 2982, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 3072, 23: 197})])",MACs,8176.20736,top1_acc,-91.25896611427157 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6308.10368,top1_acc,-91.12292851842692 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2452, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,8845.00224,top1_acc,-91.3232747959436 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2936, 21: 762, 22: 3072, 23: 115})])",MACs,8976.07424,top1_acc,-91.30101409844174 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,9224.062464,top1_acc,-91.2663863467722 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 768, 7: 384, 8: 768, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 1751, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 348, 23: 197})])",MACs,7696.549376,top1_acc,-91.09324758842445 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2500, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6168.577536,top1_acc,-90.9844175117487 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5298.5216,top1_acc,-91.03141231758595 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9317.5168,top1_acc,-91.34058867177838 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 2530, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6778.97984,top1_acc,-91.18971061093248 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 3072, 23: 197})])",MACs,8913.683968,top1_acc,-91.3034875092753 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 3024, 14: 3072, 15: 3072, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 115})])",MACs,8081.376768,top1_acc,-91.08582735592383 +"OrderedDict([(, {0: 384, 1: 768, 2: 448, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 384, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 756, 23: 197})])",MACs,7187.531264,top1_acc,-91.13529557259461 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5531.239936,top1_acc,-91.08088053425674 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 768, 5: 256, 6: 448, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3007, 16: 1772, 17: 2982, 18: 2452, 19: 2403, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,7271.745024,top1_acc,-91.12045510759337 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6783.632896,top1_acc,-91.15508285926293 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3024, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 2721, 22: 756, 23: 115})])",MACs,6704.006656,top1_acc,-91.10066782092505 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8157.988352,top1_acc,-91.32822161761068 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5007.54176,top1_acc,-90.96463022508038 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 768, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 1524, 22: 756, 23: 483})])",MACs,5982.127616,top1_acc,-90.9967845659164 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6990.33344,top1_acc,-91.23423200593619 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 192, 7: 768, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 1772, 17: 3072, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,6375.27808,top1_acc,-90.93742270591146 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5606.475264,top1_acc,-91.01904526341825 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,4780.066304,top1_acc,-91.00173138758348 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 3072, 16: 3072, 17: 3072, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8850.703872,top1_acc,-91.33069502844423 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 768, 12: 1675, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,7091.848704,top1_acc,-91.16497650259709 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 348, 23: 115})])",MACs,7356.941824,top1_acc,-91.20455107593372 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 483})])",MACs,6264.784384,top1_acc,-91.01409844175117 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2452, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,7071.59808,top1_acc,-91.16744991343062 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6243.812864,top1_acc,-91.06604006925551 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 512, 5: 768, 6: 192, 7: 768, 8: 768, 9: 192, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 348, 23: 483})])",MACs,7524.517376,top1_acc,-91.11798169675983 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5078.386176,top1_acc,-91.03635913925304 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 64, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2403, 20: 1320, 21: 1524, 22: 3072, 23: 483})])",MACs,8144.684544,top1_acc,-91.09819441009151 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 115})])",MACs,8567.916032,top1_acc,-91.28370022260698 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5356.979712,top1_acc,-91.14518921592877 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 768, 5: 768, 6: 192, 7: 768, 8: 768, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 348, 23: 115})])",MACs,6483.543552,top1_acc,-91.00173138758348 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 3072, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5285.152256,top1_acc,-90.92010883007667 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 1751, 18: 2452, 19: 2980, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,8389.264896,top1_acc,-91.28122681177344 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 768, 8: 384, 9: 192, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 2530, 15: 1791, 16: 2543, 17: 1751, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,6147.147264,top1_acc,-91.06356665842196 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 2530, 15: 3007, 16: 2543, 17: 2982, 18: 2974, 19: 2980, 20: 2100, 21: 1524, 22: 3072, 23: 197})])",MACs,8826.390016,top1_acc,-91.27133316843927 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 3072, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5589.435904,top1_acc,-90.95968340341331 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 3072, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6749.81632,top1_acc,-91.11303487509275 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6277.30176,top1_acc,-91.25401929260451 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,6549.669376,top1_acc,-91.12540192926045 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 1751, 18: 3072, 19: 2403, 20: 1320, 21: 1524, 22: 1957, 23: 483})])",MACs,8424.457728,top1_acc,-91.22681177343557 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 1751, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 348, 23: 115})])",MACs,6244.468224,top1_acc,-91.03635913925304 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6959.793664,top1_acc,-91.18723720009893 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 768, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2982, 18: 2452, 19: 2980, 20: 2100, 21: 2721, 22: 1957, 23: 197})])",MACs,8529.839616,top1_acc,-91.25649270343804 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 483})])",MACs,7625.37728,top1_acc,-91.12045510759337 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 512, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2936, 21: 1524, 22: 3072, 23: 115})])",MACs,8764.327424,top1_acc,-91.35790254761315 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6122.571264,top1_acc,-91.14271580509524 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 512, 12: 1675, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 483})])",MACs,7648.118272,top1_acc,-91.07346030175613 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 192, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5270.799872,top1_acc,-90.94484293841208 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 1791, 16: 3072, 17: 2500, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 483})])",MACs,7956.923904,top1_acc,-91.25896611427157 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 1787, 15: 3072, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,7446.529536,top1_acc,-91.11303487509275 +"OrderedDict([(, {0: 320, 1: 256, 2: 448, 3: 192, 4: 768, 5: 512, 6: 448, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2452, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,7027.754496,top1_acc,-91.06604006925551 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5424.154112,top1_acc,-91.04872619342072 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8165.131776,top1_acc,-91.29606727677468 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 3072, 19: 2980, 20: 1320, 21: 1524, 22: 756, 23: 115})])",MACs,6006.572544,top1_acc,-91.10066782092505 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6201.083392,top1_acc,-91.13776898342815 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6129.649152,top1_acc,-90.97699727924808 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,6693.586432,top1_acc,-91.06109324758842 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,6827.673088,top1_acc,-91.1476626267623 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 512, 5: 768, 6: 448, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2452, 19: 2980, 20: 2936, 21: 1524, 22: 1957, 23: 197})])",MACs,8466.597376,top1_acc,-91.29112045510759 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 768, 9: 192, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 1772, 17: 2982, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,7016.941056,top1_acc,-91.07593371258966 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 192, 7: 768, 8: 768, 9: 192, 10: 320, 11: 768, 12: 1675, 13: 1666, 14: 3072, 15: 1791, 16: 2543, 17: 3072, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 483})])",MACs,7328.105984,top1_acc,-91.07593371258966 +"OrderedDict([(, {0: 384, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,7369.4592,top1_acc,-91.16250309176354 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 768, 9: 192, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 115})])",MACs,7361.791488,top1_acc,-91.11798169675983 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9238.939136,top1_acc,-91.29112045510759 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 1524, 22: 1957, 23: 115})])",MACs,8250.721792,top1_acc,-91.23423200593619 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,6449.530368,top1_acc,-91.07346030175613 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 384, 9: 512, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,6450.97216,top1_acc,-91.20207766510018 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 1957, 23: 197})])",MACs,6093.407744,top1_acc,-91.01657185258472 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 2721, 22: 3072, 23: 115})])",MACs,8596.358656,top1_acc,-91.31832797427653 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6380.914176,top1_acc,-90.98689092258225 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 512, 6: 192, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 2974, 19: 2403, 20: 1320, 21: 2721, 22: 348, 23: 197})])",MACs,7292.12672,top1_acc,-91.20207766510018 +"OrderedDict([(, {0: 448, 1: 256, 2: 448, 3: 192, 4: 768, 5: 256, 6: 448, 7: 384, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 3007, 16: 1772, 17: 2982, 18: 2452, 19: 2980, 20: 1320, 21: 1524, 22: 348, 23: 115})])",MACs,6708.52864,top1_acc,-91.01162503091763 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 3007, 16: 2543, 17: 2500, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7442.138624,top1_acc,-91.16002968093 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 2543, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9362.474496,top1_acc,-91.3034875092753 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5436.409344,top1_acc,-91.03141231758595 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6059.197952,top1_acc,-91.16992332426416 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 483})])",MACs,9061.139968,top1_acc,-91.35542913677962 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6464.210432,top1_acc,-91.13529557259461 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 512, 5: 512, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2936, 21: 762, 22: 1957, 23: 115})])",MACs,7335.642624,top1_acc,-91.18971061093248 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 3072, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5624.956416,top1_acc,-91.0784071234232 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 512, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 197})])",MACs,7876.576768,top1_acc,-91.27380657927282 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6091.5072,top1_acc,-91.12540192926045 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 1675, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,7882.475008,top1_acc,-91.1476626267623 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 768, 5: 768, 6: 192, 7: 768, 8: 64, 9: 768, 10: 192, 11: 768, 12: 1675, 13: 3024, 14: 3072, 15: 1791, 16: 1772, 17: 3072, 18: 3072, 19: 2403, 20: 1320, 21: 1524, 22: 348, 23: 483})])",MACs,7112.820224,top1_acc,-90.91268859757605 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6316.164608,top1_acc,-91.15013603759584 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5811.144192,top1_acc,-91.127875340094 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8561.88672,top1_acc,-91.35295572594609 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5025.433088,top1_acc,-91.12045510759337 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6173.296128,top1_acc,-91.21197130843434 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 1524, 22: 348, 23: 197})])",MACs,6485.444096,top1_acc,-91.10066782092505 +"OrderedDict([(, {0: 384, 1: 256, 2: 448, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 512, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 2721, 22: 348, 23: 197})])",MACs,5743.642112,top1_acc,-91.00667820925055 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 512, 5: 512, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 3072, 23: 115})])",MACs,7998.735872,top1_acc,-91.24412564927034 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6629.099008,top1_acc,-91.22433836260203 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,7147.423232,top1_acc,-91.21939154093495 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 512, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 2452, 19: 2980, 20: 2936, 21: 2721, 22: 1957, 23: 197})])",MACs,8870.56128,top1_acc,-91.31832797427653 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6095.308288,top1_acc,-91.10066782092505 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 512, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 2530, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,5988.353536,top1_acc,-90.96215681424684 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 768, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 115})])",MACs,7342.392832,top1_acc,-91.17734355676478 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 2530, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,6873.089536,top1_acc,-91.02646549591887 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5657.98656,top1_acc,-91.12045510759337 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 512, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 3072, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,8575.3216,top1_acc,-91.25896611427157 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 2530, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,6186.86208,top1_acc,-91.00420479841702 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 256, 7: 768, 8: 384, 9: 512, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2980, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,8087.602688,top1_acc,-91.20702448676725 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9870.378496,top1_acc,-91.41973781845164 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5507.515904,top1_acc,-91.00173138758348 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 512, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,7912.228352,top1_acc,-91.28617363344051 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 2974, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,7429.228032,top1_acc,-91.1155082859263 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7403.53792,top1_acc,-91.25401929260451 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7023.035904,top1_acc,-90.96215681424684 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6759.843328,top1_acc,-91.18229037843186 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6414.534144,top1_acc,-91.23175859510265 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 192, 9: 192, 10: 320, 11: 768, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 3072, 23: 115})])",MACs,7938.63936,top1_acc,-91.15260944842939 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 512, 5: 512, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,6463.686144,top1_acc,-91.13282216176107 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9879.81568,top1_acc,-91.39747712094979 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5730.928128,top1_acc,-91.13776898342815 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7805.011456,top1_acc,-91.25649270343804 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 768, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3024, 14: 3072, 15: 3072, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2936, 21: 762, 22: 3072, 23: 115})])",MACs,7663.322624,top1_acc,-91.05119960425426 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 512, 5: 512, 6: 768, 7: 384, 8: 384, 9: 192, 10: 192, 11: 768, 12: 1675, 13: 3024, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 3072, 19: 2980, 20: 2936, 21: 1524, 22: 3072, 23: 115})])",MACs,7736.854016,top1_acc,-91.10808805342567 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,4969.334272,top1_acc,-90.99925797674993 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 3072, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5751.768576,top1_acc,-90.9844175117487 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5210.441216,top1_acc,-91.03635913925304 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6759.843328,top1_acc,-91.18229037843186 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7448.364544,top1_acc,-91.24907247093742 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6158.943744,top1_acc,-91.1155082859263 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,8302.822912,top1_acc,-91.21939154093495 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5571.80672,top1_acc,-91.127875340094 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5025.433088,top1_acc,-90.99183774424931 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 1320, 21: 1524, 22: 348, 23: 483})])",MACs,7450.592768,top1_acc,-91.14024239426169 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5725.750784,top1_acc,-90.99925797674993 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5744.625152,top1_acc,-91.1155082859263 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 1772, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,8785.233408,top1_acc,-91.30843433094236 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 115})])",MACs,7969.506816,top1_acc,-91.25154588177095 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6025.709056,top1_acc,-91.13282216176107 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5253.760512,top1_acc,-91.09324758842445 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 256, 7: 768, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 1524, 22: 348, 23: 197})])",MACs,7219.70944,top1_acc,-91.22186495176848 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 768, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 483})])",MACs,5538.38336,top1_acc,-91.1031412317586 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 2530, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9496.233472,top1_acc,-91.35790254761315 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 3007, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 2721, 22: 3072, 23: 197})])",MACs,9195.94752,top1_acc,-91.36284936928024 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2980, 20: 1320, 21: 1524, 22: 348, 23: 483})])",MACs,8122.074624,top1_acc,-91.16250309176354 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,7032.997376,top1_acc,-91.13776898342815 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 348, 23: 197})])",MACs,7866.287616,top1_acc,-91.26885975760574 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6422.464,top1_acc,-91.16250309176354 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 768, 9: 192, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 483})])",MACs,8243.05408,top1_acc,-91.25401929260451 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 483})])",MACs,7432.898048,top1_acc,-91.20949789760078 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,9111.40608,top1_acc,-91.28370022260698 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 256, 7: 768, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2980, 20: 2100, 21: 1524, 22: 348, 23: 197})])",MACs,7278.626304,top1_acc,-91.23423200593619 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8025.605632,top1_acc,-91.28864704427406 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5395.973632,top1_acc,-91.06604006925551 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 197})])",MACs,7836.337664,top1_acc,-91.26143952510512 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 1666, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 115})])",MACs,7824.344576,top1_acc,-91.29606727677468 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 768, 5: 768, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 1524, 22: 1957, 23: 115})])",MACs,6041.241088,top1_acc,-90.90774177590897 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 115})])",MACs,8975.74656,top1_acc,-91.31585456344298 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7501.317632,top1_acc,-91.25401929260451 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5102.306816,top1_acc,-90.92258224091022 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6158.943744,top1_acc,-91.1155082859263 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 768, 9: 192, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 1791, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 1320, 21: 1524, 22: 348, 23: 483})])",MACs,7506.75712,top1_acc,-91.16744991343062 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 2530, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 197})])",MACs,8489.076224,top1_acc,-91.30101409844174 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 768, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 2543, 17: 1751, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 348, 23: 115})])",MACs,5913.511424,top1_acc,-91.00667820925055 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6326.650368,top1_acc,-91.18971061093248 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 1957, 23: 483})])",MACs,5979.571712,top1_acc,-90.95473658174623 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8429.110784,top1_acc,-91.3034875092753 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 3072, 18: 2974, 19: 2980, 20: 1320, 21: 1524, 22: 1957, 23: 115})])",MACs,6810.306048,top1_acc,-91.08582735592383 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 1590, 20: 2100, 21: 2721, 22: 348, 23: 115})])",MACs,8230.209024,top1_acc,-91.27875340093989 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5163.976192,top1_acc,-91.0215186742518 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,7994.410496,top1_acc,-91.25896611427157 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7995.852288,top1_acc,-91.28370022260698 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6035.277312,top1_acc,-91.16002968093 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5986.518528,top1_acc,-91.15013603759584 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 64, 9: 768, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 115})])",MACs,6948.455936,top1_acc,-90.91268859757605 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6738.806272,top1_acc,-91.22681177343557 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7024.543232,top1_acc,-91.04377937175366 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6743.721472,top1_acc,-91.16992332426416 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 192, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 1791, 16: 3072, 17: 1751, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 348, 23: 115})])",MACs,8296.072704,top1_acc,-91.19465743259956 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5544.543744,top1_acc,-91.1476626267623 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 483})])",MACs,8929.019392,top1_acc,-91.39253029928271 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3024, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,6175.655424,top1_acc,-91.127875340094 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5818.87744,top1_acc,-91.16992332426416 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6336.873984,top1_acc,-91.15260944842939 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 2530, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8926.070272,top1_acc,-91.35048231511253 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7837.976064,top1_acc,-91.3034875092753 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5323.75296,top1_acc,-91.0784071234232 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6842.54976,top1_acc,-91.17734355676478 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 512, 5: 512, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,6429.541888,top1_acc,-91.17487014593124 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7468.09088,top1_acc,-91.16002968093 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5740.103168,top1_acc,-91.10808805342567 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7458.063872,top1_acc,-91.26885975760574 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7147.357696,top1_acc,-91.09819441009151 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6930.236928,top1_acc,-91.17487014593124 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 2530, 15: 3072, 16: 3072, 17: 3072, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8998.290944,top1_acc,-91.33316843927777 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 256, 7: 384, 8: 192, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2980, 20: 1320, 21: 1524, 22: 348, 23: 197})])",MACs,6576.211456,top1_acc,-91.11798169675983 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6266.947072,top1_acc,-91.16002968093 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2936, 21: 762, 22: 348, 23: 483})])",MACs,6078.334464,top1_acc,-90.98194410091516 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 1675, 13: 3024, 14: 3072, 15: 1791, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 3072, 23: 115})])",MACs,8725.464576,top1_acc,-91.21197130843434 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 192, 7: 768, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,7628.457472,top1_acc,-91.13034875092752 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,5856.101888,top1_acc,-91.06604006925551 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6393.366016,top1_acc,-91.13034875092752 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,6499.206656,top1_acc,-91.08830076675736 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2980, 20: 2100, 21: 2721, 22: 3072, 23: 197})])",MACs,8567.522816,top1_acc,-91.25154588177095 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 2460, 13: 3072, 14: 2530, 15: 3072, 16: 3072, 17: 3072, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8959.755776,top1_acc,-91.32574820677715 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 483})])",MACs,9028.634112,top1_acc,-91.38511006678209 +"OrderedDict([(, {0: 448, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 192, 7: 768, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 756, 23: 197})])",MACs,7069.107712,top1_acc,-91.14024239426169 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 192, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 3072, 19: 2980, 20: 2936, 21: 762, 22: 3072, 23: 115})])",MACs,7843.415552,top1_acc,-91.13282216176107 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 1320, 21: 1524, 22: 1957, 23: 483})])",MACs,7097.288192,top1_acc,-91.15013603759584 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 483})])",MACs,8676.378112,top1_acc,-91.38758347761564 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5722.080768,top1_acc,-91.10561464259213 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8316.519936,top1_acc,-91.32080138511006 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3024, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 1524, 22: 3072, 23: 197})])",MACs,8245.282304,top1_acc,-91.2292851842691 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 384, 9: 768, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5631.706624,top1_acc,-91.07098689092258 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5054.72768,top1_acc,-90.94236952757852 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 384, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5747.246592,top1_acc,-91.06604006925551 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 192, 7: 768, 8: 384, 9: 192, 10: 320, 11: 512, 12: 2460, 13: 1666, 14: 2530, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,6193.350144,top1_acc,-91.03635913925304 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 256, 7: 768, 8: 384, 9: 512, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 348, 23: 115})])",MACs,7361.988096,top1_acc,-91.24412564927034 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 483})])",MACs,9314.960896,top1_acc,-91.44694533762058 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9657.32096,top1_acc,-91.42715805095226 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 384, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 1787, 15: 3072, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,6252.856832,top1_acc,-91.06109324758842 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 320, 11: 512, 12: 1675, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 1709, 19: 2980, 20: 1320, 21: 1524, 22: 756, 23: 483})])",MACs,7218.791936,top1_acc,-91.08582735592383 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 192, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,7187.006976,top1_acc,-91.09077417759089 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6667.175424,top1_acc,-91.24412564927034 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5041.554944,top1_acc,-91.10808805342567 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5602.346496,top1_acc,-91.14518921592877 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 483})])",MACs,9343.927808,top1_acc,-91.32080138511006 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 1524, 22: 1957, 23: 483})])",MACs,9301.1328,top1_acc,-91.37521642344794 +"OrderedDict([(, {0: 448, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 768, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5545.657856,top1_acc,-91.03388572841949 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 2488, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6488.262144,top1_acc,-91.15013603759584 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 2721, 22: 3072, 23: 115})])",MACs,8214.676992,top1_acc,-91.23175859510265 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 384, 9: 192, 10: 320, 11: 512, 12: 1675, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 1709, 19: 2980, 20: 2936, 21: 762, 22: 348, 23: 197})])",MACs,6582.306304,top1_acc,-91.10808805342567 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 483})])",MACs,6804.276736,top1_acc,-91.19218402176602 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,4974.708224,top1_acc,-90.88300766757358 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 2543, 17: 3072, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6315.64032,top1_acc,-91.10808805342567 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 2530, 15: 3072, 16: 1772, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,7176.521216,top1_acc,-91.14518921592877 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,8783.595008,top1_acc,-91.29606727677468 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,4887.545344,top1_acc,-91.00173138758348 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 384, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,7103.579648,top1_acc,-91.1155082859263 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 192, 7: 384, 8: 768, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 1751, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 483})])",MACs,7045.907968,top1_acc,-91.09324758842445 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 768, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 348, 23: 483})])",MACs,8327.333376,top1_acc,-91.20949789760078 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2500, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6199.576064,top1_acc,-91.11303487509275 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2980, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,8074.823168,top1_acc,-91.20455107593372 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6797.395456,top1_acc,-91.17981696759831 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 1751, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6654.658048,top1_acc,-91.09324758842445 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7725.64736,top1_acc,-91.16250309176354 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,5816.518144,top1_acc,-91.06604006925551 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5480.71168,top1_acc,-91.00173138758348 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7859.537408,top1_acc,-91.25649270343804 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5713.167872,top1_acc,-91.13529557259461 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 483})])",MACs,8191.477248,top1_acc,-91.25896611427157 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,6494.750208,top1_acc,-91.21197130843434 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 1524, 22: 348, 23: 115})])",MACs,6967.330304,top1_acc,-91.05614642592134 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 256, 6: 192, 7: 768, 8: 64, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 3024, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 115})])",MACs,6281.23392,top1_acc,-90.97699727924808 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 1751, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6645.745152,top1_acc,-91.13529557259461 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 768, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 3072, 15: 3072, 16: 1772, 17: 3072, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,7039.092224,top1_acc,-91.18229037843186 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6261.179904,top1_acc,-91.26391293593866 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 483})])",MACs,8458.274304,top1_acc,-91.32574820677715 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5447.157248,top1_acc,-90.94978976007914 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6375.998976,top1_acc,-91.20702448676725 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5485.561344,top1_acc,-91.06109324758842 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5189.797376,top1_acc,-91.00667820925055 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6639.912448,top1_acc,-91.2416522384368 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5501.6832,top1_acc,-91.06604006925551 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,5345.183232,top1_acc,-91.03883255008657 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9739.24096,top1_acc,-91.39995053178332 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 483})])",MACs,7360.61184,top1_acc,-91.14024239426169 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7273.514496,top1_acc,-91.1723967350977 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,4943.64416,top1_acc,-91.03141231758595 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 3072, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7849.969152,top1_acc,-91.24907247093742 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 197})])",MACs,6609.962496,top1_acc,-91.09324758842445 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5270.799872,top1_acc,-91.14518921592877 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7679.968768,top1_acc,-91.19218402176602 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 483})])",MACs,8878.75328,top1_acc,-91.32574820677715 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8779.990528,top1_acc,-91.34553549344547 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 512, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8512.40704,top1_acc,-91.27133316843927 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6429.607424,top1_acc,-91.22186495176848 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5461.640704,top1_acc,-91.10808805342567 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6203.704832,top1_acc,-91.14271580509524 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 2936, 21: 762, 22: 348, 23: 483})])",MACs,7299.925504,top1_acc,-91.13529557259461 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 768, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 483})])",MACs,5677.581824,top1_acc,-91.02893890675242 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2980, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8683.324928,top1_acc,-91.27133316843927 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 115})])",MACs,6871.647744,top1_acc,-91.10561464259213 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7963.54304,top1_acc,-91.21939154093495 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,5446.501888,top1_acc,-90.95226317091269 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6157.174272,top1_acc,-91.18723720009893 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 192, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6348.08064,top1_acc,-91.07593371258966 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 512, 5: 512, 6: 768, 7: 384, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2980, 20: 2936, 21: 1524, 22: 3072, 23: 115})])",MACs,8799.585792,top1_acc,-91.33069502844423 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2936, 21: 762, 22: 756, 23: 483})])",MACs,9192.9984,top1_acc,-91.38263665594856 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6021.71136,top1_acc,-91.10561464259213 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 2452, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,8686.929408,top1_acc,-91.3603759584467 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 768, 8: 768, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 3072, 15: 3072, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 1524, 22: 1957, 23: 115})])",MACs,6753.027584,top1_acc,-91.00420479841702 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 2500, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7352.026624,top1_acc,-91.14271580509524 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 3072, 16: 2543, 17: 3072, 18: 3072, 19: 2403, 20: 1320, 21: 1524, 22: 3072, 23: 197})])",MACs,8275.887616,top1_acc,-91.29112045510759 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,8540.849664,top1_acc,-91.25649270343804 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 1320, 21: 1524, 22: 348, 23: 483})])",MACs,7437.092352,top1_acc,-91.1476626267623 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 1791, 16: 3072, 17: 1751, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 348, 23: 483})])",MACs,7386.957312,top1_acc,-91.0784071234232 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 1666, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 115})])",MACs,7693.075968,top1_acc,-91.21197130843434 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5025.433088,top1_acc,-91.01904526341825 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5258.806784,top1_acc,-91.06109324758842 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,6264.260096,top1_acc,-91.0413059609201 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 115})])",MACs,7789.086208,top1_acc,-91.25649270343804 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 3072, 23: 483})])",MACs,9606.399488,top1_acc,-91.44941874845412 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5011.867136,top1_acc,-90.972050457581 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 483})])",MACs,6745.818624,top1_acc,-91.11798169675983 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 483})])",MACs,7413.564928,top1_acc,-91.19218402176602 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8728.741376,top1_acc,-91.30596092010883 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 483})])",MACs,8324.122112,top1_acc,-91.25154588177095 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,7176.717824,top1_acc,-91.1847637892654 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,4943.64416,top1_acc,-90.97947069008163 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7543.1296,top1_acc,-91.24659906010389 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 483})])",MACs,9435.284992,top1_acc,-91.348008904279 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2980, 20: 1320, 21: 1524, 22: 348, 23: 115})])",MACs,7807.436288,top1_acc,-91.15260944842939 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 483})])",MACs,7925.597696,top1_acc,-91.26143952510512 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5111.612928,top1_acc,-91.1155082859263 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6034.949632,top1_acc,-91.20207766510018 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,8191.804928,top1_acc,-91.33316843927777 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6342.968832,top1_acc,-91.30101409844174 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7376.274944,top1_acc,-91.15260944842939 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 2500, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6409.225728,top1_acc,-91.00420479841702 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 348, 23: 115})])",MACs,6006.63808,top1_acc,-90.91763541924314 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6730.548736,top1_acc,-91.2416522384368 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 1957, 23: 115})])",MACs,8159.364608,top1_acc,-91.23175859510265 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 3072, 23: 197})])",MACs,8646.952448,top1_acc,-91.3109077417759 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 2974, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5733.811712,top1_acc,-91.02893890675242 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 192, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2936, 21: 762, 22: 348, 23: 197})])",MACs,7780.959744,top1_acc,-91.23423200593619 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5857.936896,top1_acc,-91.15755627009646 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2100, 21: 1524, 22: 3072, 23: 483})])",MACs,9329.378816,top1_acc,-91.35048231511253 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6744.57344,top1_acc,-91.19960425426663 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5671.552512,top1_acc,-91.05367301508781 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5786.568192,top1_acc,-91.15755627009646 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2936, 21: 762, 22: 3072, 23: 483})])",MACs,9712.305664,top1_acc,-91.39995053178332 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 2530, 15: 1791, 16: 2543, 17: 1751, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5743.18336,top1_acc,-90.93989611674499 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5352.5888,top1_acc,-91.08582735592383 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,7253.526016,top1_acc,-91.16992332426416 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,7371.0976,top1_acc,-91.1723967350977 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 1524, 22: 756, 23: 483})])",MACs,6015.878656,top1_acc,-90.97452386841455 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 384, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7507.543552,top1_acc,-91.28122681177344 +"OrderedDict([(, {0: 448, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 256, 7: 768, 8: 384, 9: 512, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 1524, 22: 348, 23: 197})])",MACs,6542.984704,top1_acc,-91.08830076675736 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 197})])",MACs,6599.804416,top1_acc,-91.10808805342567 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5533.992448,top1_acc,-91.01904526341825 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5057.086976,top1_acc,-90.9844175117487 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7370.704384,top1_acc,-91.27133316843927 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5337.253376,top1_acc,-91.03141231758595 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6100.944384,top1_acc,-91.18229037843186 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,7632.848384,top1_acc,-91.33316843927777 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,7100.696064,top1_acc,-91.21939154093495 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 1791, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 3072, 23: 483})])",MACs,8577.680896,top1_acc,-91.25649270343804 +"OrderedDict([(, {0: 448, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 256, 7: 768, 8: 384, 9: 512, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2980, 20: 2100, 21: 1524, 22: 756, 23: 197})])",MACs,8485.340672,top1_acc,-91.25896611427157 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 1666, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,8999.208448,top1_acc,-91.34553549344547 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 1524, 22: 348, 23: 197})])",MACs,7306.020352,top1_acc,-91.14271580509524 +"OrderedDict([(, {0: 384, 1: 768, 2: 448, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 2452, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7534.740992,top1_acc,-91.2292851842691 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 768, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6449.726976,top1_acc,-91.06109324758842 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 2530, 15: 1791, 16: 2543, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7395.542528,top1_acc,-91.27133316843927 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 64, 9: 768, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 3072, 15: 3072, 16: 1772, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,8005.48608,top1_acc,-91.10066782092505 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5758.912,top1_acc,-91.09324758842445 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 483})])",MACs,7097.4848,top1_acc,-91.12292851842692 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 1772, 17: 3072, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,8272.610816,top1_acc,-91.12045510759337 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 768, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6856.96768,top1_acc,-91.17487014593124 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5435.16416,top1_acc,-91.05861983675489 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 1524, 22: 756, 23: 197})])",MACs,8310.097408,top1_acc,-91.28617363344051 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 756, 23: 197})])",MACs,6470.96064,top1_acc,-91.24659906010389 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2936, 21: 1524, 22: 3072, 23: 197})])",MACs,9206.1056,top1_acc,-91.32080138511006 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5612.570112,top1_acc,-91.127875340094 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 1666, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 1524, 22: 1957, 23: 115})])",MACs,7992.313344,top1_acc,-91.22681177343557 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 1524, 22: 1957, 23: 483})])",MACs,8928.88832,top1_acc,-91.30101409844174 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 483})])",MACs,8797.685248,top1_acc,-91.32574820677715 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,7189.956096,top1_acc,-91.22433836260203 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 483})])",MACs,8164.214272,top1_acc,-91.28122681177344 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6368.72448,top1_acc,-91.28370022260698 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,4931.84768,top1_acc,-90.96957704674746 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9575.663104,top1_acc,-91.36779619094732 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5631.641088,top1_acc,-91.15260944842939 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5235.344896,top1_acc,-90.98936433341578 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 3072, 23: 483})])",MACs,8929.150464,top1_acc,-91.35048231511253 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 483})])",MACs,8482.719232,top1_acc,-91.33069502844423 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 1957, 23: 483})])",MACs,8779.79392,top1_acc,-91.34306208261192 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 762, 22: 756, 23: 483})])",MACs,9079.555584,top1_acc,-91.37521642344794 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6005.589504,top1_acc,-91.09572099925798 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 483})])",MACs,9142.601216,top1_acc,-91.34553549344547 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6554.977792,top1_acc,-91.11798169675983 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,8709.080576,top1_acc,-91.31832797427653 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 483})])",MACs,8181.646848,top1_acc,-91.25154588177095 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5210.441216,top1_acc,-90.97452386841455 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 768, 5: 512, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 2543, 17: 2500, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7193.232896,top1_acc,-91.24907247093742 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,4807.32928,top1_acc,-91.02399208508534 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 2452, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,8868.201984,top1_acc,-91.38263665594856 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6002.640384,top1_acc,-91.15013603759584 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5471.86432,top1_acc,-91.03141231758595 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5510.333952,top1_acc,-91.05367301508781 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2500, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 197})])",MACs,7848.19968,top1_acc,-91.17487014593124 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 483})])",MACs,7431.128576,top1_acc,-91.12292851842692 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 384, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5814.748672,top1_acc,-91.06604006925551 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 384, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,7354.189312,top1_acc,-91.22433836260203 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5709.825536,top1_acc,-91.09572099925798 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6270.682624,top1_acc,-90.96463022508038 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5882.512896,top1_acc,-91.16002968093 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 348, 23: 483})])",MACs,8640.20224,top1_acc,-91.30843433094236 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5561.583104,top1_acc,-91.03388572841949 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 768, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,7420.118528,top1_acc,-91.20455107593372 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 115})])",MACs,7179.273728,top1_acc,-91.23917882760327 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5712.315904,top1_acc,-91.05367301508781 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 768, 9: 192, 10: 320, 11: 512, 12: 1675, 13: 3072, 14: 3072, 15: 3072, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 483})])",MACs,6342.1824,top1_acc,-90.96463022508038 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 768, 5: 256, 6: 192, 7: 768, 8: 64, 9: 768, 10: 192, 11: 768, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,6034.1632,top1_acc,-90.98194410091516 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5390.075392,top1_acc,-90.94978976007914 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 1957, 23: 197})])",MACs,8062.764544,top1_acc,-91.32080138511006 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 483})])",MACs,7085.622784,top1_acc,-91.10808805342567 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 1524, 22: 1957, 23: 115})])",MACs,8008.76288,top1_acc,-91.24659906010389 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 483})])",MACs,8795.129344,top1_acc,-91.25649270343804 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 768, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 1751, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 115})])",MACs,6519.326208,top1_acc,-91.0784071234232 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6222.644736,top1_acc,-91.24659906010389 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 320, 11: 768, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 3072, 18: 3072, 19: 2980, 20: 2936, 21: 1524, 22: 348, 23: 483})])",MACs,7768.966656,top1_acc,-91.13034875092752 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 115})])",MACs,7102.4,top1_acc,-91.16744991343062 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,9639.62624,top1_acc,-91.39995053178332 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 483})])",MACs,6297.814528,top1_acc,-90.94978976007914 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 512, 6: 192, 7: 384, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5505.353216,top1_acc,-91.03883255008657 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 2530, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5543.95392,top1_acc,-91.08335394509028 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 3072, 23: 115})])",MACs,8289.650176,top1_acc,-91.21939154093495 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 768, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 1772, 17: 3072, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 3072, 23: 483})])",MACs,8574.404096,top1_acc,-91.1476626267623 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 1772, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,7186.417152,top1_acc,-91.10066782092505 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 2500, 18: 1709, 19: 2403, 20: 1320, 21: 1524, 22: 348, 23: 197})])",MACs,6163.990016,top1_acc,-91.11798169675983 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 2543, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 115})])",MACs,8083.015168,top1_acc,-91.1723967350977 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5453.84192,top1_acc,-90.98936433341578 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 2543, 17: 2982, 18: 3072, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6693.12768,top1_acc,-91.16744991343062 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 483})])",MACs,7435.126272,top1_acc,-91.09077417759089 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6489.048576,top1_acc,-91.24907247093742 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3024, 14: 3072, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,7344.948736,top1_acc,-91.05119960425426 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 512, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 2530, 15: 1791, 16: 1772, 17: 1751, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 115})])",MACs,5573.576192,top1_acc,-90.86816720257235 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 3072, 18: 2974, 19: 2980, 20: 2100, 21: 762, 22: 3072, 23: 197})])",MACs,8528.659968,top1_acc,-91.33811526094485 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2500, 18: 1709, 19: 2403, 20: 2100, 21: 1524, 22: 348, 23: 197})])",MACs,7150.306816,top1_acc,-91.13776898342815 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5051.1232,top1_acc,-91.0413059609201 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 1957, 23: 197})])",MACs,7076.447744,top1_acc,-91.1105614642592 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,4752.803328,top1_acc,-91.01904526341825 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 64, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,4725.540352,top1_acc,-90.95226317091269 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 115})])",MACs,6914.901504,top1_acc,-91.20207766510018 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,5014.291968,top1_acc,-91.09819441009151 +"OrderedDict([(, {0: 448, 1: 256, 2: 320, 3: 192, 4: 768, 5: 256, 6: 192, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 1675, 13: 1666, 14: 2530, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,5796.988416,top1_acc,-90.96463022508038 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 1957, 23: 483})])",MACs,9062.319616,top1_acc,-91.3727430126144 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 1524, 22: 1957, 23: 197})])",MACs,8444.446208,top1_acc,-91.25896611427157 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 756, 23: 483})])",MACs,8595.047936,top1_acc,-91.29854068760821 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6002.640384,top1_acc,-91.15013603759584 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 768, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 483})])",MACs,7502.038528,top1_acc,-91.17487014593124 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 192, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 3072, 15: 1791, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 348, 23: 483})])",MACs,6955.337216,top1_acc,-91.11798169675983 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 2530, 15: 3072, 16: 3072, 17: 3072, 18: 2974, 19: 2980, 20: 2100, 21: 762, 22: 3072, 23: 197})])",MACs,8892.84352,top1_acc,-91.34306208261192 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 1772, 17: 3072, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 3072, 23: 483})])",MACs,9132.70528,top1_acc,-91.32080138511006 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 3024, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,6503.204352,top1_acc,-91.01904526341825 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 192, 7: 768, 8: 768, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2452, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6579.684864,top1_acc,-91.16002968093 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 768, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 2530, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6652.626432,top1_acc,-91.23175859510265 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 192, 9: 192, 10: 320, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 1772, 17: 1751, 18: 3072, 19: 2403, 20: 2936, 21: 1524, 22: 348, 23: 483})])",MACs,7997.228544,top1_acc,-91.13282216176107 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 1791, 16: 3072, 17: 3072, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 756, 23: 197})])",MACs,8153.335296,top1_acc,-91.21444471926787 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 192, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 115})])",MACs,4833.019392,top1_acc,-91.0215186742518 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 320, 11: 512, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 2980, 20: 2100, 21: 1524, 22: 348, 23: 483})])",MACs,8716.420608,top1_acc,-91.35790254761315 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 192, 10: 320, 11: 512, 12: 3072, 13: 3024, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 197})])",MACs,8794.736128,top1_acc,-91.3109077417759 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 64, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 197})])",MACs,6195.512832,top1_acc,-91.14024239426169 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 384, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5381.883392,top1_acc,-91.07346030175613 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 768, 5: 256, 6: 768, 7: 768, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 1524, 22: 1957, 23: 115})])",MACs,6592.988672,top1_acc,-91.00667820925055 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 768, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 3072, 14: 1787, 15: 3072, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 756, 23: 197})])",MACs,6987.974144,top1_acc,-91.0215186742518 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 192, 4: 256, 5: 512, 6: 768, 7: 768, 8: 384, 9: 768, 10: 320, 11: 512, 12: 2460, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 2974, 19: 2403, 20: 2100, 21: 762, 22: 3072, 23: 115})])",MACs,7460.161024,top1_acc,-91.21939154093495 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 1751, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,5585.307136,top1_acc,-91.12540192926045 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 192, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 1772, 17: 1751, 18: 2974, 19: 2403, 20: 1320, 21: 762, 22: 348, 23: 115})])",MACs,6155.07712,top1_acc,-91.01904526341825 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 3024, 14: 3072, 15: 1791, 16: 1772, 17: 1751, 18: 1709, 19: 2403, 20: 2100, 21: 762, 22: 756, 23: 197})])",MACs,6860.047872,top1_acc,-91.01409844175117 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 768, 5: 768, 6: 768, 7: 384, 8: 768, 9: 768, 10: 192, 11: 512, 12: 2460, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 2982, 18: 3072, 19: 2980, 20: 2100, 21: 762, 22: 756, 23: 483})])",MACs,8645.11744,top1_acc,-91.2663863467722 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 768, 5: 256, 6: 768, 7: 384, 8: 768, 9: 768, 10: 192, 11: 512, 12: 1675, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 3072, 18: 1709, 19: 2980, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,6871.320064,top1_acc,-91.2292851842691 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 192, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 3072, 16: 3072, 17: 2982, 18: 2452, 19: 2403, 20: 2100, 21: 762, 22: 348, 23: 197})])",MACs,6992.168448,top1_acc,-91.16002968093 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 256, 5: 256, 6: 768, 7: 384, 8: 384, 9: 768, 10: 192, 11: 512, 12: 3072, 13: 1666, 14: 1787, 15: 1791, 16: 3072, 17: 2982, 18: 1709, 19: 2403, 20: 1320, 21: 762, 22: 3072, 23: 115})])",MACs,7232.947712,top1_acc,-91.18229037843186 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 256, 5: 768, 6: 768, 7: 768, 8: 384, 9: 768, 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a/eftnas-s1-bert-base-rte/README.md b/eftnas-s1-bert-base-rte/README.md new file mode 100644 index 0000000000000000000000000000000000000000..3e3ef5edf4eece43c24d550da665f572d606f973 --- /dev/null +++ b/eftnas-s1-bert-base-rte/README.md @@ -0,0 +1,108 @@ +--- +language: +- en +license: apache-2.0 +tags: +- generated_from_trainer +datasets: +- glue +metrics: +- accuracy +model-index: +- name: tryv3_16epochs + results: + - task: + name: Text Classification + type: text-classification + dataset: + name: GLUE RTE + type: glue + config: rte + split: validation + args: rte + metrics: + - name: Accuracy + type: accuracy + value: 0.6498194945848376 +--- + + + +# tryv3_16epochs + +This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE RTE dataset. +It achieves the following results on the evaluation set: +- Loss: 1.0256 +- Accuracy: 0.6498 + +## Model description + +More information needed + +## Intended uses & limitations + +More information needed + +## Training and evaluation data + +More information needed + +## Training procedure + +### Training hyperparameters + +The following hyperparameters were used during training: +- learning_rate: 2e-05 +- train_batch_size: 32 +- eval_batch_size: 128 +- seed: 42 +- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 +- lr_scheduler_type: linear +- num_epochs: 30 +- mixed_precision_training: Native AMP + +### Training results + +| Training Loss | Epoch | Step | Validation Loss | Accuracy | | +|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| +| No log | 1.0 | 78 | 0.6907 | 0.5126 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| No log | 1.0 | 78 | 0.6698 | 0.6318 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| No log | 2.0 | 156 | 0.7006 | 0.5884 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| No log | 2.0 | 156 | 0.6683 | 0.6715 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| No log | 3.0 | 234 | 0.7282 | 0.5957 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| No log | 3.0 | 234 | 0.7189 | 0.7004 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| No log | 4.0 | 312 | 0.7194 | 0.6534 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| No log | 4.0 | 312 | 0.7805 | 0.7004 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| No log | 5.0 | 390 | 0.8791 | 0.6354 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| No log | 5.0 | 390 | 0.8328 | 0.7076 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| No log | 6.0 | 468 | 1.0037 | 0.6173 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| No log | 6.0 | 468 | 0.8701 | 0.6895 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.5371 | 7.0 | 546 | 0.9121 | 0.6245 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| 0.5371 | 7.0 | 546 | 0.8220 | 0.6859 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.5371 | 8.0 | 624 | 1.0092 | 0.6245 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| 0.5371 | 8.0 | 624 | 0.8341 | 0.6823 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.5371 | 9.0 | 702 | 0.9687 | 0.6426 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| 0.5371 | 9.0 | 702 | 0.8538 | 0.6643 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.5371 | 10.0 | 780 | 1.0111 | 0.6354 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| 0.5371 | 10.0 | 780 | 0.8117 | 0.6968 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.5371 | 11.0 | 858 | 0.9616 | 0.6498 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| 0.5371 | 11.0 | 858 | 0.8113 | 0.6895 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.5371 | 12.0 | 936 | 0.9934 | 0.6462 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| 0.5371 | 12.0 | 936 | 0.8179 | 0.6895 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.1174 | 13.0 | 1014 | 1.0097 | 0.6318 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| 0.1174 | 13.0 | 1014 | 0.8191 | 0.7004 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.1174 | 14.0 | 1092 | 1.0019 | 0.6462 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| 0.1174 | 14.0 | 1092 | 0.8157 | 0.7004 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.1174 | 15.0 | 1170 | 1.0127 | 0.6318 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| 0.1174 | 15.0 | 1170 | 0.8178 | 0.6895 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.1174 | 16.0 | 1248 | 1.0095 | 0.6462 | OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})]) | +| 0.1174 | 16.0 | 1248 | 0.8178 | 0.6895 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | + + +### Framework versions + +- Transformers 4.29.1 +- Pytorch 1.12.1 +- Datasets 2.13.1 +- Tokenizers 0.13.3 diff --git a/eftnas-s1-bert-base-rte/all_results.json b/eftnas-s1-bert-base-rte/all_results.json new file mode 100644 index 0000000000000000000000000000000000000000..bb35a799c566f10ad0a3f619cd696d1f27cf58c3 --- /dev/null +++ b/eftnas-s1-bert-base-rte/all_results.json @@ -0,0 +1,14 @@ +{ + "epoch": 16.0, + "eval_accuracy": 0.6498194945848376, + "eval_loss": 1.0256149768829346, + "eval_runtime": 0.3567, + "eval_samples": 277, + "eval_samples_per_second": 776.612, + "eval_steps_per_second": 8.411, + "train_loss": 0.27760597070058185, + "train_runtime": 2463.0354, + "train_samples": 2490, + "train_samples_per_second": 16.175, + "train_steps_per_second": 0.507 +} \ No newline at end of file diff --git a/eftnas-s1-bert-base-rte/cache_MACs.csv b/eftnas-s1-bert-base-rte/cache_MACs.csv new file mode 100644 index 0000000000000000000000000000000000000000..f765c4fb105a23bb650c06f28223dd5898979516 --- /dev/null +++ b/eftnas-s1-bert-base-rte/cache_MACs.csv @@ -0,0 +1,984 @@ +"(0, 2, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 4, 1, 4, 1, 3, 1, 1, 1, 4, 3, 4, 1)",7244.350976 +"(1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 2, 1, 4, 4, 0, 0, 1, 1, 4, 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"324 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"330 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"333 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"334 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"339 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"340 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"342 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"343 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"347 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"348 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "359 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"359 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "361 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"361 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "362 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"362 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "363 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"363 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"364 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"365 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "367 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"367 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"370 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"371 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "373 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"373 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"374 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"375 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "377 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"377 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"380 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"381 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "393 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"383 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"384 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "386 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"386 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "387 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"387 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "395 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"388 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"389 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "391 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"391 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "392 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"392 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"393 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "394 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"394 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"395 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "397 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"397 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "398 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"398 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "399 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"399 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "400 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"400 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "402 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"402 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "403 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"403 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "404 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"404 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"405 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"406 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "408 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"408 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"411 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"412 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "414 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"414 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"415 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"416 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "418 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"418 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"421 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"422 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "434 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"424 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"425 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "427 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"427 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "428 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"428 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "436 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"429 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"430 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "432 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"432 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "433 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"433 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"434 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "435 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"435 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"436 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "438 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"438 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "439 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"439 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "440 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"440 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "441 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"441 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "443 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"443 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "444 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"444 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "445 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"445 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"446 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"447 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "449 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"449 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"452 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"453 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "455 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"455 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"456 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"457 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "459 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"459 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" -> "461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "491 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"462 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"463 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "475 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"465 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"466 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "468 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"468 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "469 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"469 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "477 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"470 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"471 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "473 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"473 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "474 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"474 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "483 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"475 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "476 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"476 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "478 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"477 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "478 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"478 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "479 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"479 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "480 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"480 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "481 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"481 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "482 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"482 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "483 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"483 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "484 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"484 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "485 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"485 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "486 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"486 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "489 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"487 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "489 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"488 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "489 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"489 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "490 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"490 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "491 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"491 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "492 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"492 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "495 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"492 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "324 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"324 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" -> "329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "330 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "334 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"330 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "333 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BertForSequenceClassification/BertModel[bert]/BertPooler[pooler]/__getitem___0" -> "360 BertForSequenceClassification/BertModel[bert]/BertPooler[pooler]/NNCFLinear[dense]/linear_0" [label="(1, 768) \n0 -> 0", style=solid]; +"360 BertForSequenceClassification/BertModel[bert]/BertPooler[pooler]/NNCFLinear[dense]/linear_0" -> "361 BertForSequenceClassification/BertModel[bert]/BertPooler[pooler]/Tanh[activation]/tanh_0" [label="(1, 768) \n0 -> 0", style=solid]; +"361 BertForSequenceClassification/BertModel[bert]/BertPooler[pooler]/Tanh[activation]/tanh_0" -> "362 BertForSequenceClassification/Dropout[dropout]/dropout_0" [label="(1, 768) \n0 -> 0", style=solid]; +"362 BertForSequenceClassification/Dropout[dropout]/dropout_0" -> "363 BertForSequenceClassification/NNCFLinear[classifier]/linear_0" [label="(1, 768) \n0 -> 0", style=solid]; +"363 BertForSequenceClassification/NNCFLinear[classifier]/linear_0" -> "364 /nncf_model_output_0" [label="(1, 2) \n0 -> 0", style=solid]; +} diff --git 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0000000000000000000000000000000000000000..496cf4a03732ad3bd69480a3cf49ff4876b78734 --- /dev/null +++ b/eftnas-s1-bert-base-rte/search_progression.csv @@ -0,0 +1,1000 @@ +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 640, 11: 768, 12: 608, 13: 2426, 14: 589, 15: 2417, 16: 1124, 17: 2446, 18: 2409, 19: 2426, 20: 562, 21: 1000, 22: 376, 23: 1602})])",MACs,7244.350976,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 3072, 15: 3072, 16: 2449, 17: 2446, 18: 568, 19: 1054, 20: 1670, 21: 453, 22: 3072, 23: 147})])",MACs,7370.638848,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 768, 11: 704, 12: 1773, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1078, 19: 3072, 20: 562, 21: 1000, 22: 1497, 23: 147})])",MACs,6692.865536,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 768, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1755, 15: 2417, 16: 1124, 17: 1768, 18: 2409, 19: 537, 20: 3072, 21: 3072, 22: 2247, 23: 3072})])",MACs,8571.848192,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 704, 9: 704, 10: 768, 11: 640, 12: 1159, 13: 3072, 14: 2419, 15: 542, 16: 2449, 17: 589, 18: 1078, 19: 2426, 20: 1670, 21: 1633, 22: 376, 23: 3072})])",MACs,7572.29312,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 640, 8: 768, 9: 704, 10: 640, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 542, 16: 1748, 17: 1100, 18: 1078, 19: 2426, 20: 2407, 21: 1000, 22: 376, 23: 3072})])",MACs,7316.309504,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 704, 9: 704, 10: 640, 11: 704, 12: 1159, 13: 3072, 14: 589, 15: 1742, 16: 2449, 17: 589, 18: 1730, 19: 537, 20: 1670, 21: 1000, 22: 2247, 23: 1602})])",MACs,7214.13888,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 640, 11: 704, 12: 3072, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 1768, 18: 3072, 19: 3072, 20: 562, 21: 1000, 22: 376, 23: 1602})])",MACs,7919.109632,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 768, 11: 640, 12: 3072, 13: 2426, 14: 3072, 15: 3072, 16: 2449, 17: 589, 18: 2409, 19: 1739, 20: 562, 21: 2376, 22: 3072, 23: 1602})])",MACs,8824.882688,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 704, 9: 704, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 1108, 16: 1124, 17: 1768, 18: 3072, 19: 1054, 20: 2407, 21: 1000, 22: 3072, 23: 147})])",MACs,8475.182592,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 704, 6: 768, 7: 640, 8: 768, 9: 704, 10: 768, 11: 704, 12: 1159, 13: 1119, 14: 1755, 15: 2417, 16: 2449, 17: 2446, 18: 2409, 19: 537, 20: 2407, 21: 1633, 22: 1497, 23: 1602})])",MACs,7758.08768,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 768, 9: 768, 10: 768, 11: 768, 12: 608, 13: 2426, 14: 3072, 15: 2417, 16: 1124, 17: 589, 18: 2409, 19: 2426, 20: 562, 21: 1633, 22: 840, 23: 147})])",MACs,7487.882752,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 768, 9: 768, 10: 768, 11: 704, 12: 608, 13: 571, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 568, 19: 1739, 20: 562, 21: 1633, 22: 2247, 23: 3072})])",MACs,7567.967744,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 768, 11: 704, 12: 1773, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 2446, 18: 1730, 19: 1054, 20: 1670, 21: 453, 22: 3072, 23: 147})])",MACs,6868.502016,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 768, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 768, 9: 768, 10: 640, 11: 640, 12: 1773, 13: 1728, 14: 589, 15: 1108, 16: 2449, 17: 3072, 18: 1730, 19: 537, 20: 562, 21: 1000, 22: 3072, 23: 424})])",MACs,7228.687872,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 768, 1: 448, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 768, 11: 768, 12: 608, 13: 571, 14: 2419, 15: 1108, 16: 576, 17: 1768, 18: 1078, 19: 2426, 20: 2407, 21: 3072, 22: 3072, 23: 842})])",MACs,7657.358848,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,8870.823424,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 576, 17: 1100, 18: 1078, 19: 537, 20: 562, 21: 2376, 22: 1497, 23: 424})])",MACs,6614.746624,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 640, 12: 1159, 13: 1728, 14: 1155, 15: 542, 16: 2449, 17: 1768, 18: 1730, 19: 2426, 20: 3072, 21: 1633, 22: 376, 23: 842})])",MACs,7365.789184,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 640, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 1748, 17: 3072, 18: 1078, 19: 1739, 20: 2407, 21: 2376, 22: 3072, 23: 424})])",MACs,7923.500544,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 768, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 768, 9: 704, 10: 640, 11: 640, 12: 2400, 13: 571, 14: 589, 15: 3072, 16: 1748, 17: 1768, 18: 1730, 19: 537, 20: 3072, 21: 453, 22: 1497, 23: 842})])",MACs,7220.3648,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 640, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1773, 13: 571, 14: 1755, 15: 1108, 16: 1124, 17: 1100, 18: 1730, 19: 1054, 20: 1670, 21: 2376, 22: 840, 23: 842})])",MACs,6597.510656,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 768, 9: 704, 10: 640, 11: 768, 12: 1773, 13: 571, 14: 2419, 15: 1108, 16: 2449, 17: 3072, 18: 2409, 19: 3072, 20: 2407, 21: 453, 22: 376, 23: 1602})])",MACs,7976.912384,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 640, 11: 768, 12: 1159, 13: 2426, 14: 1755, 15: 2417, 16: 1748, 17: 3072, 18: 1078, 19: 537, 20: 1670, 21: 2376, 22: 840, 23: 424})])",MACs,7569.868288,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 768, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 768, 9: 704, 10: 768, 11: 768, 12: 1773, 13: 2426, 14: 1755, 15: 1108, 16: 1748, 17: 2446, 18: 2409, 19: 537, 20: 1080, 21: 1633, 22: 376, 23: 424})])",MACs,7164.00384,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 640, 11: 704, 12: 1159, 13: 571, 14: 2419, 15: 542, 16: 576, 17: 3072, 18: 1078, 19: 3072, 20: 2407, 21: 1000, 22: 376, 23: 3072})])",MACs,7429.75232,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 1730, 19: 1739, 20: 1670, 21: 1633, 22: 376, 23: 147})])",MACs,7354.254848,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 640, 11: 768, 12: 608, 13: 2426, 14: 1155, 15: 1108, 16: 1748, 17: 1768, 18: 1730, 19: 1054, 20: 3072, 21: 1633, 22: 1497, 23: 424})])",MACs,7100.302848,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 768, 12: 1773, 13: 1119, 14: 589, 15: 3072, 16: 1124, 17: 1100, 18: 568, 19: 2426, 20: 1670, 21: 1633, 22: 2247, 23: 424})])",MACs,7006.324224,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 768, 1: 768, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 768, 9: 768, 10: 768, 11: 704, 12: 2400, 13: 2426, 14: 589, 15: 3072, 16: 3072, 17: 589, 18: 2409, 19: 1739, 20: 562, 21: 1000, 22: 840, 23: 3072})])",MACs,8070.301184,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 640, 8: 704, 9: 704, 10: 768, 11: 640, 12: 1773, 13: 1119, 14: 1755, 15: 1108, 16: 576, 17: 1100, 18: 3072, 19: 2426, 20: 562, 21: 1633, 22: 376, 23: 3072})])",MACs,7223.444992,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 768, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 640, 11: 704, 12: 3072, 13: 1119, 14: 2419, 15: 2417, 16: 1748, 17: 1100, 18: 1078, 19: 1054, 20: 3072, 21: 453, 22: 376, 23: 1602})])",MACs,7516.9152,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 640, 8: 768, 9: 768, 10: 640, 11: 768, 12: 1159, 13: 2426, 14: 2419, 15: 1742, 16: 3072, 17: 3072, 18: 3072, 19: 1739, 20: 1670, 21: 2376, 22: 3072, 23: 147})])",MACs,8622.638592,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 768, 1: 576, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 3072, 13: 2426, 14: 3072, 15: 1108, 16: 3072, 17: 589, 18: 568, 19: 537, 20: 2407, 21: 1000, 22: 3072, 23: 147})])",MACs,7632.782848,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 768, 12: 1773, 13: 2426, 14: 3072, 15: 1742, 16: 1748, 17: 589, 18: 1730, 19: 1739, 20: 3072, 21: 3072, 22: 1497, 23: 1602})])",MACs,8248.29696,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 640, 8: 704, 9: 768, 10: 512, 11: 768, 12: 608, 13: 3072, 14: 1755, 15: 1108, 16: 1124, 17: 1100, 18: 2409, 19: 2426, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7287.080448,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 768, 1: 448, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 1119, 14: 589, 15: 3072, 16: 2449, 17: 1768, 18: 3072, 19: 537, 20: 1080, 21: 1000, 22: 840, 23: 3072})])",MACs,7374.636544,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 704, 9: 768, 10: 640, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 562, 21: 2376, 22: 840, 23: 3072})])",MACs,7812.48256,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 704, 6: 768, 7: 704, 8: 704, 9: 704, 10: 512, 11: 768, 12: 2400, 13: 571, 14: 1155, 15: 1742, 16: 1748, 17: 589, 18: 1730, 19: 1739, 20: 3072, 21: 1000, 22: 3072, 23: 424})])",MACs,7246.120448,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 768, 1: 576, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 768, 9: 768, 10: 512, 11: 640, 12: 1773, 13: 2426, 14: 1755, 15: 3072, 16: 576, 17: 1100, 18: 2409, 19: 1739, 20: 1670, 21: 453, 22: 3072, 23: 147})])",MACs,7514.686976,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 640, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1773, 13: 571, 14: 1755, 15: 1108, 16: 1124, 17: 1100, 18: 1730, 19: 1054, 20: 1670, 21: 2376, 22: 840, 23: 1602})])",MACs,6801.458688,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 768, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 768, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 1748, 17: 3072, 18: 1078, 19: 1739, 20: 2407, 21: 3072, 22: 3072, 23: 842})])",MACs,8387.88864,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 3072, 15: 3072, 16: 1124, 17: 2446, 18: 2409, 19: 1054, 20: 562, 21: 453, 22: 3072, 23: 147})])",MACs,7390.561792,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 1108, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 3072, 23: 3072})])",MACs,9387.443712,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 704, 12: 1159, 13: 1728, 14: 1155, 15: 1108, 16: 2449, 17: 1768, 18: 2409, 19: 3072, 20: 3072, 21: 2376, 22: 376, 23: 842})])",MACs,7883.654656,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 768, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 640, 8: 768, 9: 768, 10: 640, 11: 768, 12: 1159, 13: 2426, 14: 2419, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 1739, 20: 1670, 21: 2376, 22: 3072, 23: 3072})])",MACs,9595.520512,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 640, 8: 704, 9: 704, 10: 768, 11: 640, 12: 1773, 13: 2426, 14: 1755, 15: 1108, 16: 576, 17: 1100, 18: 3072, 19: 2426, 20: 1670, 21: 1633, 22: 376, 23: 424})])",MACs,7177.635328,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 768, 11: 704, 12: 1773, 13: 2426, 14: 1755, 15: 542, 16: 576, 17: 1768, 18: 1078, 19: 3072, 20: 562, 21: 1000, 22: 1497, 23: 147})])",MACs,6783.56736,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 704, 8: 768, 9: 704, 10: 640, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 1748, 17: 1100, 18: 1078, 19: 2426, 20: 2407, 21: 453, 22: 376, 23: 3072})])",MACs,7651.657216,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 768, 12: 1773, 13: 2426, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 1730, 19: 2426, 20: 1670, 21: 1633, 22: 2247, 23: 147})])",MACs,8168.01536,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 640, 11: 768, 12: 608, 13: 2426, 14: 1755, 15: 2417, 16: 1748, 17: 3072, 18: 2409, 19: 2426, 20: 562, 21: 1000, 22: 840, 23: 1602})])",MACs,7946.896896,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 768, 1: 576, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 768, 9: 704, 10: 768, 11: 768, 12: 608, 13: 2426, 14: 1755, 15: 2417, 16: 1748, 17: 2446, 18: 2409, 19: 537, 20: 1080, 21: 1633, 22: 840, 23: 424})])",MACs,7392.593408,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 640, 8: 768, 9: 704, 10: 640, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 542, 16: 1748, 17: 1768, 18: 1730, 19: 2426, 20: 2407, 21: 1000, 22: 376, 23: 3072})])",MACs,7687.112192,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 768, 11: 704, 12: 608, 13: 571, 14: 2419, 15: 1108, 16: 2449, 17: 2446, 18: 568, 19: 1054, 20: 2407, 21: 453, 22: 3072, 23: 147})])",MACs,7137.330688,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 576, 17: 3072, 18: 1078, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,7165.773312,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 704, 9: 704, 10: 768, 11: 768, 12: 1159, 13: 3072, 14: 2419, 15: 542, 16: 2449, 17: 589, 18: 1078, 19: 2426, 20: 1670, 21: 1633, 22: 3072, 23: 3072})])",MACs,8156.87424,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 768, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 640, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1755, 15: 2417, 16: 1124, 17: 3072, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 2247, 23: 3072})])",MACs,8518.829568,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 704, 9: 768, 10: 640, 11: 704, 12: 1773, 13: 1119, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 1633, 22: 840, 23: 3072})])",MACs,6920.472064,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 2400, 13: 3072, 14: 589, 15: 1108, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 1602})])",MACs,8747.615744,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 640, 11: 704, 12: 3072, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 1768, 18: 3072, 19: 3072, 20: 562, 21: 1000, 22: 376, 23: 842})])",MACs,7715.1616,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 640, 11: 768, 12: 608, 13: 571, 14: 2419, 15: 1108, 16: 576, 17: 1768, 18: 1078, 19: 2426, 20: 2407, 21: 2376, 22: 3072, 23: 424})])",MACs,7192.970752,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 768, 9: 768, 10: 768, 11: 768, 12: 608, 13: 2426, 14: 3072, 15: 2417, 16: 2449, 17: 589, 18: 568, 19: 2426, 20: 1670, 21: 1633, 22: 840, 23: 147})])",MACs,7467.959808,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 1497, 23: 424})])",MACs,5897.389568,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 704, 9: 768, 10: 640, 11: 640, 12: 1773, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 1730, 19: 2426, 20: 562, 21: 1633, 22: 840, 23: 3072})])",MACs,7294.617088,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 1119, 14: 589, 15: 1742, 16: 2449, 17: 1768, 18: 3072, 19: 537, 20: 1080, 21: 1000, 22: 840, 23: 147})])",MACs,6401.754624,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 640, 11: 768, 12: 1159, 13: 1119, 14: 1755, 15: 2417, 16: 1748, 17: 3072, 18: 1078, 19: 537, 20: 562, 21: 2376, 22: 840, 23: 3072})])",MACs,7615.677952,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 768, 1: 576, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 2417, 16: 1124, 17: 1768, 18: 2409, 19: 537, 20: 3072, 21: 3072, 22: 2247, 23: 3072})])",MACs,8481.146368,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 768, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 640, 8: 768, 9: 768, 10: 512, 11: 640, 12: 1773, 13: 2426, 14: 1755, 15: 542, 16: 576, 17: 1100, 18: 2409, 19: 1739, 20: 1670, 21: 1000, 22: 3072, 23: 147})])",MACs,7179.339264,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 640, 12: 608, 13: 1119, 14: 589, 15: 3072, 16: 1124, 17: 1100, 18: 568, 19: 1739, 20: 1670, 21: 1633, 22: 376, 23: 424})])",MACs,6192.563712,top1_acc,-62.454873646209386 +"OrderedDict([(, {0: 768, 1: 448, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 640, 11: 768, 12: 1159, 13: 2426, 14: 589, 15: 2417, 16: 1124, 17: 2446, 18: 1078, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 424})])",MACs,6867.322368,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 768, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 768, 9: 768, 10: 768, 11: 768, 12: 1773, 13: 2426, 14: 3072, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 2426, 20: 562, 21: 1633, 22: 376, 23: 147})])",MACs,7259.293184,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 640, 12: 1159, 13: 1728, 14: 589, 15: 542, 16: 2449, 17: 1100, 18: 1078, 19: 2426, 20: 3072, 21: 1633, 22: 376, 23: 842})])",MACs,6994.986496,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 768, 1: 448, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 768, 12: 608, 13: 571, 14: 3072, 15: 3072, 16: 576, 17: 1768, 18: 1078, 19: 2426, 20: 1670, 21: 3072, 22: 3072, 23: 842})])",MACs,7890.667008,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 768, 12: 608, 13: 2426, 14: 1155, 15: 3072, 16: 1748, 17: 1100, 18: 1730, 19: 1739, 20: 562, 21: 1633, 22: 376, 23: 147})])",MACs,6803.22816,top1_acc,-61.73285198555957 +"OrderedDict([(, {0: 768, 1: 576, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 3072, 13: 2426, 14: 3072, 15: 1108, 16: 3072, 17: 589, 18: 568, 19: 537, 20: 2407, 21: 1000, 22: 376, 23: 147})])",MACs,7048.201728,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 704, 8: 768, 9: 768, 10: 640, 11: 768, 12: 1159, 13: 2426, 14: 2419, 15: 1742, 16: 3072, 17: 1768, 18: 2409, 19: 1739, 20: 3072, 21: 3072, 22: 3072, 23: 147})])",MACs,8675.657216,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 768, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1100, 18: 2409, 19: 2426, 20: 1670, 21: 2376, 22: 2247, 23: 424})])",MACs,7898.33472,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 768, 9: 704, 10: 640, 11: 640, 12: 1773, 13: 571, 14: 2419, 15: 542, 16: 2449, 17: 3072, 18: 2409, 19: 3072, 20: 2407, 21: 453, 22: 376, 23: 3072})])",MACs,8100.120064,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,7975.798272,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 640, 8: 704, 9: 704, 10: 640, 11: 768, 12: 1773, 13: 571, 14: 1755, 15: 1108, 16: 1124, 17: 1100, 18: 1730, 19: 1054, 20: 562, 21: 2376, 22: 840, 23: 842})])",MACs,6434.194944,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 768, 9: 704, 10: 640, 11: 704, 12: 608, 13: 3072, 14: 2419, 15: 2417, 16: 1124, 17: 3072, 18: 2409, 19: 3072, 20: 3072, 21: 3072, 22: 2247, 23: 3072})])",MACs,9620.751872,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 768, 11: 768, 12: 1773, 13: 2426, 14: 1755, 15: 542, 16: 1124, 17: 1768, 18: 1078, 19: 3072, 20: 562, 21: 2376, 22: 1497, 23: 147})])",MACs,7216.367104,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9368.241664,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 1155, 15: 3072, 16: 576, 17: 589, 18: 568, 19: 1739, 20: 562, 21: 2376, 22: 3072, 23: 424})])",MACs,7831.291392,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 640, 8: 704, 9: 704, 10: 768, 11: 704, 12: 1773, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 2426, 20: 562, 21: 1633, 22: 1497, 23: 147})])",MACs,7055.083008,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1755, 15: 2417, 16: 1124, 17: 3072, 18: 3072, 19: 1054, 20: 1670, 21: 2376, 22: 2247, 23: 3072})])",MACs,8756.790784,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 1768, 18: 2409, 19: 3072, 20: 3072, 21: 2376, 22: 840, 23: 3072})])",MACs,8483.24352,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 640, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1773, 13: 571, 14: 1755, 15: 3072, 16: 1124, 17: 1100, 18: 1730, 19: 1739, 20: 1670, 21: 1633, 22: 840, 23: 1602})])",MACs,7176.193536,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 640, 11: 768, 12: 1159, 13: 3072, 14: 589, 15: 2417, 16: 2449, 17: 2446, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 376, 23: 1602})])",MACs,8594.9824,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 640, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 562, 21: 2376, 22: 840, 23: 3072})])",MACs,7691.765248,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 768, 1: 448, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 768, 12: 1773, 13: 2426, 14: 1755, 15: 1108, 16: 1124, 17: 1100, 18: 1730, 19: 1054, 20: 1670, 21: 2376, 22: 840, 23: 1602})])",MACs,7275.218432,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 1730, 19: 1739, 20: 1670, 21: 1633, 22: 1497, 23: 147})])",MACs,8028.096,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 768, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 640, 8: 768, 9: 704, 10: 768, 11: 704, 12: 1773, 13: 3072, 14: 1755, 15: 542, 16: 1124, 17: 3072, 18: 3072, 19: 1054, 20: 1670, 21: 2376, 22: 2247, 23: 147})])",MACs,8014.857728,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 704, 8: 704, 9: 768, 10: 640, 11: 704, 12: 1159, 13: 1728, 14: 1155, 15: 1108, 16: 2449, 17: 1768, 18: 2409, 19: 3072, 20: 3072, 21: 2376, 22: 376, 23: 842})])",MACs,7938.180608,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 768, 9: 704, 10: 640, 11: 704, 12: 1773, 13: 571, 14: 2419, 15: 1108, 16: 2449, 17: 3072, 18: 2409, 19: 537, 20: 2407, 21: 3072, 22: 376, 23: 3072})])",MACs,8255.17824,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 768, 9: 768, 10: 768, 11: 768, 12: 1773, 13: 2426, 14: 3072, 15: 1108, 16: 2449, 17: 2446, 18: 2409, 19: 2426, 20: 562, 21: 1633, 22: 376, 23: 147})])",MACs,7939.425792,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 640, 12: 2400, 13: 1119, 14: 589, 15: 3072, 16: 1124, 17: 1100, 18: 568, 19: 1739, 20: 1670, 21: 1633, 22: 376, 23: 3072})])",MACs,7283.60704,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 768, 9: 704, 10: 512, 11: 768, 12: 1773, 13: 571, 14: 1155, 15: 1108, 16: 2449, 17: 1768, 18: 2409, 19: 537, 20: 2407, 21: 453, 22: 376, 23: 1602})])",MACs,6837.30688,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 768, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 640, 11: 704, 12: 1159, 13: 2426, 14: 589, 15: 2417, 16: 576, 17: 2446, 18: 1078, 19: 537, 20: 1670, 21: 1000, 22: 376, 23: 424})])",MACs,6434.522624,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 768, 12: 1773, 13: 1119, 14: 589, 15: 542, 16: 1124, 17: 1100, 18: 568, 19: 2426, 20: 1670, 21: 1633, 22: 2247, 23: 424})])",MACs,6508.905984,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 2426, 14: 3072, 15: 542, 16: 2449, 17: 589, 18: 2409, 19: 537, 20: 562, 21: 453, 22: 1497, 23: 1602})])",MACs,6890.980864,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 768, 11: 640, 12: 1773, 13: 1119, 14: 1755, 15: 1108, 16: 576, 17: 1100, 18: 1078, 19: 3072, 20: 562, 21: 1000, 22: 376, 23: 3072})])",MACs,6861.22752,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 640, 8: 768, 9: 704, 10: 768, 11: 704, 12: 608, 13: 571, 14: 2419, 15: 1108, 16: 2449, 17: 2446, 18: 568, 19: 537, 20: 2407, 21: 453, 22: 3072, 23: 147})])",MACs,6899.369472,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 704, 12: 1159, 13: 1728, 14: 1155, 15: 1108, 16: 2449, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 376, 23: 842})])",MACs,7376.209408,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 1108, 16: 1748, 17: 3072, 18: 1730, 19: 1054, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6979.52,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 768, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 2400, 13: 2426, 14: 589, 15: 1108, 16: 1124, 17: 3072, 18: 1078, 19: 537, 20: 1670, 21: 453, 22: 3072, 23: 424})])",MACs,7019.955712,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 704, 9: 768, 10: 512, 11: 768, 12: 1773, 13: 3072, 14: 1155, 15: 1108, 16: 576, 17: 1100, 18: 1078, 19: 537, 20: 562, 21: 2376, 22: 1497, 23: 424})])",MACs,6735.463936,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 640, 8: 704, 9: 704, 10: 640, 11: 768, 12: 608, 13: 571, 14: 589, 15: 2417, 16: 1124, 17: 2446, 18: 2409, 19: 2426, 20: 562, 21: 1000, 22: 376, 23: 842})])",MACs,6566.6432,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5223.548416,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 2426, 14: 1155, 15: 2417, 16: 576, 17: 1768, 18: 1078, 19: 2426, 20: 562, 21: 1000, 22: 1497, 23: 3072})])",MACs,7171.474944,top1_acc,-62.093862815884485 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,7921.27232,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 768, 1: 576, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 768, 9: 704, 10: 512, 11: 768, 12: 608, 13: 3072, 14: 1155, 15: 2417, 16: 1124, 17: 1768, 18: 2409, 19: 3072, 20: 3072, 21: 453, 22: 2247, 23: 1602})])",MACs,8202.880512,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 768, 11: 704, 12: 608, 13: 571, 14: 2419, 15: 1108, 16: 1124, 17: 589, 18: 568, 19: 1054, 20: 2407, 21: 453, 22: 3072, 23: 147})])",MACs,6457.19808,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 424})])",MACs,7779.780096,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 2426, 14: 589, 15: 542, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 562, 21: 453, 22: 3072, 23: 3072})])",MACs,8580.498944,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 3072, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 1602})])",MACs,8246.527488,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 640, 11: 768, 12: 608, 13: 3072, 14: 1755, 15: 2417, 16: 1748, 17: 3072, 18: 2409, 19: 2426, 20: 1670, 21: 1000, 22: 840, 23: 1602})])",MACs,8237.221376,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 704, 9: 704, 10: 768, 11: 704, 12: 1773, 13: 2426, 14: 3072, 15: 1108, 16: 2449, 17: 589, 18: 2409, 19: 1739, 20: 562, 21: 2376, 22: 3072, 23: 3072})])",MACs,8554.153472,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 704, 9: 768, 10: 768, 11: 704, 12: 1773, 13: 3072, 14: 1755, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 3072})])",MACs,8331.986432,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 704, 12: 1773, 13: 2426, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 1078, 19: 3072, 20: 562, 21: 1000, 22: 840, 23: 147})])",MACs,6316.099072,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1773, 13: 1119, 14: 589, 15: 542, 16: 1124, 17: 1100, 18: 568, 19: 2426, 20: 1080, 21: 1000, 22: 2247, 23: 424})])",MACs,6213.928448,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 640, 11: 768, 12: 608, 13: 3072, 14: 589, 15: 2417, 16: 2449, 17: 2446, 18: 2409, 19: 2426, 20: 1670, 21: 1000, 22: 2247, 23: 1602})])",MACs,8217.560576,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 704, 9: 768, 10: 768, 11: 768, 12: 608, 13: 2426, 14: 3072, 15: 2417, 16: 576, 17: 589, 18: 2409, 19: 2426, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,7120.881152,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 608, 13: 571, 14: 1755, 15: 2417, 16: 1748, 17: 3072, 18: 2409, 19: 2426, 20: 562, 21: 1000, 22: 840, 23: 842})])",MACs,7323.715072,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 3072, 13: 2426, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 2409, 19: 1739, 20: 1670, 21: 2376, 22: 840, 23: 147})])",MACs,8209.499648,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 768, 12: 1159, 13: 2426, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 1730, 19: 1739, 20: 1670, 21: 1633, 22: 840, 23: 147})])",MACs,7771.915776,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 2426, 14: 589, 15: 542, 16: 1124, 17: 1768, 18: 1078, 19: 3072, 20: 562, 21: 1000, 22: 840, 23: 147})])",MACs,6478.366208,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 576, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 453, 22: 1497, 23: 3072})])",MACs,7000.425984,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 768, 9: 768, 10: 768, 11: 768, 12: 608, 13: 2426, 14: 3072, 15: 3072, 16: 2449, 17: 589, 18: 568, 19: 2426, 20: 1670, 21: 1633, 22: 840, 23: 147})])",MACs,7596.738048,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1773, 13: 3072, 14: 1755, 15: 1108, 16: 1124, 17: 1100, 18: 1730, 19: 1054, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,7691.24096,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 768, 9: 768, 10: 768, 11: 768, 12: 608, 13: 2426, 14: 3072, 15: 2417, 16: 2449, 17: 1100, 18: 568, 19: 2426, 20: 1670, 21: 1633, 22: 840, 23: 147})])",MACs,7568.426496,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 640, 8: 704, 9: 704, 10: 768, 11: 768, 12: 608, 13: 1119, 14: 2419, 15: 1108, 16: 2449, 17: 2446, 18: 2409, 19: 537, 20: 2407, 21: 453, 22: 3072, 23: 147})])",MACs,7287.277056,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 704, 12: 608, 13: 571, 14: 2419, 15: 1108, 16: 1748, 17: 589, 18: 568, 19: 1054, 20: 2407, 21: 453, 22: 3072, 23: 147})])",MACs,6661.6704,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 768, 1: 576, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 640, 11: 640, 12: 608, 13: 2426, 14: 1755, 15: 2417, 16: 576, 17: 3072, 18: 568, 19: 537, 20: 562, 21: 1000, 22: 840, 23: 1602})])",MACs,6846.8096,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 768, 12: 1159, 13: 2426, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 1730, 19: 1054, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,7912.490496,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9340.978688,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 640, 11: 768, 12: 1159, 13: 1728, 14: 1155, 15: 1108, 16: 2449, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 842})])",MACs,7705.65888,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 640, 8: 704, 9: 768, 10: 640, 11: 768, 12: 1773, 13: 571, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 1054, 20: 562, 21: 2376, 22: 840, 23: 842})])",MACs,6349.260288,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 640, 8: 768, 9: 704, 10: 512, 11: 704, 12: 1773, 13: 2426, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 1078, 19: 2426, 20: 562, 21: 1633, 22: 840, 23: 147})])",MACs,6259.017216,top1_acc,-62.454873646209386 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 768, 12: 1159, 13: 1119, 14: 589, 15: 1742, 16: 2449, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 1633, 22: 840, 23: 147})])",MACs,6696.73216,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 704, 9: 704, 10: 640, 11: 704, 12: 1159, 13: 2426, 14: 589, 15: 1742, 16: 1124, 17: 589, 18: 1730, 19: 537, 20: 562, 21: 1000, 22: 376, 23: 1602})])",MACs,6240.92928,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,5590.550016,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 640, 8: 704, 9: 768, 10: 640, 11: 768, 12: 1773, 13: 2426, 14: 1755, 15: 1108, 16: 1124, 17: 1100, 18: 1730, 19: 1054, 20: 1670, 21: 2376, 22: 840, 23: 1602})])",MACs,7220.69248,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 589, 18: 1730, 19: 3072, 20: 1670, 21: 1633, 22: 376, 23: 1602})])",MACs,7391.282688,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 640, 11: 768, 12: 1159, 13: 3072, 14: 1755, 15: 2417, 16: 1748, 17: 3072, 18: 1078, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,7826.048512,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 1108, 16: 576, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,7759.005184,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 840, 23: 424})])",MACs,6872.761856,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 640, 12: 608, 13: 1119, 14: 589, 15: 2417, 16: 1124, 17: 1100, 18: 568, 19: 1739, 20: 1670, 21: 1633, 22: 376, 23: 424})])",MACs,6063.785472,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 640, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 571, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 842})])",MACs,6882.067968,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 640, 12: 608, 13: 1119, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 568, 19: 1739, 20: 1670, 21: 1633, 22: 376, 23: 424})])",MACs,6092.097024,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 571, 14: 589, 15: 1742, 16: 2449, 17: 1768, 18: 1078, 19: 537, 20: 1080, 21: 1000, 22: 840, 23: 147})])",MACs,5983.766016,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 3072, 16: 1124, 17: 3072, 18: 1730, 19: 1739, 20: 1670, 21: 1633, 22: 376, 23: 147})])",MACs,7149.782528,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 1748, 17: 589, 18: 2409, 19: 2426, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,6323.635712,top1_acc,-62.454873646209386 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 1108, 16: 1748, 17: 3072, 18: 1730, 19: 1739, 20: 1670, 21: 1633, 22: 376, 23: 147})])",MACs,7095.125504,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 768, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 640, 11: 768, 12: 1773, 13: 1119, 14: 589, 15: 542, 16: 1124, 17: 1100, 18: 568, 19: 2426, 20: 1670, 21: 1633, 22: 2247, 23: 424})])",MACs,6536.16896,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5567.940096,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 704, 9: 704, 10: 640, 11: 704, 12: 1773, 13: 3072, 14: 1755, 15: 1108, 16: 1124, 17: 1100, 18: 1730, 19: 3072, 20: 562, 21: 2376, 22: 840, 23: 3072})])",MACs,7897.417216,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 768, 11: 704, 12: 1773, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 3072, 20: 562, 21: 1000, 22: 1497, 23: 147})])",MACs,7112.164864,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 640, 8: 768, 9: 704, 10: 768, 11: 704, 12: 1159, 13: 571, 14: 1155, 15: 1108, 16: 576, 17: 2446, 18: 568, 19: 537, 20: 2407, 21: 453, 22: 1497, 23: 424})])",MACs,6135.744,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 608, 13: 3072, 14: 2419, 15: 542, 16: 2449, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 3072, 23: 147})])",MACs,6661.01504,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 2426, 14: 1155, 15: 1742, 16: 2449, 17: 589, 18: 1078, 19: 537, 20: 1080, 21: 1000, 22: 376, 23: 424})])",MACs,6272.976384,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 608, 13: 2426, 14: 1155, 15: 3072, 16: 1748, 17: 589, 18: 1730, 19: 1739, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6879.380992,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,5934.941696,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9163.17952,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 2449, 17: 3072, 18: 568, 19: 2426, 20: 1080, 21: 1000, 22: 2247, 23: 424})])",MACs,7369.393664,top1_acc,-62.093862815884485 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 640, 8: 768, 9: 704, 10: 768, 11: 704, 12: 1159, 13: 571, 14: 1155, 15: 1108, 16: 576, 17: 2446, 18: 568, 19: 3072, 20: 2407, 21: 453, 22: 376, 23: 424})])",MACs,6386.484736,top1_acc,-62.454873646209386 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 704, 12: 608, 13: 1119, 14: 2419, 15: 1108, 16: 1748, 17: 589, 18: 568, 19: 1739, 20: 2407, 21: 1633, 22: 3072, 23: 147})])",MACs,7136.085504,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 768, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 640, 11: 704, 12: 3072, 13: 2426, 14: 2419, 15: 2417, 16: 1748, 17: 2446, 18: 1078, 19: 1054, 20: 3072, 21: 453, 22: 376, 23: 1602})])",MACs,8038.516224,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 640, 11: 704, 12: 1159, 13: 2426, 14: 1155, 15: 1108, 16: 2449, 17: 1768, 18: 2409, 19: 3072, 20: 3072, 21: 2376, 22: 376, 23: 842})])",MACs,8157.20192,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,6991.709696,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 768, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 3072, 16: 2449, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 1633, 22: 3072, 23: 424})])",MACs,7540.114944,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 3072, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 1768, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 1602})])",MACs,8793.359872,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 704, 8: 704, 9: 768, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 1730, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,8354.46528,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 640, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1100, 18: 568, 19: 1739, 20: 1670, 21: 1633, 22: 376, 23: 1602})])",MACs,6889.932288,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 2426, 14: 589, 15: 1742, 16: 2449, 17: 1768, 18: 3072, 19: 537, 20: 1080, 21: 1000, 22: 840, 23: 424})])",MACs,6713.181696,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 1633, 22: 840, 23: 3072})])",MACs,7856.981504,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 768, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 1000, 22: 3072, 23: 3072})])",MACs,9530.312192,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 840, 23: 147})])",MACs,5301.339648,top1_acc,-61.371841155234655 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 3072, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 1497, 23: 147})])",MACs,6372.263424,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 576, 17: 589, 18: 1730, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 1602})])",MACs,7024.281088,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,8099.071488,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1773, 13: 1119, 14: 589, 15: 3072, 16: 1124, 17: 1100, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,8212.776448,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 704, 12: 1159, 13: 1728, 14: 1155, 15: 1108, 16: 2449, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 842})])",MACs,7125.468672,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 640, 12: 608, 13: 571, 14: 589, 15: 3072, 16: 1124, 17: 1100, 18: 568, 19: 1054, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5718.148608,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 768, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 640, 11: 704, 12: 1159, 13: 1119, 14: 589, 15: 2417, 16: 576, 17: 1100, 18: 1078, 19: 537, 20: 1670, 21: 1000, 22: 376, 23: 424})])",MACs,5912.9216,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 704, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 1728, 14: 1155, 15: 1108, 16: 1748, 17: 3072, 18: 1730, 19: 1054, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6760.498688,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 562, 21: 453, 22: 840, 23: 3072})])",MACs,6881.478144,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 3072, 18: 1078, 19: 3072, 20: 562, 21: 453, 22: 376, 23: 3072})])",MACs,7388.595712,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 571, 14: 589, 15: 1742, 16: 1124, 17: 589, 18: 1078, 19: 537, 20: 1080, 21: 1000, 22: 840, 23: 147})])",MACs,5436.933632,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 640, 11: 704, 12: 1159, 13: 1728, 14: 1155, 15: 1108, 16: 2449, 17: 1768, 18: 2409, 19: 1739, 20: 3072, 21: 1633, 22: 376, 23: 842})])",MACs,7611.811328,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 1119, 14: 1155, 15: 3072, 16: 1124, 17: 589, 18: 1730, 19: 3072, 20: 1670, 21: 1633, 22: 376, 23: 424})])",MACs,6693.914112,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 768, 1: 448, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 640, 11: 768, 12: 1159, 13: 1119, 14: 589, 15: 2417, 16: 1124, 17: 2446, 18: 1078, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6555.895296,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 768, 9: 768, 10: 768, 11: 768, 12: 608, 13: 2426, 14: 3072, 15: 2417, 16: 1124, 17: 589, 18: 2409, 19: 2426, 20: 562, 21: 2376, 22: 840, 23: 147})])",MACs,7606.69952,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1773, 13: 1119, 14: 589, 15: 542, 16: 1124, 17: 1100, 18: 568, 19: 2426, 20: 1080, 21: 453, 22: 2247, 23: 424})])",MACs,6024.594944,top1_acc,-61.73285198555957 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 1119, 14: 589, 15: 1742, 16: 2449, 17: 1768, 18: 3072, 19: 537, 20: 1080, 21: 1000, 22: 840, 23: 424})])",MACs,6647.055872,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5939.79136,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 147})])",MACs,5345.248768,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 3072, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 562, 21: 2376, 22: 840, 23: 1602})])",MACs,7419.004416,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 1730, 19: 1739, 20: 1670, 21: 1633, 22: 840, 23: 1602})])",MACs,7858.554368,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 3072, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,7483.098624,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 2426, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 562, 21: 453, 22: 840, 23: 3072})])",MACs,6525.421056,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 2417, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,5959.190016,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 1730, 19: 1739, 20: 1670, 21: 1633, 22: 2247, 23: 147})])",MACs,8175.552,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 2426, 14: 589, 15: 3072, 16: 2449, 17: 589, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 1602})])",MACs,8300.463616,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 1497, 23: 147})])",MACs,5063.509504,top1_acc,-61.371841155234655 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,8084.850176,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 768, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 2426, 14: 1155, 15: 1742, 16: 2449, 17: 589, 18: 1078, 19: 537, 20: 1080, 21: 1000, 22: 376, 23: 424})])",MACs,6382.028288,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 768, 1: 448, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 640, 11: 768, 12: 2400, 13: 3072, 14: 589, 15: 2417, 16: 2449, 17: 2446, 18: 3072, 19: 2426, 20: 1670, 21: 2376, 22: 3072, 23: 424})])",MACs,8792.311296,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 768, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 640, 11: 704, 12: 608, 13: 2426, 14: 589, 15: 2417, 16: 576, 17: 2446, 18: 1078, 19: 537, 20: 1670, 21: 1000, 22: 376, 23: 424})])",MACs,6298.92864,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 3072, 16: 576, 17: 589, 18: 1730, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6556.681728,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 1730, 19: 537, 20: 1670, 21: 1633, 22: 376, 23: 147})])",MACs,7571.375616,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9190.442496,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,5744.82176,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 2426, 14: 589, 15: 2417, 16: 576, 17: 2446, 18: 1078, 19: 3072, 20: 1670, 21: 1000, 22: 3072, 23: 424})])",MACs,7299.401216,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 1497, 23: 3072})])",MACs,7835.944448,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 589, 15: 542, 16: 2449, 17: 3072, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 3072, 23: 147})])",MACs,6229.78816,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 640, 11: 768, 12: 1159, 13: 3072, 14: 589, 15: 2417, 16: 1124, 17: 3072, 18: 1078, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,7583.172096,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 1730, 19: 1739, 20: 1670, 21: 1633, 22: 376, 23: 147})])",MACs,7710.311936,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 640, 12: 608, 13: 1119, 14: 589, 15: 542, 16: 1124, 17: 1100, 18: 568, 19: 1739, 20: 1670, 21: 1633, 22: 376, 23: 424})])",MACs,5695.145472,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 1119, 14: 589, 15: 1742, 16: 1124, 17: 3072, 18: 1078, 19: 537, 20: 1080, 21: 1000, 22: 840, 23: 424})])",MACs,6223.627776,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 840, 23: 424})])",MACs,6135.219712,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5458.888192,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,5825.889792,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 2426, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 1078, 19: 1054, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7417.890304,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5359.1424,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 1602})])",MACs,5812.848128,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 1739, 20: 562, 21: 453, 22: 840, 23: 424})])",MACs,5768.480256,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 640, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 562, 21: 2376, 22: 840, 23: 3072})])",MACs,7664.502272,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 2426, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,5780.669952,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 640, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,8476.100096,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 704, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 2376, 22: 840, 23: 424})])",MACs,6037.243392,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8439.793152,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 768, 1: 448, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 2426, 14: 1155, 15: 3072, 16: 1748, 17: 2446, 18: 1730, 19: 1739, 20: 1670, 21: 1633, 22: 376, 23: 147})])",MACs,7312.246272,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 1108, 16: 576, 17: 589, 18: 568, 19: 1054, 20: 2407, 21: 453, 22: 376, 23: 147})])",MACs,5407.31136,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 768, 10: 640, 11: 704, 12: 3072, 13: 1728, 14: 2419, 15: 2417, 16: 2449, 17: 1768, 18: 2409, 19: 3072, 20: 3072, 21: 2376, 22: 376, 23: 1602})])",MACs,9051.375104,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 2426, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 2376, 22: 376, 23: 424})])",MACs,6343.362048,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 768, 11: 704, 12: 608, 13: 2426, 14: 2419, 15: 542, 16: 1748, 17: 589, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 424})])",MACs,7194.1504,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 768, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 704, 8: 704, 9: 704, 10: 640, 11: 704, 12: 1159, 13: 1119, 14: 1155, 15: 1108, 16: 1748, 17: 1100, 18: 1078, 19: 1054, 20: 3072, 21: 453, 22: 376, 23: 842})])",MACs,6403.720704,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 1633, 22: 1497, 23: 424})])",MACs,6238.897664,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 768, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,8030.324224,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 768, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 1730, 19: 1739, 20: 1670, 21: 1633, 22: 1497, 23: 1602})])",MACs,8042.251776,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 768, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 576, 17: 589, 18: 1730, 19: 3072, 20: 2407, 21: 453, 22: 376, 23: 147})])",MACs,7019.431424,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 768, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 2426, 14: 1155, 15: 2417, 16: 576, 17: 2446, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 376, 23: 3072})])",MACs,7906.919936,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,7218.857472,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 1633, 22: 376, 23: 424})])",MACs,6152.78336,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5838.996992,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 571, 14: 589, 15: 3072, 16: 2449, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 147})])",MACs,7812.744704,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 640, 11: 768, 12: 1159, 13: 2426, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 147})])",MACs,8368.096768,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 2426, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 1739, 20: 562, 21: 1633, 22: 840, 23: 424})])",MACs,5996.938752,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,6116.214272,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 1633, 22: 3072, 23: 3072})])",MACs,9600.239104,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5509.8752,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 1497, 23: 424})])",MACs,5870.126592,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 640, 11: 704, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8521.58208,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 1773, 13: 2426, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 147})])",MACs,8461.092352,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 3072, 23: 3072})])",MACs,9623.045632,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,4879.812096,top1_acc,-61.73285198555957 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 1119, 14: 2419, 15: 1108, 16: 1748, 17: 589, 18: 568, 19: 2426, 20: 1670, 21: 3072, 22: 3072, 23: 1602})])",MACs,7558.923776,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 1108, 16: 1124, 17: 589, 18: 1078, 19: 537, 20: 1670, 21: 1000, 22: 840, 23: 424})])",MACs,6313.281024,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 704, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,6501.76256,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 2376, 22: 1497, 23: 424})])",MACs,6664.816128,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1773, 13: 2426, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 562, 21: 453, 22: 3072, 23: 3072})])",MACs,8791.066112,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 3072, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 840, 23: 3072})])",MACs,6679.03744,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1159, 13: 1728, 14: 1155, 15: 1108, 16: 2449, 17: 589, 18: 1730, 19: 1739, 20: 1670, 21: 1633, 22: 376, 23: 842})])",MACs,6780.028416,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,5072.881152,top1_acc,-62.454873646209386 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 3072, 16: 576, 17: 589, 18: 1730, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6031.017472,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 2446, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 1602})])",MACs,6177.949184,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5566.629376,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 1497, 23: 147})])",MACs,4777.18272,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5486.151168,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 562, 21: 2376, 22: 840, 23: 3072})])",MACs,7609.97632,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 3072})])",MACs,6047.335936,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7543.195136,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,5717.558784,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 640, 11: 640, 12: 608, 13: 1119, 14: 589, 15: 542, 16: 1124, 17: 1100, 18: 568, 19: 1739, 20: 1670, 21: 1633, 22: 376, 23: 424})])",MACs,5831.460352,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 589, 18: 1730, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 1602})])",MACs,6913.00096,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 704, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 1748, 17: 3072, 18: 1730, 19: 537, 20: 562, 21: 1633, 22: 840, 23: 147})])",MACs,6493.89824,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,5617.812992,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,5689.574912,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8551.07328,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 2407, 21: 1633, 22: 2247, 23: 1602})])",MACs,9293.92384,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 2426, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,7535.724032,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 768, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,5221.5168,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 2426, 14: 1155, 15: 3072, 16: 1748, 17: 3072, 18: 1730, 19: 1739, 20: 1670, 21: 1633, 22: 376, 23: 147})])",MACs,7381.517824,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8303.478272,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9244.968448,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9368.241664,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8494.319104,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,5590.550016,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 768, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 576, 17: 589, 18: 1730, 19: 3072, 20: 2407, 21: 453, 22: 376, 23: 424})])",MACs,7073.89184,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 640, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 2407, 21: 2376, 22: 840, 23: 3072})])",MACs,8054.507008,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 2426, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,7091.062272,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 640, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7595.165184,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 1497, 23: 424})])",MACs,5937.956352,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 1633, 22: 3072, 23: 147})])",MACs,8034.911744,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 768, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 576, 17: 589, 18: 1730, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,7020.217856,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 1054, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,6649.480704,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5226.235392,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,5045.618176,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9410.774528,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 1108, 16: 576, 17: 589, 18: 568, 19: 1054, 20: 2407, 21: 453, 22: 376, 23: 147})])",MACs,5352.785408,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 840, 23: 147})])",MACs,5274.076672,top1_acc,-61.01083032490975 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 1497, 23: 147})])",MACs,5008.983552,top1_acc,-62.454873646209386 +"OrderedDict([(, {0: 576, 1: 448, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 147})])",MACs,5580.588544,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5169.088,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 1108, 16: 576, 17: 589, 18: 568, 19: 1054, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5017.306624,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 1054, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,7094.142464,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 2400, 13: 571, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 1497, 23: 147})])",MACs,5989.9264,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4556.785152,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 704, 12: 608, 13: 571, 14: 589, 15: 3072, 16: 2449, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 3072})])",MACs,6429.607424,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 2449, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 1633, 22: 3072, 23: 424})])",MACs,7190.54592,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 562, 21: 2376, 22: 840, 23: 3072})])",MACs,7637.239296,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9272.231424,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,6776.620544,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 568, 19: 3072, 20: 1670, 21: 1633, 22: 376, 23: 3072})])",MACs,8235.582976,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5539.3664,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9259.18976,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 2449, 17: 3072, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,8104.11776,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 768, 11: 704, 12: 608, 13: 2426, 14: 1155, 15: 3072, 16: 576, 17: 589, 18: 1730, 19: 3072, 20: 2407, 21: 1633, 22: 376, 23: 424})])",MACs,7178.880512,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5539.431936,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 768, 11: 704, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 589, 18: 1730, 19: 3072, 20: 2407, 21: 453, 22: 376, 23: 3072})])",MACs,8163.624448,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 1497, 23: 147})])",MACs,5295.506944,top1_acc,-61.371841155234655 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 3072, 23: 3072})])",MACs,8855.291392,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 3072, 20: 1670, 21: 2376, 22: 376, 23: 424})])",MACs,6580.471296,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9111.864832,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 2407, 21: 453, 22: 376, 23: 424})])",MACs,5948.245504,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 3072, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 3072, 23: 3072})])",MACs,8532.526592,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 1602})])",MACs,5975.705088,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 3072, 18: 568, 19: 3072, 20: 562, 21: 1633, 22: 2247, 23: 3072})])",MACs,7755.46624,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5910.95552,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 424})])",MACs,6607.013376,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 562, 21: 453, 22: 3072, 23: 3072})])",MACs,8882.095616,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 768, 11: 704, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 3072, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,5541.791232,top1_acc,-61.73285198555957 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 571, 14: 1155, 15: 3072, 16: 576, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5935.793664,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 576, 17: 589, 18: 1730, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6738.216448,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8522.499584,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,7017.661952,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 768, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,7350.12608,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 1602})])",MACs,5580.850688,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 1155, 15: 1108, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8476.755456,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 1497, 23: 424})])",MACs,5637.473792,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8463.844864,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 640, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 2376, 22: 840, 23: 3072})])",MACs,7329.80992,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7876.773376,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5376.574976,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,7189.89056,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 1155, 15: 1108, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,6567.101952,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 3072})])",MACs,6179.784192,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 2426, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5900.011008,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 576, 17: 589, 18: 1730, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,6358.23872,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 768, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 2407, 21: 453, 22: 376, 23: 424})])",MACs,6309.873152,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 1497, 23: 1602})])",MACs,5349.574144,top1_acc,-61.371841155234655 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9191.753216,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5540.67712,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 768, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,7126.713856,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,5582.554624,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8330.741248,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,7892.895232,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 768, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 1602})])",MACs,5921.900032,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 768, 12: 1773, 13: 571, 14: 589, 15: 542, 16: 2449, 17: 3072, 18: 568, 19: 3072, 20: 562, 21: 453, 22: 1497, 23: 147})])",MACs,6442.845696,top1_acc,-61.371841155234655 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 3072, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7772.571136,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 768, 1: 768, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,6521.09568,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,8664.77824,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 424})])",MACs,6715.344384,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 768, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 2407, 21: 453, 22: 376, 23: 424})])",MACs,6337.136128,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,5069.342208,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8902.149632,top1_acc,-73.28519855595668 +"OrderedDict([(, {0: 768, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 424})])",MACs,6380.324352,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 3072, 23: 3072})])",MACs,9595.782656,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 2376, 22: 1497, 23: 147})])",MACs,5844.502016,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9383.511552,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 1108, 16: 576, 17: 589, 18: 568, 19: 1054, 20: 2407, 21: 453, 22: 376, 23: 424})])",MACs,5898.962432,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5278.074368,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 1054, 20: 1670, 21: 2376, 22: 840, 23: 1602})])",MACs,7142.770176,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 3072, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 3072, 23: 147})])",MACs,6069.88032,top1_acc,-59.92779783393502 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,6991.578624,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,8418.559488,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,5717.558784,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 640, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 2407, 21: 2376, 22: 840, 23: 3072})])",MACs,8027.244032,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5349.836288,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,8700.82304,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 768, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 2426, 20: 562, 21: 2376, 22: 1497, 23: 147})])",MACs,5774.247424,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6201.673216,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 640, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 2407, 21: 453, 22: 840, 23: 3072})])",MACs,6987.187712,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 589, 18: 1730, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6626.93632,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 768, 11: 704, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 2407, 21: 453, 22: 376, 23: 147})])",MACs,5763.696128,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5455.349248,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4858.840576,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 1054, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5327.881728,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 562, 21: 453, 22: 3072, 23: 3072})])",MACs,8863.548928,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 640, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 2407, 21: 2376, 22: 840, 23: 3072})])",MACs,8109.03296,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,8956.41344,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 1108, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4915.660288,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,5206.705664,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 1108, 16: 576, 17: 589, 18: 568, 19: 1054, 20: 2407, 21: 453, 22: 376, 23: 147})])",MACs,5298.259456,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,6702.237184,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 2426, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,7377.389056,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,4786.554368,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9395.50464,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8207.468032,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 768, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 1768, 18: 3072, 19: 537, 20: 2407, 21: 453, 22: 376, 23: 3072})])",MACs,8216.315392,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 2426, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,7050.29888,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9015.854592,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5983.831552,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 2407, 21: 453, 22: 376, 23: 424})])",MACs,6391.66208,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6304.761344,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9244.968448,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 453, 22: 376, 23: 3072})])",MACs,5739.316736,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 768, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 1119, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 424})])",MACs,5969.085952,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 1602})])",MACs,5924.128256,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 1768, 18: 2409, 19: 2426, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8061.388288,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 1768, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 3072})])",MACs,8630.175232,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 1108, 16: 576, 17: 589, 18: 568, 19: 1054, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5618.0096,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8874.886656,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 768, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 2426, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6410.798592,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 1155, 15: 542, 16: 2449, 17: 3072, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8044.873216,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 1773, 13: 2426, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9036.170752,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 3072, 18: 1730, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 424})])",MACs,7284.000256,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 768, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 424})])",MACs,5206.902272,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8463.844864,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 1633, 22: 376, 23: 424})])",MACs,5935.400448,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 1108, 16: 576, 17: 589, 18: 568, 19: 1054, 20: 2407, 21: 453, 22: 376, 23: 147})])",MACs,5352.785408,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,8742.045184,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 1108, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4833.87136,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 640, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 2407, 21: 2376, 22: 840, 23: 147})])",MACs,6871.975424,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 2426, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4948.755968,top1_acc,-62.093862815884485 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4804.38016,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 1078, 19: 1054, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,4877.190656,top1_acc,-62.093862815884485 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 768, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 2426, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,7241.532928,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6006.3104,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,8646.297088,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 768, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 2407, 21: 2376, 22: 1497, 23: 424})])",MACs,7017.399808,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,7058.949632,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 147})])",MACs,8588.10112,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 1108, 16: 576, 17: 2446, 18: 568, 19: 3072, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5695.145472,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 640, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 1768, 18: 2409, 19: 3072, 20: 2407, 21: 2376, 22: 1497, 23: 3072})])",MACs,8470.005248,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 1100, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8100.054528,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,4648.011264,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 2446, 18: 3072, 19: 2426, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9051.637248,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 1100, 18: 2409, 19: 1054, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6292.506112,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 768, 11: 704, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 2407, 21: 453, 22: 840, 23: 3072})])",MACs,8695.973376,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 2426, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4928.177664,top1_acc,-61.371841155234655 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 3072, 16: 576, 17: 3072, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7088.506368,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 1054, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,5460.06784,top1_acc,-62.454873646209386 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 424})])",MACs,5523.572224,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 1100, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7237.142016,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 1155, 15: 3072, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,6569.395712,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 2426, 20: 562, 21: 2376, 22: 376, 23: 424})])",MACs,6343.362048,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 640, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 2407, 21: 2376, 22: 840, 23: 3072})])",MACs,8081.769984,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8902.149632,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5764.613632,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 640, 11: 640, 12: 1159, 13: 571, 14: 1155, 15: 1108, 16: 576, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 2376, 22: 376, 23: 147})])",MACs,6009.521664,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 2426, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6326.78144,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5917.378048,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6678.906368,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 542, 16: 2449, 17: 1768, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 3072, 23: 147})])",MACs,7063.537152,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 1078, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8319.272448,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,6719.34208,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 1054, 20: 1670, 21: 453, 22: 3072, 23: 424})])",MACs,8245.806592,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 1108, 16: 2449, 17: 3072, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,7509.444096,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,6287.13216,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 424})])",MACs,6579.7504,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6277.498368,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5512.16896,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4993.844736,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 1108, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5147.46112,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 1078, 19: 1054, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,4931.716608,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 2407, 21: 453, 22: 840, 23: 3072})])",MACs,6933.382656,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5582.358016,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,5278.270976,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 542, 16: 2449, 17: 3072, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,7524.255232,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 640, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 2407, 21: 2376, 22: 840, 23: 3072})])",MACs,7943.22688,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 1730, 19: 537, 20: 2407, 21: 1633, 22: 376, 23: 1602})])",MACs,6431.31136,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5803.214336,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7682.655744,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,6813.517312,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 768, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 2376, 22: 1497, 23: 424})])",MACs,6398.936576,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 1773, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6797.460992,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 1119, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 568, 19: 537, 20: 562, 21: 453, 22: 3072, 23: 3072})])",MACs,7232.554496,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6332.02432,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8605.599232,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 1633, 22: 376, 23: 424})])",MACs,5690.295808,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8847.62368,top1_acc,-72.92418772563177 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 640, 11: 704, 12: 1159, 13: 571, 14: 589, 15: 1108, 16: 576, 17: 589, 18: 1078, 19: 1054, 20: 2407, 21: 453, 22: 840, 23: 3072})])",MACs,6252.72576,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 2409, 19: 2426, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,7321.552384,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8986.166784,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 640, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6754.600448,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1100, 18: 2409, 19: 1054, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6403.78624,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 562, 21: 2376, 22: 840, 23: 147})])",MACs,6125.127168,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 640, 8: 768, 9: 704, 10: 640, 11: 640, 12: 1159, 13: 571, 14: 1155, 15: 1108, 16: 1124, 17: 589, 18: 2409, 19: 2426, 20: 2407, 21: 2376, 22: 840, 23: 3072})])",MACs,7353.992704,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8902.149632,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,6815.155712,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8358.004224,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 2426, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,6233.982464,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6035.867136,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5403.837952,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,8673.560064,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 562, 21: 2376, 22: 840, 23: 147})])",MACs,6678.971904,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6335.759872,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4747.560448,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 2407, 21: 2376, 22: 840, 23: 3072})])",MACs,7390.299648,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4693.100032,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 1078, 19: 1054, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5359.076864,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 704, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 1108, 16: 576, 17: 589, 18: 568, 19: 1054, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5509.023232,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8874.886656,top1_acc,-72.92418772563177 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6195.774976,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1773, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,9135.916544,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,5373.101568,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5293.147648,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 640, 11: 640, 12: 1773, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 589, 18: 3072, 19: 3072, 20: 2407, 21: 2376, 22: 840, 23: 3072})])",MACs,8979.482112,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,6268.978688,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8276.215296,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 1054, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6437.406208,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4830.26688,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 3072, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 3072, 23: 3072})])",MACs,8154.187264,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 1119, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4775.806464,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8358.004224,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 1078, 19: 537, 20: 562, 21: 453, 22: 840, 23: 424})])",MACs,5046.797824,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 704, 12: 1773, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 3072, 23: 3072})])",MACs,9707.062784,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,6162.28608,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6815.221248,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 840, 23: 3072})])",MACs,5961.680384,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7048.070656,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 768, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 3072})])",MACs,7739.213312,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4749.854208,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 3072, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5396.039168,top1_acc,-62.454873646209386 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6086.723072,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8559.855104,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 768, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 2407, 21: 453, 22: 376, 23: 424})])",MACs,6391.66208,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6371.476992,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 1100, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,5402.461696,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 424})])",MACs,6710.101504,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8929.412608,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 2417, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,8103.527936,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 2407, 21: 453, 22: 376, 23: 424})])",MACs,6173.558272,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,7770.736128,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 424})])",MACs,6141.511168,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,7450.06848,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 1108, 16: 576, 17: 1768, 18: 2409, 19: 2426, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,7134.316032,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7436.96128,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5567.350272,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8618.509824,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5294.786048,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5000.529408,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 1054, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5538.05568,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6174.41024,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 589, 15: 1108, 16: 2449, 17: 589, 18: 1078, 19: 1054, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,6140.200448,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 2446, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8890.353152,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,9307.489792,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,6218.909184,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6282.741248,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 1100, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6321.21088,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 2426, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,6644.95872,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 3072, 18: 568, 19: 3072, 20: 1670, 21: 1633, 22: 840, 23: 3072})])",MACs,8346.27328,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5431.100928,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8618.509824,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8532.592128,top1_acc,-73.28519855595668 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 424})])",MACs,6367.544832,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 424})])",MACs,6483.478016,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8929.412608,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,7277.250048,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,7741.769216,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,7162.299904,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,6791.300608,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6195.774976,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,5679.810048,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 542, 16: 2449, 17: 1768, 18: 3072, 19: 2426, 20: 1670, 21: 2376, 22: 840, 23: 147})])",MACs,7826.5728,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 2407, 21: 453, 22: 376, 23: 424})])",MACs,6200.821248,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5961.811456,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7934.182912,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,5908.465152,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 453, 22: 840, 23: 3072})])",MACs,6565.594624,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7267.8784,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5984.880128,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,8285.259264,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 2407, 21: 453, 22: 376, 23: 147})])",MACs,5871.502848,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5458.298368,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5374.87104,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 3072, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 1497, 23: 3072})])",MACs,8125.875712,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4529.522176,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 562, 21: 2376, 22: 1497, 23: 147})])",MACs,6365.578752,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,6625.494528,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 589, 15: 542, 16: 576, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7317.227008,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,9040.692736,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 2426, 20: 2407, 21: 2376, 22: 1497, 23: 424})])",MACs,7331.44832,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,5573.7728,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6868.43648,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8587.11808,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6388.188672,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 1768, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,6405.75232,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5428.807168,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5892.408832,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 2376, 22: 376, 23: 424})])",MACs,5783.16032,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5984.880128,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8645.7728,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8180.270592,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,6618.08896,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6534.268416,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 768, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 2407, 21: 453, 22: 1497, 23: 424})])",MACs,6530.27072,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7859.602944,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5048.17408,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4556.785152,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,7269.320192,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5329.847808,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 2426, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6673.925632,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 576, 17: 1768, 18: 1730, 19: 3072, 20: 2407, 21: 453, 22: 840, 23: 3072})])",MACs,8242.595328,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 1768, 18: 568, 19: 3072, 20: 562, 21: 453, 22: 840, 23: 3072})])",MACs,7160.530432,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4913.432064,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8469.284352,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 3072, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,6884.4928,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 1155, 15: 542, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,7886.407168,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5403.837952,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6166.21824,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6787.958272,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5663.491584,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 3072, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7942.178304,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5564.92544,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,6463.09632,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 768, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6425.282048,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5863.310848,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5349.246464,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6193.481216,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 3072, 19: 3072, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,7160.268288,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,6908.151296,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5956.371968,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6092.621312,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,8441.366016,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 562, 21: 2376, 22: 1497, 23: 147})])",MACs,6458.83648,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8496.547328,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6168.512,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 768, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 2426, 20: 2407, 21: 2376, 22: 376, 23: 424})])",MACs,7111.050752,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,6127.093248,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,4885.906944,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6063.130112,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8820.360704,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,6249.12128,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5428.807168,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,9280.226816,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5512.16896,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 2426, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,6617.695744,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,7828.2112,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,8756.397568,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6787.958272,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 2400, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 3072, 18: 1730, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7601.849856,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 568, 19: 3072, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,6963.725824,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 2449, 17: 589, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,7211.058688,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5232.33024,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8126.203392,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 2449, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,6181.6192,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,6167.332352,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8614.381056,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 576, 17: 1768, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,7892.829696,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7290.48832,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,5603.395072,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6706.169344,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,6823.151104,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,6042.289664,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7726.95808,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6085.150208,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4981.65504,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8122.074624,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 424})])",MACs,6540.232192,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8248.95232,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 2449, 17: 3072, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7824.541184,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8956.675584,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4830.332416,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,5574.42816,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8385.2672,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6406.800896,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4749.854208,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6699.091456,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6222.972416,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5184.751104,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7487.686144,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5540.087296,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,6273.566208,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4665.77152,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,8211.400192,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,4920.37888,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5689.44384,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 147})])",MACs,7045.907968,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6400.312832,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 768, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,5686.363648,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,4913.16992,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4774.823424,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4800.77568,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7536.576,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,9013.42976,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6304.761344,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4638.57408,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8559.855104,top1_acc,-72.92418772563177 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,6751.979008,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6060.770816,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 1078, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5095.163392,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 3072})])",MACs,8072.791552,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,6041.765376,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 2376, 22: 376, 23: 147})])",MACs,5658.379776,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4722.591232,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8765.834752,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5323.359744,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 3072, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,7031.883264,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6193.481216,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6008.60416,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6084.429312,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5781.128704,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,6108.284416,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,6381.307392,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 1054, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4929.684992,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 424})])",MACs,6497.895936,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5854.070272,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 768, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 424})])",MACs,6893.274624,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 424})])",MACs,6622.02112,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4773.512704,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6226.707968,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6057.231872,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 2376, 22: 376, 23: 424})])",MACs,6069.487104,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 3072, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,6977.8816,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4638.508544,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,6313.084416,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 3072})])",MACs,6111.49568,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,8431.339008,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 3072, 18: 1078, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,6602.36032,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8469.284352,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4611.311104,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 3072, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,5547.099648,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5677.057536,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5103.027712,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6426.002944,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 1602})])",MACs,7811.8272,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 453, 22: 840, 23: 3072})])",MACs,5748.75392,top1_acc,-62.454873646209386 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,6896.94464,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5670.4384,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 424})])",MACs,5899.617792,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,7340.426752,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5428.807168,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4583.982592,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7898.6624,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5100.406272,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5346.166272,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6216.0256,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,7045.056,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,7313.360384,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5241.570816,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 2376, 22: 376, 23: 147})])",MACs,5701.436928,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,7004.75136,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 562, 21: 453, 22: 840, 23: 3072})])",MACs,7817.332224,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 424})])",MACs,6866.077184,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 424})])",MACs,6328.026624,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 1730, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5551.81824,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,7843.28448,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8343.062016,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 3072, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5299.308032,top1_acc,-62.093862815884485 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 1497, 23: 147})])",MACs,5489.23136,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 2376, 22: 376, 23: 147})])",MACs,5043.91424,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5663.950336,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 2449, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7363.626496,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5157.488128,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4939.38432,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6195.774976,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 1497, 23: 147})])",MACs,5461.968384,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,6495.798784,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5647.238656,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 3072})])",MACs,7990.806016,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8495.302144,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5487.199744,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6057.166336,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,9040.692736,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5239.342592,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 562, 21: 453, 22: 376, 23: 3072})])",MACs,8168.9984,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,6896.94464,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 1108, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 562, 21: 453, 22: 376, 23: 3072})])",MACs,7891.912192,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5075.764736,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 1768, 18: 2409, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,7127.893504,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6711.608832,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 1078, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8167.818752,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5377.885696,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6540.363264,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5622.203904,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5568.071168,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,4920.37888,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6084.429312,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 589, 15: 1108, 16: 1124, 17: 3072, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 840, 23: 3072})])",MACs,6938.494464,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6220.744192,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5280.302592,top1_acc,-63.1768953068592 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 589, 18: 1078, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,6617.236992,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8385.2672,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5961.811456,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 2417, 16: 576, 17: 589, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6133.384704,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5401.544192,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 1730, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5168.891392,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 1768, 18: 2409, 19: 537, 20: 562, 21: 453, 22: 376, 23: 3072})])",MACs,6240.208384,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8793.097728,top1_acc,-72.92418772563177 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6060.770816,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 768, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4774.823424,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 3072, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 1602})])",MACs,6922.700288,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7686.587904,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6651.643392,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 1155, 15: 3072, 16: 576, 17: 589, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6288.508416,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 3072, 20: 562, 21: 453, 22: 840, 23: 424})])",MACs,6266.684928,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5144.970752,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8303.478272,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 1155, 15: 3072, 16: 1124, 17: 3072, 18: 1078, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,6632.048128,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 840, 23: 3072})])",MACs,6943.344128,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,6150.81728,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,7046.432256,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 424})])",MACs,6752.372224,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 768, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 3072})])",MACs,9260.1728,top1_acc,-70.03610108303249 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 3072})])",MACs,5186.389504,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5619.97568,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 589, 18: 568, 19: 3072, 20: 562, 21: 453, 22: 376, 23: 1602})])",MACs,7271.286272,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6786.647552,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5049.091584,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 424})])",MACs,6020.597248,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 3072})])",MACs,6452.348416,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5214.30784,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7022.970368,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6708.659712,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,5523.047936,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 3072})])",MACs,6944.45824,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6038.160896,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,6087.640576,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,8381.531648,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5323.359744,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 3072, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,6037.11232,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6060.770816,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5184.751104,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 562, 21: 2376, 22: 376, 23: 424})])",MACs,6223.365632,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 589, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,6353.389056,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 1497, 23: 424})])",MACs,5775.492608,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 2449, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7326.926336,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5781.128704,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,5789.517312,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,7795.967488,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4668.06528,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 1078, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5122.426368,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5485.561344,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5296.096768,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5401.544192,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5649.79456,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5837.88288,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 1730, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6109.136384,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,6029.379072,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8443.004416,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,7031.9488,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6424.561152,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8303.478272,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 3072, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,6669.20704,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1730, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5674.567168,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 1078, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5532.419584,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 562, 21: 2376, 22: 376, 23: 424})])",MACs,6480.004608,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5673.911808,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4804.314624,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 768, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 2376, 22: 376, 23: 147})])",MACs,5098.440192,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,6060.3776,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6060.770816,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8440.776192,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 1078, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5554.308608,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5241.570816,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5513.938432,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6141.249024,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 3072})])",MACs,6392.907264,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,4829.152768,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,6214.3872,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,4801.889792,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5214.897664,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 1078, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5067.965952,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,6246.303232,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4720.297472,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,7000.098304,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5130.880512,top1_acc,-63.898916967509024 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 1078, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5954.340352,top1_acc,-69.31407942238266 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6277.498368,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 3072})])",MACs,9327.609344,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5500.569088,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5238.031872,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5956.371968,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5510.333952,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,4994.893312,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4804.38016,top1_acc,-62.8158844765343 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,6117.131776,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6464.800256,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5266.933248,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 424})])",MACs,6842.418688,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8902.149632,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 704, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6428.165632,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,8729.134592,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 589, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,7635.076608,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 768, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8902.149632,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,7697.597952,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,5966.792192,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4611.311104,top1_acc,-64.25992779783394 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7889.094144,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4665.77152,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,6518.932992,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 2376, 22: 1497, 23: 147})])",MACs,6289.950208,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6697.911808,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6057.166336,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 1078, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5858.19904,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,4729.800192,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 3072, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 3072})])",MACs,5729.09312,top1_acc,-62.454873646209386 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6891.0464,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7536.576,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 1078, 19: 537, 20: 1670, 21: 453, 22: 1497, 23: 147})])",MACs,5889.132032,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8478.066176,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 3072, 18: 1078, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6597.838336,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4695.328256,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8614.381056,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4695.328256,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 768, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,7342.58944,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5817.763328,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8522.56512,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5349.901824,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4584.048128,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 3072})])",MACs,7988.250112,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 768, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6480.528896,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4936.369664,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8559.855104,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 424})])",MACs,6725.109248,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4693.034496,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 424})])",MACs,6725.109248,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4638.508544,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 2449, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6429.0176,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6863.783424,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 3072, 16: 1124, 17: 589, 18: 2409, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5826.020864,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 3072})])",MACs,9178.383872,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,4937.483776,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6277.498368,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 571, 14: 589, 15: 542, 16: 576, 17: 3072, 18: 568, 19: 537, 20: 562, 21: 453, 22: 840, 23: 147})])",MACs,5570.299392,top1_acc,-62.093862815884485 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 1768, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,8018.855424,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6347.0976,top1_acc,-71.11913357400722 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5350.62272,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6616.12288,top1_acc,-72.92418772563177 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8532.592128,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6359.287296,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 3072, 18: 1078, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7453.607424,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,6033.114624,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5473.371648,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,4883.613184,top1_acc,-65.34296028880865 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7519.077888,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 2449, 17: 3072, 18: 2409, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7425.885696,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6604.719616,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4668.06528,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5732.566528,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6697.911808,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8904.377856,top1_acc,-72.20216606498195 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 147})])",MACs,7325.091328,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8505.329152,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 2409, 19: 537, 20: 562, 21: 2376, 22: 1497, 23: 147})])",MACs,6461.064704,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4664.526336,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 1078, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5583.341056,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4668.06528,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6060.770816,top1_acc,-68.59205776173285 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6220.744192,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7088.834048,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6304.761344,top1_acc,-70.3971119133574 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 768, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5076.747776,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5321.065984,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8820.360704,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 1078, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5040.702976,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4638.57408,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8752.92416,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 2376, 22: 840, 23: 3072})])",MACs,8910.669312,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4668.06528,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 2449, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,6615.46752,top1_acc,-66.4259927797834 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 576, 17: 3072, 18: 3072, 19: 3072, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,7595.165184,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 1159, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 1078, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,5722.53952,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,5839.324672,top1_acc,-64.98194945848375 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6411.585024,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8847.62368,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 2376, 22: 1497, 23: 147})])",MACs,6918.309376,top1_acc,-72.56317689530685 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 2426, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8405.58336,top1_acc,-70.7581227436823 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 424})])",MACs,6809.388544,top1_acc,-69.67509025270758 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,4940.432896,top1_acc,-67.14801444043322 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5157.553664,top1_acc,-68.23104693140795 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 768, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6238.045696,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4556.785152,top1_acc,-64.62093862815884 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 3072, 16: 1124, 17: 3072, 18: 568, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,7797.016064,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 589, 15: 542, 16: 2449, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,6874.99008,top1_acc,-67.87003610108303 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,6292.571648,top1_acc,-70.7581227436823 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17: 1768, 18: 2409, 19: 537, 20: 1670, 21: 2376, 22: 376, 23: 147})])",MACs,6567.560704,top1_acc,-71.48014440433214 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 424})])",MACs,4665.77152,top1_acc,-66.06498194945848 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 1155, 15: 542, 16: 576, 17: 1768, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5226.694144,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 704, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 1054, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,4631.168512,top1_acc,-63.537906137184116 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 589, 15: 542, 16: 2449, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,8258.979328,top1_acc,-68.95306859205776 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 768, 10: 512, 11: 640, 12: 608, 13: 1119, 14: 589, 15: 542, 16: 1124, 17: 589, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5782.242816,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 2400, 13: 3072, 14: 1155, 15: 3072, 16: 1124, 17: 3072, 18: 3072, 19: 3072, 20: 1670, 21: 453, 22: 840, 23: 3072})])",MACs,8643.872256,top1_acc,-71.84115523465704 +"OrderedDict([(, {0: 576, 1: 768, 2: 704, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 3072, 18: 3072, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 3072})])",MACs,7204.505088,top1_acc,-67.50902527075813 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 3072, 14: 1155, 15: 542, 16: 1124, 17: 589, 18: 1078, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 424})])",MACs,5694.621184,top1_acc,-66.78700361010831 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 704, 9: 704, 10: 512, 11: 640, 12: 608, 13: 571, 14: 589, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 1670, 21: 453, 22: 376, 23: 147})])",MACs,4856.415744,top1_acc,-65.70397111913357 +"OrderedDict([(, {0: 576, 1: 576, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 576, 8: 768, 9: 704, 10: 512, 11: 704, 12: 608, 13: 2426, 14: 1155, 15: 542, 16: 576, 17: 589, 18: 568, 19: 537, 20: 562, 21: 453, 22: 376, 23: 147})])",MACs,5114.562048,top1_acc,-62.093862815884485 +"OrderedDict([(, {0: 576, 1: 576, 2: 704, 3: 768, 4: 704, 5: 768, 6: 768, 7: 576, 8: 704, 9: 704, 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+license: apache-2.0 +tags: +- generated_from_trainer +datasets: +- squad +model-index: +- name: first_try + results: [] +--- + + + +# first_try + +This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the squad dataset. + +## Model description + +More information needed + +## Intended uses & limitations + +More information needed + +## Training and evaluation data + +More information needed + +## Training procedure + +### Training hyperparameters + +The following hyperparameters were used during training: +- learning_rate: 3e-05 +- train_batch_size: 16 +- eval_batch_size: 128 +- seed: 42 +- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 +- lr_scheduler_type: linear +- num_epochs: 8 +- mixed_precision_training: Native AMP + +### Training results + + + +### Framework versions + +- Transformers 4.29.1 +- Pytorch 1.12.1 +- Datasets 2.13.1 +- Tokenizers 0.13.3 diff --git a/eftnas-s1-bert-base-squadv1/all_results.json b/eftnas-s1-bert-base-squadv1/all_results.json new file mode 100644 index 0000000000000000000000000000000000000000..cd7479af248ede4fdbd45df94d1912b3e98d1ac4 --- /dev/null +++ b/eftnas-s1-bert-base-squadv1/all_results.json @@ -0,0 +1,14 @@ +{ + "epoch": 3.0, + "eval_exact_match": 80.43519394512772, + "eval_f1": 87.97377271576424, + "eval_runtime": 20.7453, + "eval_samples": 10784, + "eval_samples_per_second": 519.83, + "eval_steps_per_second": 4.097, + "train_loss": 0.563158837906804, + "train_runtime": 32896.2087, + "train_samples": 88524, + "train_samples_per_second": 8.073, + "train_steps_per_second": 0.505 +} \ No newline at end of file diff --git a/eftnas-s1-bert-base-squadv1/cache_MACs.csv b/eftnas-s1-bert-base-squadv1/cache_MACs.csv new file mode 100644 index 0000000000000000000000000000000000000000..42e06a3fa4d5b743e4706945a65dcb9cf5e6f4ad --- /dev/null +++ b/eftnas-s1-bert-base-squadv1/cache_MACs.csv @@ -0,0 +1,980 @@ +"(0, 0, 2, 0, 0, 2, 1, 0, 1, 1, 2, 0, 0, 0, 3, 3, 1, 2, 0, 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2)",24120.262656 +"(1, 1, 1, 2, 1, 0, 1, 1, 1, 1, 2, 0, 0, 0, 3, 1, 2, 2, 1, 3, 2, 1, 3, 2)",22356.099072 +"(1, 1, 0, 1, 2, 1, 1, 1, 1, 0, 1, 1, 1, 3, 1, 0, 2, 3, 2, 2, 3, 2, 2, 0)",22228.697088 +"(1, 1, 0, 2, 0, 2, 0, 1, 0, 1, 0, 0, 3, 3, 2, 3, 2, 2, 2, 1, 1, 3, 0, 2)",23089.840128 +"(1, 1, 0, 2, 0, 2, 1, 1, 0, 0, 0, 0, 0, 1, 2, 1, 0, 1, 1, 1, 0, 2, 2, 3)",26929.004544 +"(1, 1, 2, 0, 2, 1, 0, 1, 1, 0, 1, 0, 3, 1, 0, 3, 1, 2, 0, 2, 2, 2, 2, 2)",22921.740288 +"(1, 1, 2, 2, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 2, 3, 1, 2, 1, 0, 3, 0, 3)",24262.41024 +"(1, 1, 2, 2, 1, 0, 0, 0, 0, 0, 2, 1, 1, 2, 0, 3, 2, 1, 0, 3, 2, 2, 3, 2)",22983.671808 +"(1, 1, 1, 1, 1, 2, 1, 0, 1, 0, 1, 1, 0, 1, 0, 3, 0, 2, 2, 0, 3, 3, 1, 2)",22964.207616 +"(1, 1, 1, 2, 0, 2, 1, 1, 1, 0, 2, 0, 1, 0, 1, 1, 1, 3, 1, 2, 2, 2, 2, 3)",23243.784192 +"(1, 0, 0, 2, 0, 2, 1, 1, 0, 0, 0, 0, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 1, 1)",19753.20576 +"(1, 1, 1, 2, 0, 2, 0, 1, 1, 0, 2, 0, 0, 2, 2, 2, 3, 1, 3, 3, 2, 1, 2, 0)",23193.059328 +"(1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 2, 0, 0, 3, 0, 1, 2, 3, 2, 3, 3, 1, 3, 0)",23905.56672 +"(1, 1, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 2, 3, 3, 2, 2, 1, 2, 3, 0, 2)",25738.739712 +"(1, 1, 2, 2, 2, 1, 1, 0, 0, 0, 0, 0, 1, 3, 0, 2, 0, 2, 1, 0, 1, 3, 0, 0)",27777.76128 +"(0, 0, 2, 2, 0, 2, 1, 1, 1, 1, 2, 0, 3, 3, 3, 2, 3, 2, 1, 1, 1, 3, 0, 2)",21611.15136 +"(0, 1, 1, 2, 0, 0, 1, 0, 1, 0, 2, 1, 2, 2, 1, 3, 0, 1, 1, 3, 0, 2, 2, 1)",23828.8896 +"(0, 0, 0, 2, 2, 0, 1, 0, 0, 1, 2, 0, 1, 3, 1, 0, 3, 2, 2, 1, 3, 3, 1, 3)",23144.103936 +"(1, 1, 1, 2, 0, 0, 1, 1, 1, 0, 2, 1, 0, 0, 1, 0, 1, 3, 1, 1, 2, 2, 2, 3)",23920.902144 +"(0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 2, 2, 0, 1, 2, 1, 0, 2, 2, 0, 2, 1)",26834.04288 +"(1, 1, 2, 1, 1, 0, 1, 0, 0, 0, 2, 0, 1, 2, 0, 3, 2, 1, 0, 2, 0, 2, 3, 2)",24650.514432 +"(1, 1, 0, 2, 0, 1, 1, 1, 1, 0, 2, 0, 2, 0, 2, 3, 3, 1, 0, 2, 0, 0, 0, 2)",25890.32448 +"(1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 2, 0, 0, 0, 3, 0, 1, 1, 1, 3, 2, 1, 3, 2)",24290.131968 +"(1, 1, 1, 2, 0, 0, 1, 1, 1, 0, 2, 0, 1, 0, 1, 1, 2, 3, 1, 2, 2, 2, 2, 3)",23403.626496 +"(1, 1, 2, 1, 1, 0, 1, 0, 0, 0, 2, 1, 0, 2, 0, 3, 2, 1, 0, 1, 0, 2, 0, 2)",26189.365248 +"(0, 1, 1, 0, 0, 2, 1, 0, 1, 1, 2, 0, 3, 1, 3, 1, 0, 2, 1, 3, 2, 1, 1, 2)",23174.18496 +"(1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 2, 0, 3, 1, 0, 3, 2, 1, 0, 1, 1)",25640.828928 +"(1, 1, 1, 2, 2, 0, 0, 0, 1, 0, 0, 1, 2, 1, 2, 0, 0, 2, 0, 0, 1, 1, 0, 0)",29409.214464 +"(1, 1, 2, 2, 2, 0, 1, 1, 1, 0, 2, 1, 2, 2, 1, 3, 0, 1, 1, 2, 0, 2, 2, 1)",23093.379072 +"(1, 0, 0, 2, 0, 2, 1, 1, 0, 0, 0, 0, 3, 3, 3, 3, 3, 3, 3, 1, 2, 2, 0, 1)",21622.94784 +"(1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 2, 1, 0, 1, 0, 1, 0, 0, 2, 1)",29534.257152 +"(1, 1, 1, 2, 1, 0, 0, 1, 1, 1, 2, 0, 0, 0, 3, 1, 2, 2, 1, 3, 2, 1, 2, 0)",24500.699136 +"(0, 1, 1, 2, 0, 0, 1, 0, 0, 0, 2, 0, 2, 2, 1, 3, 0, 0, 0, 3, 0, 2, 2, 1)",25299.320832 +"(0, 1, 0, 2, 1, 1, 1, 0, 0, 1, 2, 0, 3, 2, 0, 1, 2, 3, 2, 0, 1, 0, 2, 1)",24749.01504 +"(0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 0, 1, 2, 3, 1, 2, 0, 0, 1, 3, 3, 2, 3)",25815.416832 +"(0, 0, 2, 2, 0, 2, 1, 1, 0, 1, 2, 0, 3, 3, 3, 2, 2, 0, 0, 1, 1, 3, 0, 2)",23395.958784 +"(1, 0, 0, 2, 0, 2, 1, 1, 1, 0, 0, 0, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 1, 1)",19375.7184 +"(1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 2, 1, 0, 1, 0, 1, 0, 2, 2, 2)",28424.798208 +"(1, 1, 1, 2, 1, 0, 1, 1, 1, 1, 2, 0, 0, 0, 3, 1, 2, 1, 0, 3, 2, 1, 0, 2)",24616.30464 +"(1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 3, 0, 1, 1, 3, 1, 2, 3, 2, 3, 0, 2)",25009.717248 +"(0, 1, 1, 2, 1, 0, 0, 0, 1, 1, 0, 1, 2, 1, 3, 0, 0, 1, 2, 2, 1, 0, 0, 0)",28426.56768 +"(1, 1, 0, 2, 0, 2, 0, 1, 0, 1, 0, 0, 3, 3, 2, 3, 2, 2, 2, 1, 1, 3, 3, 2)",21516.189696 +"(0, 1, 0, 2, 2, 2, 1, 0, 1, 1, 1, 1, 1, 3, 1, 3, 1, 0, 3, 3, 3, 0, 1, 0)",23303.356416 +"(1, 0, 2, 0, 1, 0, 1, 1, 0, 0, 1, 1, 3, 3, 0, 0, 0, 2, 3, 2, 2, 2, 2, 2)",22281.781248 +"(1, 1, 0, 2, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 3, 1, 2, 2, 1, 1, 3, 0, 0)",28227.207168 +"(1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 2, 0, 1, 2, 0, 3, 2, 2, 0, 2, 0, 2, 3, 2)",24306.64704 +"(0, 0, 2, 2, 0, 2, 1, 1, 1, 1, 2, 0, 0, 3, 3, 2, 3, 2, 1, 1, 1, 3, 2, 2)",21384.658944 +"(0, 1, 1, 2, 1, 2, 1, 1, 0, 0, 2, 0, 2, 2, 0, 1, 3, 1, 1, 2, 2, 2, 2, 3)",22842.703872 +"(0, 1, 0, 2, 0, 0, 1, 1, 1, 1, 0, 1, 1, 2, 3, 1, 1, 0, 0, 1, 3, 0, 3, 2)",25139.478528 +"(0, 0, 2, 2, 0, 2, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 2, 1, 1, 1, 1, 3, 0, 2)",21379.350528 +"(0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 2, 0, 2, 2, 0, 2, 3, 1, 0, 2, 2, 0, 2, 3)",24687.673344 +"(0, 1, 2, 2, 1, 1, 0, 1, 1, 1, 0, 1, 0, 2, 1, 1, 1, 0, 0, 1, 0, 0, 2, 0)",28671.34464 +"(0, 0, 2, 2, 0, 2, 1, 1, 1, 1, 2, 0, 3, 3, 3, 3, 3, 2, 1, 1, 1, 3, 0, 2)",21064.974336 +"(1, 0, 2, 2, 2, 2, 0, 0, 0, 1, 2, 1, 3, 3, 3, 0, 3, 0, 0, 2, 1, 2, 1, 2)",21982.74048 +"(1, 1, 2, 2, 1, 2, 1, 1, 0, 0, 2, 1, 0, 2, 0, 3, 2, 1, 1, 1, 0, 2, 3, 3)",23119.921152 +"(0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 2, 0, 2, 1, 0, 1, 1, 2, 1, 2, 2, 0, 3, 1)",26373.98016 +"(1, 1, 1, 2, 0, 0, 0, 1, 1, 0, 0, 0, 1, 3, 2, 3, 3, 2, 3, 1, 2, 3, 2, 2)",21546.27072 +"(1, 1, 2, 2, 2, 1, 0, 0, 1, 1, 1, 1, 2, 1, 0, 2, 2, 2, 0, 0, 1, 1, 0, 3)",25462.112256 +"(0, 0, 2, 2, 1, 1, 0, 0, 1, 1, 1, 1, 2, 3, 3, 0, 3, 0, 0, 2, 1, 2, 1, 2)",22906.994688 +"(1, 0, 0, 2, 0, 0, 0, 1, 1, 0, 2, 0, 1, 2, 1, 3, 3, 1, 2, 3, 0, 1, 2, 2)",24264.179712 +"(1, 1, 2, 2, 2, 2, 0, 0, 1, 1, 2, 1, 3, 1, 3, 2, 2, 1, 2, 2, 1, 0, 0, 3)",23223.140352 +"(0, 0, 1, 0, 2, 0, 1, 1, 0, 0, 2, 1, 2, 2, 3, 3, 0, 3, 1, 2, 2, 2, 2, 1)",21999.255552 +"(0, 1, 2, 1, 1, 1, 0, 0, 1, 0, 2, 0, 2, 1, 3, 2, 2, 1, 2, 2, 2, 0, 0, 3)",25231.491072 +"(0, 1, 1, 2, 1, 1, 0, 0, 0, 1, 1, 1, 2, 1, 0, 1, 1, 1, 0, 2, 1, 0, 0, 1)",27927.576576 +"(1, 0, 0, 2, 0, 1, 1, 1, 0, 0, 0, 0, 3, 3, 0, 3, 3, 2, 3, 3, 2, 2, 1, 1)",21519.72864 +"(1, 0, 2, 2, 1, 2, 0, 0, 0, 1, 2, 1, 3, 3, 3, 0, 3, 0, 0, 2, 1, 2, 1, 2)",22171.48416 +"(0, 1, 0, 2, 1, 1, 1, 1, 0, 0, 2, 0, 2, 2, 0, 1, 3, 1, 1, 2, 2, 2, 1, 3)",23862.509568 +"(1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 2, 0, 3, 2, 1, 0, 1, 0, 2, 3, 2)",25936.920576 +"(0, 0, 1, 2, 0, 2, 1, 1, 1, 1, 2, 0, 0, 3, 1, 1, 3, 2, 1, 1, 1, 3, 2, 2)",22819.700736 +"(1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 2, 1, 0, 1, 0, 3, 2, 1, 2, 2)",26441.80992 +"(1, 0, 1, 0, 2, 0, 1, 1, 1, 0, 2, 0, 2, 3, 3, 3, 0, 2, 1, 1, 1, 3, 2, 1)",22645.702656 +"(1, 0, 2, 2, 0, 2, 1, 1, 1, 0, 2, 0, 3, 3, 3, 3, 3, 1, 3, 3, 2, 2, 0, 1)",19911.278592 +"(1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 0, 1, 2, 0, 1, 0, 1, 0, 1, 0, 2, 3, 2)",27778.351104 +"(0, 0, 2, 2, 0, 0, 0, 1, 0, 0, 0, 0, 0, 2, 1, 1, 1, 0, 0, 1, 0, 3, 2, 3)",28175.302656 +"(0, 0, 0, 2, 0, 0, 1, 0, 0, 0, 0, 0, 0, 3, 1, 0, 0, 2, 2, 1, 0, 2, 1, 2)",27971.813376 +"(1, 1, 1, 2, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 2, 1, 2, 2, 1, 3, 2, 1, 2, 2)",24152.702976 +"(1, 0, 2, 2, 1, 2, 0, 0, 0, 1, 2, 1, 0, 3, 1, 0, 3, 0, 0, 2, 1, 2, 1, 2)",24232.91904 +"(0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 2, 0, 1, 2, 1, 0, 2, 2, 0, 2, 1)",27738.832896 +"(0, 0, 2, 2, 0, 2, 1, 1, 0, 1, 2, 0, 3, 3, 3, 3, 3, 3, 1, 1, 1, 3, 0, 2)",20919.287808 +"(0, 1, 0, 2, 0, 2, 1, 1, 1, 1, 0, 0, 0, 1, 2, 1, 2, 1, 1, 1, 0, 2, 2, 3)",25703.940096 +"(0, 0, 0, 2, 0, 2, 1, 1, 0, 0, 0, 0, 3, 2, 3, 3, 3, 3, 1, 3, 2, 2, 1, 1)",21540.37248 +"(1, 1, 0, 2, 0, 2, 1, 1, 0, 0, 0, 0, 0, 1, 2, 1, 0, 1, 0, 1, 0, 2, 2, 1)",27535.93344 +"(1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 2, 1, 0, 2, 0, 3, 2, 1, 0, 1, 0, 2, 3, 2)",24898.830336 +"(1, 0, 2, 0, 1, 2, 1, 1, 1, 0, 1, 0, 3, 3, 3, 3, 1, 3, 3, 2, 2, 2, 2, 2)",19169.28 +"(1, 1, 2, 2, 2, 2, 1, 1, 0, 0, 2, 1, 0, 2, 0, 3, 2, 1, 1, 1, 0, 2, 3, 3)",22931.177472 +"(0, 0, 1, 2, 0, 2, 1, 1, 0, 1, 2, 0, 2, 3, 1, 0, 3, 2, 2, 1, 3, 3, 2, 3)",21219.508224 +"(0, 1, 2, 2, 0, 0, 1, 1, 1, 1, 2, 1, 1, 2, 3, 1, 1, 0, 0, 1, 3, 0, 3, 2)",23818.272768 +"(1, 0, 2, 0, 0, 1, 1, 1, 1, 0, 0, 1, 3, 3, 3, 2, 3, 1, 3, 3, 2, 3, 2, 2)",19382.206464 +"(1, 1, 1, 2, 1, 0, 1, 0, 0, 1, 2, 0, 0, 1, 3, 1, 2, 2, 1, 1, 0, 2, 3, 2)",24339.08736 +"(0, 0, 2, 2, 0, 2, 1, 1, 1, 1, 2, 1, 3, 2, 1, 3, 3, 1, 1, 2, 0, 2, 0, 2)",22550.740992 +"(0, 0, 0, 2, 0, 2, 1, 1, 0, 1, 0, 1, 3, 3, 3, 3, 2, 3, 1, 1, 1, 3, 1, 2)",21221.277696 +"(1, 1, 2, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 2, 3, 2, 1, 0, 2, 0, 0, 2, 1)",26406.42048 +"(0, 1, 0, 2, 1, 1, 0, 1, 1, 1, 0, 1, 1, 2, 3, 1, 2, 0, 0, 1, 3, 0, 2, 0)",26311.458816 +"(1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 2, 0, 2, 1, 2, 1, 3, 1, 0, 1, 3, 3, 2, 3)",22692.298752 +"(1, 1, 1, 2, 1, 0, 0, 1, 1, 0, 2, 0, 1, 3, 3, 3, 3, 2, 3, 1, 2, 3, 3, 2)",19749.666816 +"(0, 0, 2, 2, 2, 1, 0, 1, 0, 0, 0, 0, 3, 2, 3, 1, 2, 0, 0, 1, 0, 3, 2, 3)",24952.50432 +"(1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 2, 0, 2, 2, 0, 3, 2, 2, 0, 2, 0, 2, 3, 2)",23401.857024 +"(1, 0, 0, 2, 0, 2, 1, 1, 1, 0, 0, 0, 3, 3, 3, 3, 3, 2, 3, 3, 2, 2, 1, 1)",19898.892288 +"(1, 0, 2, 2, 0, 2, 1, 1, 0, 0, 2, 1, 3, 3, 3, 3, 0, 1, 1, 1, 1, 3, 0, 2)",22604.414976 +"(1, 1, 1, 2, 1, 2, 1, 1, 1, 0, 2, 0, 2, 3, 0, 1, 3, 1, 3, 2, 2, 2, 2, 3)",20678.049792 +"(1, 1, 2, 1, 1, 1, 0, 1, 0, 0, 2, 1, 0, 2, 0, 3, 2, 1, 1, 1, 0, 0, 3, 3)",25118.244864 +"(1, 0, 2, 0, 1, 1, 1, 1, 1, 0, 0, 1, 3, 3, 1, 1, 3, 1, 3, 3, 2, 3, 2, 2)",20534.132736 +"(0, 0, 2, 2, 1, 1, 0, 0, 0, 1, 1, 0, 2, 3, 3, 2, 2, 1, 2, 2, 2, 0, 2, 3)",23195.418624 +"(1, 1, 2, 0, 1, 1, 1, 1, 1, 0, 1, 1, 3, 1, 0, 3, 1, 2, 3, 2, 1, 2, 0, 2)",22642.753536 +"(1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 2, 0, 1, 1, 1, 0, 1, 0, 2, 3, 2)",27479.90016 +"(0, 1, 2, 2, 0, 0, 0, 1, 1, 1, 2, 1, 1, 2, 3, 1, 1, 0, 0, 1, 3, 3, 3, 2)",22714.712064 +"(1, 1, 2, 1, 1, 1, 1, 1, 0, 0, 2, 1, 2, 2, 0, 3, 2, 1, 1, 1, 3, 0, 3, 3)",22727.098368 +"(1, 0, 1, 2, 2, 0, 1, 1, 1, 0, 2, 1, 2, 2, 1, 3, 0, 1, 1, 2, 0, 2, 2, 1)",23659.610112 +"(1, 1, 1, 2, 1, 2, 1, 1, 1, 0, 2, 0, 2, 3, 0, 1, 3, 3, 3, 2, 2, 2, 2, 1)",20075.249664 +"(1, 0, 2, 0, 1, 1, 1, 1, 1, 0, 1, 0, 3, 3, 3, 1, 1, 3, 3, 1, 2, 2, 2, 2)",20788.936704 +"(1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 2, 0, 3, 2, 1, 0, 1, 0, 2, 2, 2)",26822.2464 +"(1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 2, 2, 3, 3, 2, 0, 1, 2, 3, 3, 2)",22413.312 +"(1, 1, 1, 2, 1, 2, 1, 0, 0, 0, 2, 0, 2, 2, 0, 1, 3, 1, 1, 2, 2, 2, 2, 3)",23031.447552 +"(1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 3, 3, 3, 2, 3, 1, 3, 1, 0, 3, 2, 2)",22098.345984 +"(1, 0, 2, 0, 0, 1, 1, 1, 0, 0, 0, 0, 3, 3, 0, 3, 1, 2, 3, 3, 2, 2, 2, 2)",21765.685248 +"(0, 1, 0, 2, 0, 2, 0, 1, 0, 0, 0, 0, 0, 3, 1, 3, 2, 0, 2, 1, 1, 3, 2, 2)",24740.16768 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 1, 0, 0, 1, 3, 2, 3, 2, 2, 2, 1, 1, 3, 0, 2)",24635.768832 +"(0, 0, 0, 2, 0, 0, 1, 1, 1, 1, 0, 0, 1, 2, 3, 1, 1, 0, 0, 1, 3, 0, 2, 2)",26496.663552 +"(0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 2, 1, 0, 2, 0, 3, 2, 1, 0, 1, 0, 2, 2, 2)",25878.528 +"(0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 2, 3, 3, 3, 0, 3, 3, 3, 2, 2, 1, 1)",22722.379776 +"(1, 0, 1, 0, 2, 0, 1, 1, 1, 0, 2, 1, 2, 2, 1, 1, 0, 1, 1, 2, 0, 0, 2, 1)",26322.665472 +"(0, 1, 1, 2, 1, 2, 1, 1, 0, 0, 0, 0, 2, 2, 0, 1, 3, 1, 3, 2, 2, 2, 2, 2)",22850.961408 +"(1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 2, 0, 1, 2, 0, 1, 0, 1, 0, 1, 0, 2, 3, 2)",27589.607424 +"(1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 2, 3, 2, 1, 0, 1, 3, 1, 0, 2, 2, 3)",24521.342976 +"(1, 1, 2, 2, 1, 2, 0, 1, 1, 0, 2, 0, 0, 1, 0, 3, 2, 1, 1, 1, 0, 2, 2, 3)",24521.9328 +"(1, 1, 1, 2, 1, 0, 1, 1, 1, 0, 2, 0, 1, 3, 3, 3, 3, 2, 3, 1, 2, 0, 3, 2)",20853.22752 +"(0, 0, 1, 2, 0, 2, 0, 1, 0, 1, 2, 0, 0, 3, 1, 0, 3, 2, 2, 1, 0, 3, 2, 3)",23610.65472 +"(1, 1, 1, 0, 2, 0, 1, 1, 1, 0, 2, 1, 2, 2, 1, 3, 0, 2, 1, 2, 0, 2, 2, 1)",23221.37088 +"(1, 0, 0, 2, 0, 2, 1, 1, 1, 0, 0, 0, 3, 3, 3, 3, 3, 1, 3, 3, 2, 2, 1, 3)",19978.518528 +"(0, 0, 2, 2, 1, 2, 0, 1, 0, 0, 0, 0, 0, 2, 1, 3, 2, 0, 0, 2, 0, 3, 2, 3)",25583.026176 +"(1, 1, 0, 2, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 2, 3, 3)",27212.709888 +"(1, 1, 1, 2, 0, 0, 0, 0, 1, 0, 2, 0, 0, 3, 0, 3, 2, 1, 3, 1, 0, 2, 2, 2)",24031.789056 +"(0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 2, 0, 1, 2, 0, 1, 0, 1, 0, 1, 0, 2, 3, 2)",27589.607424 +"(1, 1, 2, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 2, 1, 0, 1, 0, 3, 2, 0, 2, 1)",26818.117632 +"(1, 0, 2, 0, 1, 1, 1, 1, 1, 0, 1, 1, 3, 3, 3, 2, 3, 1, 3, 2, 2, 3, 2, 2)",18929.811456 +"(1, 0, 2, 2, 1, 1, 0, 1, 0, 1, 0, 0, 3, 2, 2, 1, 2, 2, 0, 1, 0, 3, 3, 3)",23978.704896 +"(1, 1, 1, 2, 1, 2, 0, 1, 1, 0, 2, 0, 3, 3, 3, 3, 3, 2, 3, 1, 2, 3, 3, 2)",18203.738112 +"(1, 1, 2, 0, 1, 2, 1, 1, 1, 0, 1, 1, 3, 3, 3, 3, 1, 3, 3, 2, 2, 2, 3, 2)",17812.094976 +"(1, 1, 1, 2, 0, 2, 1, 1, 0, 1, 2, 0, 2, 3, 1, 0, 3, 2, 2, 1, 3, 3, 3, 3)",20239.81056 +"(1, 0, 1, 2, 2, 2, 1, 1, 1, 0, 2, 1, 3, 2, 3, 3, 3, 3, 1, 2, 2, 2, 2, 1)",18652.594176 +"(0, 1, 2, 2, 0, 0, 1, 1, 1, 1, 2, 1, 1, 2, 3, 3, 1, 0, 0, 1, 3, 2, 3, 2)",21627.076608 +"(1, 0, 2, 0, 1, 1, 1, 1, 1, 0, 2, 1, 3, 3, 1, 1, 3, 1, 1, 3, 2, 3, 2, 3)",20525.8752 +"(1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 2, 0, 3, 2, 1, 0, 1, 0, 2, 3, 2)",26125.664256 +"(1, 1, 1, 2, 0, 2, 0, 1, 1, 0, 2, 0, 0, 1, 0, 1, 3, 1, 0, 2, 2, 0, 2, 1)",25690.963968 +"(0, 1, 0, 2, 1, 0, 1, 1, 0, 0, 2, 0, 2, 2, 0, 1, 3, 1, 1, 2, 2, 2, 1, 3)",24239.996928 +"(1, 1, 1, 2, 0, 0, 0, 1, 1, 0, 0, 0, 1, 3, 2, 3, 3, 2, 3, 1, 2, 2, 3, 2)",21653.618688 +"(1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 3, 3, 3, 2, 0, 1, 0, 1, 2, 3, 2, 2)",23417.192448 +"(1, 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0, 0, 1, 3, 3, 0, 1, 3, 1, 3, 1, 0, 3, 3, 2)",22103.064576 +"(1, 0, 1, 0, 2, 0, 1, 1, 1, 0, 2, 1, 2, 3, 3, 2, 0, 1, 1, 2, 0, 2, 2, 1)",23190.700032 +"(0, 0, 1, 0, 2, 1, 1, 1, 0, 0, 2, 1, 2, 2, 3, 3, 0, 3, 1, 2, 2, 2, 2, 1)",21621.768192 +"(0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 2, 0, 1, 2, 0, 1, 0, 1, 0, 1, 0, 3, 2, 2)",27482.259456 +"(1, 1, 2, 1, 0, 1, 0, 1, 1, 0, 2, 0, 1, 2, 0, 1, 3, 1, 3, 2, 0, 2, 3, 2)",23290.970112 +"(0, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 0, 2, 3, 1, 3, 3, 2, 3, 1, 3, 3, 3, 3)",18368.299008 +"(1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 3, 2, 3, 3, 2, 3, 3, 2, 0, 2, 3, 2)",19506.659328 +"(1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 1, 2, 2, 3, 2, 1)",17188.061184 +"(1, 1, 2, 1, 0, 1, 1, 1, 0, 0, 0, 1, 3, 2, 3, 3, 2, 1, 0, 1, 2, 2, 3, 2)",21735.0144 +"(1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 2, 0, 1, 0, 1, 0, 1, 0, 2, 3, 2)",27166.113792 +"(0, 1, 2, 2, 0, 2, 1, 1, 0, 1, 2, 1, 1, 2, 3, 3, 1, 0, 0, 1, 3, 2, 3, 2)",21438.332928 +"(1, 1, 1, 2, 1, 2, 0, 1, 1, 0, 0, 0, 3, 3, 3, 3, 3, 2, 3, 1, 2, 3, 3, 2)",19053.084672 +"(0, 1, 2, 2, 0, 0, 1, 1, 1, 1, 2, 1, 1, 2, 3, 3, 1, 0, 0, 1, 3, 3, 3, 2)",21295.005696 +"(0, 0, 2, 2, 1, 2, 1, 1, 1, 0, 0, 0, 3, 2, 3, 3, 2, 3, 0, 2, 2, 3, 2, 3)",20634.402816 +"(1, 1, 2, 0, 1, 2, 1, 1, 1, 0, 1, 1, 3, 3, 3, 3, 2, 3, 3, 2, 2, 2, 3, 2)",17405.70624 +"(1, 1, 2, 1, 1, 1, 1, 1, 0, 0, 2, 1, 2, 2, 0, 3, 2, 3, 1, 2, 3, 2, 3, 3)",20039.2704 +"(1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 1, 2, 3, 2, 0, 1, 0, 3, 2, 2, 2, 2)",25057.492992 +"(1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 2, 1, 0, 2, 0, 3, 2, 1, 0, 1, 0, 2, 3, 2)",24710.086656 +"(1, 0, 2, 0, 1, 1, 1, 1, 1, 0, 1, 1, 3, 2, 1, 3, 3, 1, 3, 2, 2, 3, 2, 2)",19870.580736 +"(0, 0, 0, 2, 0, 2, 1, 1, 0, 1, 2, 0, 1, 2, 1, 0, 1, 0, 2, 1, 3, 0, 2, 3)",25718.685696 +"(0, 1, 2, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 1, 0, 0, 1, 3, 2, 3, 2)",21194.145792 +"(1, 1, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 1, 0, 1, 0, 1, 0, 3, 3, 2)",27823.767552 +"(0, 1, 1, 2, 0, 0, 1, 1, 1, 1, 0, 1, 2, 3, 3, 1, 3, 2, 0, 1, 3, 3, 3, 2)",20640.301056 +"(1, 1, 2, 1, 1, 1, 1, 1, 0, 0, 2, 1, 1, 2, 0, 3, 2, 1, 1, 1, 3, 0, 3, 3)",23160.029184 +"(0, 0, 0, 2, 1, 2, 0, 1, 0, 0, 2, 0, 0, 2, 1, 3, 2, 0, 0, 2, 0, 2, 2, 3)",25537.609728 +"(0, 0, 2, 2, 1, 2, 0, 1, 0, 0, 0, 0, 0, 2, 1, 1, 2, 0, 0, 2, 0, 2, 2, 3)",26862.944256 +"(0, 1, 0, 2, 0, 0, 0, 1, 1, 0, 2, 1, 1, 2, 3, 3, 1, 0, 0, 1, 3, 3, 3, 2)",22804.955136 +"(0, 1, 0, 2, 1, 1, 0, 1, 0, 0, 2, 0, 2, 2, 0, 1, 2, 1, 1, 2, 2, 2, 1, 2)",24986.124288 +"(1, 0, 2, 0, 0, 1, 1, 0, 0, 0, 0, 0, 3, 2, 0, 2, 0, 1, 3, 1, 2, 2, 2, 2)",24902.36928 +"(0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 2, 3, 1, 1, 0, 0, 1, 3, 0, 3, 2)",25233.850368 +"(1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 2, 1, 2, 1, 3, 1, 0, 1, 3, 3, 2, 3)",24013.504512 +"(1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 1, 2, 1, 0, 1, 0, 2, 3, 2)",28017.229824 +"(1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 1, 1, 1, 2, 0, 2, 1)",21574.582272 +"(1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 2, 1, 0, 2, 0, 3, 2, 1, 1, 1, 0, 2, 3, 2)",25028.001792 +"(0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 2, 0, 1, 2, 0, 1, 0, 2, 0, 1, 0, 3, 3, 2)",26158.6944 +"(0, 1, 0, 2, 0, 2, 1, 1, 0, 1, 2, 1, 1, 2, 2, 3, 1, 0, 0, 1, 3, 2, 3, 2)",22443.982848 +"(1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 1, 1, 2, 0, 1, 0, 1, 0, 1, 0, 2, 3, 2)",27117.748224 +"(0, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 0, 3, 2, 0, 1, 3, 1, 1, 2, 2, 3, 1, 1)",21926.7072 +"(0, 0, 2, 2, 0, 0, 1, 1, 1, 1, 0, 1, 3, 3, 3, 1, 3, 1, 0, 1, 3, 3, 3, 2)",20909.2608 +"(1, 1, 2, 0, 1, 2, 1, 0, 0, 0, 0, 1, 0, 2, 0, 3, 2, 1, 0, 1, 2, 2, 3, 2)",24383.913984 +"(1, 1, 0, 2, 0, 1, 1, 1, 0, 1, 2, 0, 1, 1, 2, 1, 3, 0, 0, 1, 3, 3, 3, 3)",22990.159872 +"(0, 1, 1, 2, 1, 0, 0, 1, 1, 0, 0, 0, 1, 2, 3, 1, 3, 0, 3, 1, 2, 0, 3, 2)",24575.606784 +"(1, 1, 2, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 2, 0, 1, 2, 1, 0, 1, 0, 2, 3, 2)",26035.421184 +"(1, 1, 0, 2, 0, 2, 1, 1, 0, 1, 2, 0, 3, 3, 2, 3, 3, 2, 2, 1, 1, 3, 3, 3)",19543.228416 +"(1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 2, 1, 1, 3, 3, 1, 3, 1, 0, 3, 0, 3, 3, 2)",22258.188288 +"(1, 1, 2, 2, 1, 1, 1, 1, 0, 0, 2, 1, 2, 2, 0, 3, 2, 3, 1, 2, 3, 2, 3, 3)",19944.89856 +"(1, 1, 1, 2, 1, 2, 1, 1, 1, 0, 2, 0, 3, 3, 3, 3, 3, 2, 3, 1, 2, 3, 3, 2)",17731.878912 +"(1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 2, 1, 1, 2, 0, 3, 0, 1, 0, 1, 0, 2, 3, 2)",25509.298176 +"(1, 1, 2, 2, 2, 1, 1, 1, 0, 0, 2, 1, 3, 2, 0, 3, 3, 3, 1, 2, 3, 3, 3, 3)",18340.57728 +"(1, 1, 2, 1, 1, 1, 1, 1, 0, 0, 0, 1, 2, 2, 0, 3, 2, 3, 0, 2, 3, 2, 3, 3)",21136.932864 +"(1, 1, 0, 2, 1, 2, 1, 1, 1, 0, 2, 0, 2, 3, 1, 3, 3, 1, 3, 1, 3, 2, 3, 3)",19799.212032 +"(1, 1, 2, 2, 0, 2, 0, 1, 0, 1, 2, 0, 3, 3, 3, 3, 2, 2, 2, 1, 1, 3, 3, 2)",19661.193216 +"(1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 2, 0, 1, 1, 1, 0, 1, 0, 2, 3, 2)",28140.50304 +"(1, 1, 0, 2, 2, 2, 1, 1, 0, 0, 2, 1, 2, 2, 3, 3, 3, 3, 1, 2, 2, 2, 2, 3)",19123.863552 +"(1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 2, 3, 3, 2, 3, 2, 3, 3, 2, 3, 2, 2)",19113.24672 +"(1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 3, 3, 3, 3, 2, 3, 3, 2, 0, 2, 3, 2)",18958.712832 +"(0, 1, 2, 1, 0, 0, 0, 1, 1, 1, 2, 1, 2, 2, 3, 1, 1, 1, 0, 1, 3, 3, 2, 2)",22416.850944 +"(1, 1, 0, 2, 0, 2, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 1, 2, 0, 1, 3, 3, 3, 2)",18767.609856 +"(0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 2, 1, 0, 2, 0, 3, 2, 1, 0, 1, 0, 2, 2, 2)",26256.01536 +"(1, 1, 2, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 3, 3, 3, 2, 3, 3, 1, 2, 2, 3, 2)",19906.56 +"(1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 2, 0, 2, 2, 1, 0, 1, 0, 2, 3, 2)",26671.84128 +"(1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 2, 0, 2, 1, 2, 1, 3, 1, 1, 1, 3, 3, 3, 3)",22785.490944 +"(1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 2, 0, 3, 2, 1, 0, 1, 0, 2, 3, 2)",25559.433216 +"(1, 1, 1, 2, 1, 2, 1, 1, 1, 0, 2, 0, 3, 3, 3, 3, 3, 2, 3, 2, 2, 3, 3, 2)",17248.813056 +"(1, 0, 2, 0, 1, 1, 1, 1, 1, 0, 1, 1, 3, 3, 3, 3, 3, 1, 3, 2, 2, 3, 2, 2)",18383.634432 +"(1, 1, 2, 1, 1, 1, 1, 1, 0, 1, 2, 1, 2, 2, 0, 3, 2, 3, 0, 2, 3, 2, 2, 3)",19946.078208 +"(0, 1, 2, 0, 0, 2, 1, 1, 0, 0, 2, 1, 1, 2, 3, 3, 1, 0, 0, 1, 0, 2, 3, 2)",23820.04224 +"(0, 1, 0, 2, 1, 0, 1, 1, 0, 0, 2, 0, 1, 2, 0, 1, 1, 0, 1, 2, 2, 2, 1, 2)",25915.097088 +"(1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 2, 1, 1, 2, 0, 1, 0, 1, 0, 1, 0, 2, 2, 2)",27814.330368 +"(1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 2, 0, 3, 3, 0, 3, 2, 2, 2, 1, 1, 2, 3, 2)",22180.33152 +"(0, 1, 0, 2, 0, 0, 0, 1, 1, 0, 2, 1, 1, 2, 3, 3, 1, 0, 0, 1, 2, 3, 2, 1)",23724.490752 +"(0, 1, 0, 1, 0, 0, 1, 1, 0, 0, 2, 0, 2, 2, 0, 1, 2, 1, 0, 1, 0, 3, 2, 2)",26013.007872 +"(1, 1, 1, 2, 1, 2, 1, 1, 1, 0, 2, 0, 3, 3, 0, 3, 3, 2, 3, 2, 0, 3, 3, 2)",19195.82208 +"(0, 1, 2, 0, 0, 1, 1, 1, 1, 0, 1, 1, 3, 2, 3, 3, 3, 1, 0, 2, 3, 2, 2, 2)",20016.857088 +"(0, 1, 0, 1, 1, 0, 1, 1, 0, 0, 2, 0, 2, 2, 0, 1, 3, 1, 1, 2, 2, 2, 1, 3)",24334.368768 +"(0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 2, 0, 1, 2, 0, 1, 0, 1, 0, 1, 0, 2, 2, 2)",27814.330368 +"(0, 1, 0, 1, 0, 2, 0, 1, 1, 1, 2, 1, 2, 2, 3, 3, 1, 1, 0, 1, 3, 3, 3, 2)",21149.908992 +"(1, 1, 0, 2, 0, 1, 0, 1, 0, 1, 2, 0, 2, 3, 2, 3, 2, 2, 2, 1, 1, 3, 3, 2)",21402.353664 +"(1, 1, 0, 2, 0, 2, 1, 1, 0, 1, 2, 0, 3, 3, 3, 3, 3, 2, 2, 1, 1, 3, 3, 2)",19124.453376 +"(0, 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2)",27449.229312 +"(1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 1, 1, 2, 0, 1, 0, 1, 0, 1, 0, 3, 3, 2)",26785.677312 +"(1, 1, 2, 2, 2, 1, 1, 1, 0, 0, 2, 1, 3, 2, 0, 3, 3, 3, 0, 2, 3, 3, 3, 3)",18588.893184 +"(0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 1, 1, 2, 0, 1, 0, 1, 0, 1, 0, 2, 3, 2)",27400.863744 +"(1, 1, 2, 2, 0, 1, 1, 1, 0, 0, 2, 1, 2, 2, 0, 3, 2, 3, 1, 2, 3, 2, 3, 3)",20133.64224 +"(0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 2, 0, 1, 3, 0, 1, 0, 2, 2, 1, 1, 3, 3, 2)",25189.613568 +"(1, 1, 1, 2, 1, 0, 1, 1, 0, 0, 1, 1, 3, 2, 0, 3, 2, 3, 1, 2, 3, 2, 3, 2)",20079.378432 +"(1, 1, 0, 2, 0, 1, 0, 1, 0, 1, 2, 0, 2, 2, 2, 3, 2, 2, 2, 1, 1, 3, 3, 2)",21950.30016 +"(0, 1, 2, 2, 1, 0, 1, 1, 0, 1, 0, 1, 0, 2, 2, 1, 2, 0, 0, 1, 3, 2, 2, 2)",24107.876352 +"(1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 2, 0, 2, 2, 0, 1, 2, 1, 0, 2, 0, 3, 3, 3)",25378.947072 +"(1, 1, 2, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 2, 0, 3, 2, 3, 0, 1, 0, 2, 3, 3)",23916.773376 +"(1, 0, 2, 0, 1, 1, 1, 1, 0, 0, 1, 0, 3, 3, 0, 3, 1, 2, 3, 2, 2, 2, 2, 1)",21556.887552 +"(0, 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2)",22016.360448 +"(0, 1, 2, 2, 0, 1, 1, 1, 1, 0, 2, 1, 3, 2, 0, 3, 1, 3, 0, 2, 3, 3, 3, 3)",19815.13728 +"(1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 2, 3, 3, 3, 2, 1, 3, 2, 2, 3, 3, 2)",19903.021056 +"(0, 1, 0, 2, 0, 1, 0, 1, 1, 1, 2, 1, 2, 2, 3, 3, 1, 1, 0, 1, 3, 3, 3, 2)",21244.280832 +"(1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 2, 1, 0, 2, 0, 3, 1, 1, 1, 1, 0, 2, 3, 2)",25434.390528 +"(0, 1, 2, 2, 0, 0, 1, 1, 1, 1, 2, 1, 1, 2, 3, 3, 1, 0, 0, 2, 3, 2, 3, 2)",21144.010752 +"(1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 2, 1, 1, 2, 0, 1, 2, 1, 0, 1, 3, 2, 3, 2)",24643.436544 +"(1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 0, 2, 3, 3, 3, 3)",17316.052992 +"(1, 1, 0, 2, 0, 1, 0, 1, 0, 1, 2, 1, 2, 2, 3, 3, 2, 2, 2, 1, 3, 3, 3, 2)",19784.466432 +"(1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 2, 0, 1, 2, 1, 0, 1, 0, 2, 3, 2)",27545.370624 +"(1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 3, 2, 0, 3, 2, 1, 1, 1, 0, 2, 3, 2)",23999.93856 +"(1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 2, 3, 3, 2, 3, 2, 2, 2)",16141.123584 +"(0, 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0, 0, 2, 1, 2, 2, 0, 1, 0, 3, 1, 1, 3, 2, 3, 2)",23565.238272 +"(1, 1, 2, 2, 1, 1, 1, 0, 0, 0, 2, 1, 2, 2, 0, 3, 2, 3, 1, 1, 3, 2, 3, 3)",20899.823616 +"(1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 1, 2, 2, 2, 2, 2)",17276.534784 +"(0, 1, 2, 2, 0, 1, 1, 1, 1, 0, 2, 1, 3, 2, 0, 3, 3, 3, 1, 2, 3, 3, 3, 3)",18623.6928 +"(1, 1, 2, 1, 0, 1, 0, 1, 0, 0, 2, 1, 1, 2, 0, 3, 2, 1, 0, 2, 0, 3, 3, 3)",23354.08128 +"(1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 2, 1, 0, 2, 0, 3, 2, 1, 1, 2, 0, 2, 3, 2)",24073.076736 +"(1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 3, 2, 0, 1, 0, 1, 0, 1, 3, 2, 3, 2)",23190.110208 +"(1, 1, 2, 2, 0, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 1, 3, 0, 2, 3, 3, 3, 3)",17911.185408 +"(0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 2, 1, 2, 2, 3, 3, 0, 1, 0, 1, 3, 3, 3, 2)",21874.212864 +"(1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 2, 1, 2, 2, 3, 3, 2, 1, 1, 2, 3, 2, 3, 2)",21382.299648 +"(1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 3, 2, 3, 3, 1, 3, 3, 2, 3, 2, 2, 2)",17095.458816 +"(1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 2, 1, 1, 2, 0, 1, 0, 3, 0, 1, 3, 3, 3, 2)",24008.78592 +"(0, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 0, 2, 3, 2, 3, 2)",18140.626944 +"(1, 1, 1, 2, 1, 0, 1, 0, 0, 0, 1, 1, 0, 2, 0, 3, 2, 1, 0, 1, 3, 2, 3, 2)",23366.467584 +"(0, 1, 1, 2, 1, 0, 1, 1, 1, 1, 1, 1, 3, 2, 3, 3, 2, 3, 3, 2, 3, 2, 3, 2)",17408.065536 +"(1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 2, 0, 3, 2, 1, 1, 1, 0, 2, 3, 2)",25877.348352 +"(1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 2, 1, 2, 2, 0, 3, 2, 1, 1, 2, 3, 2, 3, 2)",22531.2768 +"(0, 1, 0, 1, 0, 2, 0, 0, 1, 0, 2, 1, 1, 2, 0, 3, 1, 1, 0, 1, 3, 3, 3, 2)",23675.53536 +"(1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 2, 1, 1, 2, 3, 3, 2, 2, 2, 1, 3, 3, 3, 2)",20783.628288 +"(1, 1, 2, 2, 0, 2, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 0, 2, 2, 3, 3, 2)",17345.544192 +"(1, 1, 1, 2, 0, 0, 0, 0, 1, 0, 2, 0, 1, 2, 3, 3, 1, 3, 3, 2, 0, 2, 3, 2)",22119.579648 +"(0, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 1, 2, 3, 3, 3, 3)",17350.852608 +"(1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 2, 1, 2, 2, 0, 3, 1, 1, 1, 2, 0, 3, 3, 2)",24043.585536 +"(1, 1, 2, 1, 1, 1, 1, 1, 0, 0, 1, 1, 2, 2, 0, 3, 2, 1, 3, 2, 2, 2, 3, 2)",20705.181696 +"(1, 1, 0, 1, 0, 2, 0, 1, 1, 1, 2, 1, 2, 3, 3, 3, 2, 1, 0, 1, 3, 3, 3, 2)",19912.45824 +"(1, 1, 2, 2, 2, 2, 0, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 1, 1, 2, 0, 2, 3, 2)",19377.487872 +"(1, 1, 0, 2, 0, 0, 1, 0, 0, 0, 2, 1, 0, 2, 0, 3, 2, 1, 1, 1, 0, 3, 3, 3)",24486.54336 +"(1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 1, 3, 2, 0, 3, 2, 3, 1, 2, 0, 2, 3, 2)",22649.831424 +"(1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 2, 1, 2, 2, 3, 3, 1, 1, 0, 1, 3, 3, 3, 2)",21433.024512 +"(1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 2, 1, 0, 2, 0, 3, 2, 1, 0, 1, 0, 2, 3, 2)",25087.574016 +"(1, 1, 0, 2, 0, 1, 1, 1, 0, 1, 2, 0, 2, 2, 2, 3, 2, 2, 2, 1, 1, 3, 3, 2)",21478.44096 +"(1, 1, 0, 2, 1, 0, 0, 1, 0, 1, 0, 1, 2, 2, 3, 3, 2, 1, 0, 1, 0, 2, 3, 2)",23646.04416 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 0, 2, 1, 2, 2, 0, 1, 0, 1, 0, 1, 0, 2, 3, 2)",26118.586368 +"(0, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 1, 3, 1, 2, 3, 3, 2, 3)",17793.220608 +"(1, 1, 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2)",25038.0288 +"(1, 1, 0, 2, 2, 2, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 3, 3, 2, 1, 3, 3, 3, 2)",17308.975104 +"(1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3)",14649.458688 +"(1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 3, 2, 3, 1, 0, 1, 0, 1, 3, 2, 3, 2)",22135.504896 +"(1, 1, 0, 2, 1, 0, 0, 0, 0, 0, 2, 1, 1, 2, 0, 3, 2, 1, 1, 1, 3, 2, 3, 2)",23730.388992 +"(1, 1, 1, 2, 1, 0, 1, 1, 0, 1, 1, 1, 3, 2, 3, 3, 3, 3, 1, 2, 3, 3, 3, 2)",17589.731328 +"(0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 2, 1, 2, 2, 3, 3, 0, 1, 0, 1, 3, 3, 3, 2)",22346.072064 +"(1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 0, 2, 3, 3, 3, 3)",16590.569472 +"(0, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 1, 3, 1, 2, 3, 3, 3, 3)",17757.241344 +"(1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 2, 1, 2, 2, 0, 3, 2, 1, 2, 2, 0, 3, 3, 2)",23175.954432 +"(1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 3, 3, 2, 2, 3, 3, 3, 2)",15259.336704 +"(0, 1, 0, 2, 1, 1, 0, 1, 0, 0, 2, 1, 1, 2, 3, 3, 2, 1, 1, 1, 3, 3, 3, 3)",21662.466048 +"(1, 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0, 2, 1, 1, 2, 0, 1, 0, 1, 0, 1, 0, 2, 3, 2)",26645.889024 +"(1, 1, 1, 2, 1, 1, 1, 1, 0, 0, 1, 1, 2, 2, 0, 3, 2, 3, 1, 2, 3, 3, 3, 2)",19916.587008 +"(1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 1, 2, 3, 3, 3, 2)",16805.265408 +"(1, 1, 2, 2, 0, 1, 1, 1, 0, 1, 2, 1, 3, 3, 3, 3, 3, 3, 1, 2, 3, 3, 3, 3)",16549.281792 +"(1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 2, 1, 0, 2, 0, 3, 2, 1, 2, 1, 0, 2, 3, 2)",24000.528384 +"(1, 1, 2, 2, 0, 1, 1, 0, 0, 0, 2, 1, 3, 2, 3, 3, 2, 3, 0, 2, 3, 2, 3, 2)",19367.460864 +"(1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3)",15480.520704 +"(1, 1, 2, 2, 0, 0, 1, 1, 1, 0, 2, 1, 3, 2, 3, 3, 0, 3, 1, 1, 0, 3, 3, 2)",20706.361344 +"(1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 2, 1, 2, 2, 0, 1, 2, 1, 1, 2, 3, 2, 3, 2)",21969.174528 +"(1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 2, 3, 2, 2, 3, 3, 3, 2)",15984.820224 +"(1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 3, 2, 0, 1, 0, 1, 0, 1, 3, 2, 3, 2)",24322.572288 +"(0, 1, 0, 2, 0, 0, 0, 1, 1, 1, 2, 1, 3, 2, 3, 3, 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2)",23661.969408 +"(1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 3, 2, 2, 2, 3, 3, 3)",17604.476928 +"(1, 1, 0, 1, 2, 0, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 0, 2, 3, 3, 3, 2)",17649.303552 +"(1, 1, 0, 1, 0, 2, 0, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 2, 1, 1, 3, 3, 3, 2)",19773.8496 +"(1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 0, 2, 3, 3, 3, 3)",17127.309312 +"(1, 1, 2, 2, 0, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 1, 2, 3, 3, 3, 3)",17256.480768 +"(1, 1, 2, 2, 0, 1, 1, 1, 0, 1, 2, 0, 2, 3, 3, 3, 2, 3, 2, 2, 3, 3, 3, 3)",17832.148992 +"(0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 2, 1, 2, 2, 0, 3, 2, 1, 0, 1, 3, 2, 3, 2)",23734.51776 +"(1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 1, 1, 3, 2, 0, 3, 0, 1, 0, 2, 3, 3, 3, 3)",20462.764032 +"(1, 1, 0, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 1, 1, 1, 2, 3, 3, 3, 2)",19569.180672 +"(0, 1, 0, 2, 1, 1, 1, 1, 0, 1, 2, 1, 3, 2, 3, 1, 2, 3, 1, 1, 3, 2, 3, 2)",20078.198784 +"(0, 1, 2, 1, 0, 1, 0, 1, 0, 1, 2, 1, 3, 2, 3, 3, 2, 2, 0, 2, 3, 3, 3, 2)",19369.82016 +"(1, 1, 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2, 1, 3, 3, 3, 3, 2, 3, 1, 2, 3, 3, 3, 3)",16331.046912 +"(1, 1, 0, 2, 1, 0, 0, 0, 0, 0, 2, 1, 1, 2, 0, 1, 2, 1, 0, 1, 0, 2, 3, 2)",26270.171136 +"(1, 1, 2, 2, 0, 0, 1, 1, 0, 0, 2, 1, 1, 2, 0, 1, 0, 1, 0, 1, 0, 3, 3, 2)",25275.727872 +"(1, 1, 2, 2, 0, 2, 0, 1, 1, 1, 2, 1, 2, 3, 3, 3, 1, 1, 1, 1, 3, 3, 3, 2)",19504.300032 +"(1, 1, 0, 1, 0, 2, 0, 1, 1, 1, 2, 1, 1, 2, 3, 3, 0, 1, 0, 1, 3, 3, 3, 2)",21457.79712 +"(1, 1, 2, 2, 0, 0, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 3, 2, 3, 3, 3, 2)",16256.139264 +"(0, 1, 0, 2, 0, 0, 1, 1, 1, 0, 2, 1, 2, 2, 3, 3, 0, 1, 0, 2, 3, 2, 3, 2)",21723.21792 +"(0, 1, 2, 1, 0, 1, 1, 0, 1, 1, 2, 1, 1, 2, 0, 1, 0, 1, 0, 2, 3, 2, 3, 3)",23194.238976 +"(0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 2, 1, 2, 2, 0, 3, 1, 1, 1, 1, 3, 2, 3, 2)",23043.244032 +"(1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 1, 2, 2, 0, 1, 0, 1, 1, 1, 0, 2, 3, 2)",26436.501504 +"(0, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 1, 1, 2, 3, 3, 3, 3)",18312.265728 +"(1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 2, 1, 1, 3, 0, 1, 0, 1, 3, 1, 3, 3, 3, 2)",22840.344576 +"(1, 1, 2, 2, 2, 0, 0, 1, 1, 0, 2, 1, 2, 2, 0, 1, 3, 1, 0, 1, 0, 2, 3, 2)",23790.55104 +"(1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 2, 1, 2, 2, 0, 3, 2, 1, 3, 2, 0, 3, 3, 2)",21643.001856 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 0, 2, 0, 3, 2, 3, 3, 1, 3, 1, 1, 0, 3, 3, 2)",22530.097152 +"(1, 1, 2, 2, 1, 2, 1, 0, 0, 1, 2, 1, 2, 3, 3, 3, 2, 1, 1, 2, 3, 3, 3, 2)",18803.58912 +"(1, 1, 0, 1, 0, 2, 0, 1, 1, 1, 2, 1, 1, 2, 3, 3, 2, 2, 0, 1, 3, 3, 3, 2)",20455.09632 +"(1, 1, 0, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 1, 3, 1, 2, 3, 3, 3, 2)",18607.767552 +"(1, 1, 2, 2, 2, 2, 0, 1, 0, 1, 2, 1, 3, 2, 3, 3, 3, 3, 0, 2, 0, 3, 3, 3)",18594.791424 +"(1, 1, 0, 2, 0, 0, 1, 1, 0, 1, 2, 1, 3, 2, 3, 3, 0, 3, 3, 2, 3, 3, 3, 3)",18091.671552 +"(1, 1, 1, 2, 1, 0, 1, 1, 1, 0, 1, 1, 3, 2, 3, 3, 1, 3, 1, 2, 3, 2, 3, 2)",19053.674496 +"(1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 2, 0, 1, 2, 0, 1, 0, 1, 0, 1, 0, 2, 3, 2)",27212.120064 +"(1, 1, 0, 1, 1, 2, 1, 1, 0, 1, 2, 1, 3, 2, 0, 1, 0, 1, 0, 2, 3, 2, 3, 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2)",25964.642304 +"(1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 3, 3, 3, 3, 1, 3, 2, 3, 3, 3, 3)",16346.382336 +"(1, 1, 2, 2, 2, 0, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 3, 2, 2, 2, 3, 3, 3, 3)",16233.725952 +"(1, 1, 2, 1, 0, 0, 0, 1, 0, 1, 1, 1, 3, 2, 0, 3, 0, 3, 0, 1, 3, 2, 3, 2)",21469.5936 +"(1, 1, 2, 2, 2, 0, 1, 1, 0, 1, 2, 1, 2, 2, 3, 1, 0, 1, 2, 1, 3, 3, 3, 3)",20676.28032 +"(1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 0, 1, 2, 0, 1, 0, 3, 0, 1, 0, 2, 3, 2)",26816.937984 +"(1, 1, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 3, 3, 0, 1, 3, 1, 3, 2, 3, 2, 3, 2)",18815.3856 +"(1, 1, 2, 1, 1, 0, 0, 1, 0, 1, 2, 1, 3, 2, 3, 3, 0, 1, 0, 1, 3, 2, 3, 3)",20978.270208 +"(1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 2)",15141.961728 +"(1, 1, 2, 2, 0, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 1, 2, 3, 3, 3, 2)",17371.496448 +"(1, 1, 2, 2, 2, 0, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 3, 2, 3, 3, 3, 2)",16415.391744 +"(1, 1, 0, 2, 0, 0, 0, 0, 0, 0, 2, 1, 2, 2, 0, 1, 0, 1, 0, 1, 0, 2, 3, 2)",26590.445568 +"(1, 1, 0, 2, 0, 0, 0, 1, 1, 1, 2, 1, 3, 2, 3, 3, 1, 3, 1, 1, 3, 3, 3, 3)",19467.14112 +"(1, 1, 2, 2, 0, 1, 0, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 3, 2, 3, 3, 3, 2)",16350.511104 +"(1, 1, 0, 2, 1, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 1, 2, 1, 1, 2, 3, 3, 3, 3)",19448.856576 +"(1, 1, 0, 2, 0, 0, 0, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 3, 2, 3, 2, 3, 2)",17531.928576 +"(1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 1, 1, 2, 3, 3, 3, 2)",17418.682368 +"(1, 1, 0, 2, 2, 0, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 0, 3, 0, 1, 3, 3, 3, 3)",19024.183296 +"(1, 1, 0, 2, 2, 0, 1, 1, 1, 1, 1, 0, 3, 3, 0, 1, 3, 3, 3, 2, 3, 3, 3, 2)",18559.991808 +"(1, 1, 0, 2, 2, 2, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 1, 1, 2, 3, 3, 3, 2)",18785.304576 +"(1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 1, 2, 3, 3, 3, 3)",16342.253568 +"(1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 3, 3, 2, 2, 3, 3, 3, 3)",15333.064704 +"(0, 1, 0, 2, 0, 0, 0, 1, 0, 1, 2, 0, 1, 3, 3, 1, 0, 1, 1, 1, 0, 2, 3, 2)",25078.136832 +"(1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 2, 3, 3, 2, 3, 3, 3, 3)",15186.198528 +"(1, 1, 2, 2, 0, 0, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 1, 1, 3, 2, 3, 3, 3, 3)",18045.66528 +"(1, 1, 2, 2, 0, 1, 1, 1, 0, 1, 2, 1, 2, 3, 3, 1, 0, 1, 2, 1, 3, 3, 3, 2)",20243.349504 +"(0, 1, 0, 2, 1, 0, 1, 1, 0, 1, 0, 1, 1, 2, 0, 1, 0, 3, 1, 2, 3, 2, 3, 2)",23420.731392 +"(1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 2, 1, 2, 2, 0, 3, 2, 1, 0, 1, 3, 3, 3, 3)",23004.315648 +"(1, 1, 2, 2, 0, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 1, 2, 3, 3, 3, 3)",16719.740928 +"(1, 1, 0, 2, 2, 0, 0, 1, 1, 1, 2, 1, 2, 2, 3, 3, 3, 3, 1, 1, 3, 3, 3, 3)",18693.292032 +"(1, 1, 0, 2, 2, 0, 0, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 3, 2, 3, 2, 3, 3)",17039.425536 +"(1, 1, 2, 1, 0, 1, 0, 0, 1, 0, 2, 1, 3, 2, 3, 3, 2, 1, 0, 1, 0, 3, 3, 3)",21897.216 +"(1, 1, 2, 2, 2, 0, 0, 1, 1, 1, 2, 1, 3, 3, 3, 3, 2, 3, 2, 2, 3, 3, 3, 2)",16834.166784 +"(1, 1, 0, 2, 0, 1, 1, 1, 0, 1, 2, 1, 2, 2, 3, 1, 0, 1, 2, 1, 3, 2, 3, 2)",21595.226112 +"(1, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 1, 3, 0, 2, 3, 3, 3, 2)",19422.314496 +"(1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 1, 1, 1, 1, 3, 3, 3, 2)",20146.618368 +"(1, 1, 0, 2, 0, 1, 1, 1, 0, 0, 2, 1, 2, 2, 0, 3, 1, 1, 0, 2, 0, 2, 3, 2)",23680.253952 +"(1, 1, 0, 2, 1, 0, 0, 1, 1, 1, 2, 1, 2, 2, 3, 1, 0, 3, 1, 1, 3, 3, 3, 2)",21046.099968 +"(1, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 1, 1, 1, 1, 3, 3, 3, 3)",20503.461888 +"(1, 1, 0, 2, 2, 0, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 2, 1, 0, 2, 3, 3, 3, 2)",18505.138176 +"(1, 1, 0, 2, 1, 1, 0, 1, 1, 1, 2, 1, 2, 2, 3, 3, 1, 3, 0, 1, 3, 3, 3, 3)",19695.992832 +"(1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 2, 1, 3, 2, 0, 1, 0, 1, 0, 1, 3, 2, 3, 2)",23756.341248 +"(1, 1, 2, 2, 2, 0, 0, 1, 0, 0, 2, 1, 1, 2, 0, 1, 3, 3, 3, 2, 0, 3, 3, 2)",21619.99872 +"(1, 1, 2, 1, 0, 1, 1, 1, 0, 0, 2, 1, 2, 2, 3, 3, 0, 3, 1, 2, 0, 2, 3, 2)",21196.505088 +"(1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 3, 2, 3, 1, 3, 3, 3, 1, 3, 2, 3, 2)",17075.4048 +"(1, 1, 2, 2, 0, 1, 0, 1, 0, 1, 2, 1, 3, 2, 3, 3, 0, 2, 2, 2, 3, 2, 3, 2)",19179.307008 +"(1, 1, 0, 2, 0, 1, 0, 1, 1, 1, 1, 0, 3, 2, 0, 1, 0, 1, 0, 1, 3, 2, 3, 2)",23661.969408 +"(1, 1, 0, 2, 0, 2, 0, 1, 1, 1, 2, 1, 3, 3, 0, 3, 0, 1, 1, 2, 3, 3, 3, 2)",20159.004672 +"(1, 1, 2, 1, 0, 1, 1, 1, 0, 1, 2, 1, 3, 2, 0, 3, 3, 3, 1, 1, 3, 3, 3, 3)",18729.271296 +"(1, 1, 2, 1, 2, 0, 0, 0, 0, 1, 2, 1, 1, 2, 3, 3, 3, 1, 0, 2, 0, 2, 3, 3)",22000.4352 +"(1, 1, 0, 2, 0, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 1, 3, 1, 2, 3, 3, 3, 3)",18134.728704 +"(1, 1, 0, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 1, 0, 1, 3, 3, 3, 2)",19894.173696 +"(0, 1, 0, 2, 0, 1, 0, 1, 0, 1, 2, 1, 2, 2, 3, 3, 0, 1, 1, 1, 3, 3, 3, 2)",21531.52512 +"(1, 1, 0, 2, 1, 1, 0, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 1, 1, 2, 3, 3, 3, 2)",19634.651136 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 0, 2, 1, 2, 2, 0, 1, 0, 1, 0, 1, 0, 3, 3, 2)",25786.515456 +"(0, 1, 2, 1, 0, 1, 0, 1, 1, 1, 2, 1, 2, 2, 3, 3, 1, 3, 2, 1, 3, 3, 3, 2)",19195.82208 +"(0, 1, 2, 1, 0, 0, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 1, 1, 2, 3, 3, 3, 2)",19087.884288 +"(1, 1, 0, 2, 1, 0, 0, 1, 0, 1, 1, 0, 2, 2, 3, 1, 0, 1, 2, 1, 3, 2, 3, 2)",23010.803712 +"(1, 1, 0, 1, 0, 2, 1, 0, 1, 1, 2, 0, 3, 3, 3, 3, 0, 1, 0, 1, 3, 2, 3, 3)",20807.811072 +"(1, 1, 0, 1, 2, 0, 0, 1, 1, 1, 2, 1, 3, 2, 0, 1, 3, 1, 3, 1, 3, 3, 3, 3)",20248.65792 +"(1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 0, 1, 3, 0, 3, 0, 1, 0, 2, 0, 3, 3, 2)",25467.420672 +"(1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 3, 2, 0, 1, 3, 1, 0, 1, 3, 3, 3, 2)",21379.350528 +"(1, 1, 2, 1, 1, 0, 1, 1, 0, 1, 2, 1, 3, 2, 3, 3, 2, 3, 1, 2, 3, 3, 3, 3)",17917.083648 +"(1, 1, 2, 1, 2, 0, 1, 1, 0, 0, 2, 1, 2, 2, 3, 1, 3, 3, 3, 1, 0, 2, 3, 3)",20455.09632 +"(1, 1, 0, 2, 0, 0, 0, 0, 1, 0, 0, 1, 1, 2, 3, 1, 0, 1, 0, 2, 0, 2, 3, 2)",25957.564416 +"(1, 1, 0, 2, 0, 0, 1, 1, 1, 0, 2, 1, 3, 2, 0, 1, 0, 3, 3, 1, 3, 3, 3, 2)",20880.949248 +"(1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 3, 1, 3, 2, 3, 3, 3, 2)",17198.088192 +"(1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 2, 1, 2, 2, 3, 3, 1, 1, 1, 2, 3, 3, 3, 2)",20701.642752 +"(1, 1, 2, 2, 1, 0, 1, 1, 1, 1, 2, 1, 3, 2, 3, 1, 2, 3, 2, 2, 3, 2, 3, 3)",18263.90016 +"(1, 1, 0, 2, 0, 1, 0, 1, 0, 1, 2, 1, 2, 2, 3, 3, 1, 2, 2, 1, 3, 3, 3, 2)",20190.855168 +"(1, 1, 2, 2, 1, 0, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 3, 1, 2, 3, 3, 3, 2)",18107.006976 +"(1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 3, 2, 0, 1, 0, 1, 0, 1, 3, 2, 3, 2)",24700.059648 +"(1, 1, 2, 2, 2, 0, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 2, 2, 3, 3, 3, 2)",16373.51424 +"(1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 2, 1, 2, 2, 3, 3, 2, 1, 1, 2, 3, 3, 3, 2)",19634.651136 +"(1, 1, 0, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 3, 1, 2, 3, 3, 3, 2)",18201.378816 +"(0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 2, 1, 3, 2, 3, 3, 1, 1, 0, 1, 3, 3, 3, 3)",20676.870144 +"(1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 2, 0, 1, 2, 0, 1, 0, 1, 0, 1, 0, 2, 3, 2)",26740.260864 +"(1, 1, 2, 2, 0, 1, 0, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 2, 3, 2, 3, 3, 3, 3)",16758.669312 +"(1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 2, 1, 3, 2, 0, 1, 3, 2, 0, 1, 3, 2, 3, 2)",22783.131648 +"(1, 1, 0, 2, 0, 0, 0, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 2, 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3)",20125.974528 +"(1, 1, 0, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 1, 3, 2, 3, 3, 3, 2)",18206.687232 +"(0, 1, 2, 2, 2, 0, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 3, 3, 2, 2, 3, 3, 3, 3)",15993.667584 +"(1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 3, 0, 3, 0, 1, 3, 1, 3, 3, 3, 3)",22626.828288 +"(1, 1, 2, 2, 1, 0, 1, 1, 0, 1, 2, 1, 3, 2, 3, 3, 2, 3, 1, 2, 3, 3, 3, 3)",17822.711808 +"(1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 2, 2, 3, 3, 3, 2)",16532.76672 +"(1, 1, 2, 1, 0, 0, 0, 1, 0, 0, 2, 1, 3, 3, 0, 1, 0, 1, 1, 1, 0, 2, 3, 3)",24283.05408 +"(1, 1, 2, 2, 0, 0, 0, 1, 0, 1, 2, 1, 2, 2, 3, 3, 0, 1, 2, 1, 3, 2, 3, 2)",21024.866304 +"(1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 2, 3, 3, 2, 3, 3, 3, 3)",15374.942208 +"(1, 1, 2, 2, 1, 1, 1, 0, 1, 0, 2, 1, 2, 2, 3, 3, 3, 1, 3, 2, 3, 2, 3, 2)",18568.249344 +"(1, 1, 0, 2, 1, 0, 0, 1, 1, 0, 2, 1, 2, 2, 0, 3, 2, 1, 1, 1, 0, 3, 3, 2)",23459.659776 +"(1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 2, 1, 1, 2, 3, 1, 0, 1, 2, 2, 3, 3, 3, 2)",22817.34144 +"(1, 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0, 1, 1, 1, 3, 2, 0, 1, 3, 1, 0, 1, 3, 2, 3, 3)",21973.89312 +"(1, 1, 2, 1, 2, 1, 1, 1, 0, 1, 2, 1, 3, 2, 3, 3, 3, 3, 1, 2, 3, 3, 3, 3)",16814.112768 +"(1, 1, 2, 2, 2, 0, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 0, 3, 3, 2, 3, 3, 3, 2)",16979.853312 +"(1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 3, 1, 2, 3, 3, 3, 2)",18295.750656 +"(1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 1, 2, 2, 3, 3, 3, 2)",18229.690368 +"(1, 1, 2, 2, 0, 0, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 1, 1, 3, 2, 3, 3)",18449.104896 +"(1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 2, 1, 1, 2, 0, 3, 0, 1, 0, 1, 0, 2, 3, 2)",25320.554496 +"(1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 2, 1, 2, 2, 0, 1, 0, 1, 0, 1, 0, 2, 3, 2)",26212.958208 +"(1, 1, 2, 2, 2, 1, 0, 1, 1, 1, 2, 1, 3, 2, 3, 3, 0, 3, 2, 2, 3, 2, 3, 2)",17901.1584 +"(1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 3, 2, 3, 3, 3, 2)",15312.420864 +"(1, 1, 0, 2, 1, 1, 1, 0, 1, 1, 2, 1, 3, 3, 3, 3, 0, 3, 0, 2, 3, 3, 3, 2)",18391.302144 +"(1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 1, 2, 3, 3, 3, 3)",17067.737088 +"(0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 2, 1, 2, 2, 0, 1, 0, 1, 0, 1, 3, 2, 3, 2)",24586.223616 +"(1, 1, 0, 2, 2, 0, 0, 1, 0, 0, 2, 1, 2, 2, 0, 3, 0, 1, 0, 1, 0, 3, 3, 2)",24461.180928 +"(1, 1, 2, 2, 2, 1, 1, 1, 0, 1, 2, 1, 3, 2, 3, 3, 3, 3, 1, 2, 3, 3, 3, 3)",16719.740928 +"(1, 1, 0, 2, 2, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 1, 2, 3, 3, 3, 2)",17465.868288 +"(1, 1, 0, 2, 1, 1, 0, 1, 0, 1, 1, 0, 2, 2, 3, 1, 0, 1, 2, 2, 3, 3, 3, 2)",21818.179584 +"(1, 1, 2, 2, 0, 1, 0, 0, 0, 1, 0, 1, 2, 2, 3, 1, 1, 1, 1, 1, 3, 3, 3, 3)",22772.514816 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 1, 2, 1, 2, 2, 3, 1, 0, 1, 2, 1, 3, 3, 3, 2)",22112.50176 +"(1, 1, 2, 2, 0, 0, 1, 1, 0, 1, 2, 1, 2, 3, 3, 3, 2, 1, 2, 1, 3, 3, 3, 2)",19108.528128 +"(1, 1, 0, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 3, 3, 3, 2, 3, 1, 2, 3, 3, 3, 2)",17653.43232 +"(1, 1, 2, 1, 2, 0, 0, 1, 0, 0, 1, 1, 3, 2, 0, 1, 2, 1, 3, 1, 3, 2, 3, 3)",21683.699712 +"(0, 1, 2, 2, 0, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 1, 2, 3, 3, 3, 3)",17539.596288 +"(1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 2, 1, 3, 2, 3, 3, 1, 1, 0, 1, 3, 3, 3, 2)",20886.257664 +"(1, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 2, 3, 1, 1, 1, 1, 1, 3, 3, 3, 3)",21451.309056 +"(1, 1, 0, 2, 1, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 1, 2, 3, 3, 3, 2)",17654.611968 +"(1, 1, 2, 2, 0, 1, 0, 1, 0, 1, 2, 1, 3, 2, 3, 3, 0, 2, 1, 2, 3, 2, 3, 2)",19640.549376 +"(1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 2, 1, 3, 2, 0, 1, 0, 1, 0, 1, 3, 2, 3, 2)",23378.853888 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 1, 2, 1, 2, 2, 3, 1, 0, 1, 1, 1, 3, 2, 3, 2)",22905.81504 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 1, 2, 1, 2, 2, 0, 3, 0, 1, 2, 1, 3, 2, 3, 2)",22551.330816 +"(1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3)",15384.969216 +"(1, 1, 0, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 1, 2, 2, 3, 3, 3, 2)",18701.549568 +"(0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 2, 1, 2, 2, 3, 3, 1, 1, 0, 1, 3, 3, 3, 2)",22093.627392 +"(1, 1, 2, 1, 2, 1, 1, 1, 0, 1, 2, 1, 3, 2, 3, 3, 3, 3, 2, 2, 3, 3, 3, 3)",16352.8704 +"(1, 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1, 1, 2, 1, 2, 2, 3, 3, 2, 1, 2, 2, 3, 3, 3, 2)",18890.293248 +"(1, 1, 0, 2, 1, 1, 1, 1, 0, 1, 2, 1, 2, 2, 0, 3, 1, 3, 0, 1, 3, 3, 3, 2)",20771.241984 +"(1, 1, 0, 2, 1, 1, 1, 0, 1, 0, 1, 1, 2, 2, 3, 3, 0, 1, 0, 2, 3, 2, 3, 2)",21440.1024 +"(0, 1, 0, 2, 0, 1, 0, 1, 0, 1, 2, 1, 2, 2, 3, 1, 1, 1, 1, 1, 3, 2, 3, 2)",22653.370368 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 1, 2, 1, 2, 2, 0, 1, 0, 1, 0, 1, 0, 3, 3, 2)",25220.284416 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 1, 2, 1, 2, 2, 0, 3, 1, 1, 1, 1, 0, 3, 3, 3)",23751.032832 +"(1, 1, 0, 2, 1, 0, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 1, 1, 1, 1, 3, 3, 3, 2)",20429.733888 +"(1, 1, 2, 1, 0, 0, 1, 1, 0, 1, 2, 1, 3, 2, 0, 1, 0, 3, 0, 2, 3, 3, 3, 3)",20921.05728 +"(1, 1, 2, 2, 0, 0, 0, 1, 0, 1, 2, 1, 3, 3, 3, 1, 0, 1, 0, 1, 3, 3, 3, 2)",21255.487488 +"(1, 1, 0, 2, 2, 1, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3)",15310.061568 +"(1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 3, 2, 3, 1, 0, 1, 1, 2, 3, 2, 3, 2)",22536.585216 +"(1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 2, 1, 3, 2, 0, 1, 1, 3, 1, 1, 3, 3, 3, 2)",21867.7248 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 1, 2, 1, 2, 2, 3, 3, 0, 2, 2, 1, 3, 3, 3, 2)",20726.41536 +"(1, 1, 2, 2, 2, 1, 1, 1, 0, 0, 2, 1, 3, 2, 3, 3, 3, 3, 1, 2, 3, 3, 3, 3)",17285.971968 +"(1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 2, 1, 2, 2, 3, 1, 0, 1, 0, 1, 3, 3, 3, 2)",23105.175552 +"(1, 1, 0, 2, 0, 1, 0, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 1, 3, 1, 3, 2, 3, 2)",18598.920192 +"(0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 2, 1, 2, 2, 0, 3, 2, 1, 1, 1, 3, 3, 3, 2)",21927.297024 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 1, 2, 1, 2, 2, 3, 1, 0, 1, 1, 1, 3, 3, 3, 2)",22573.744128 +"(1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 2)",14953.218048 +"(1, 1, 2, 2, 0, 0, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 0, 1, 3, 2, 3, 3, 3, 2)",18318.753792 +"(1, 1, 0, 2, 0, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 1, 2, 1, 3, 3, 3, 2)",19373.359104 +"(1, 1, 0, 2, 1, 0, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 1, 2, 1, 3, 3, 3, 2)",19015.335936 +"(1, 1, 2, 2, 0, 0, 1, 1, 1, 0, 2, 1, 3, 2, 3, 1, 0, 3, 1, 2, 0, 2, 3, 3)",21388.197888 +"(1, 1, 2, 2, 0, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 3, 2, 2, 3, 2, 3, 3)",17127.309312 +"(1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 2, 1, 3, 2, 0, 1, 0, 1, 0, 1, 3, 2, 3, 3)",23641.325568 +"(1, 1, 2, 2, 0, 1, 0, 1, 0, 1, 2, 1, 2, 2, 3, 3, 3, 3, 2, 1, 3, 2, 3, 3)",18469.748736 +"(1, 1, 2, 2, 1, 0, 1, 1, 0, 1, 2, 1, 2, 3, 3, 3, 2, 1, 2, 2, 3, 3, 3, 2)",18436.718592 +"(1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 3, 3, 3, 1, 3, 1, 2, 3, 3, 3, 3)",17284.202496 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 1, 2, 1, 2, 2, 3, 1, 0, 1, 0, 1, 3, 2, 3, 2)",23154.130944 +"(1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 3, 3, 3, 1, 3, 3, 3, 3)",15132.524544 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 1, 2, 1, 2, 2, 3, 3, 1, 1, 2, 1, 3, 3, 3, 2)",21006.58176 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 0, 2, 1, 2, 3, 3, 1, 0, 1, 3, 1, 3, 2, 3, 2)",21967.99488 +"(1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 2, 1, 3, 2, 0, 1, 0, 1, 1, 1, 3, 2, 3, 2)",23508.025344 +"(1, 1, 2, 2, 0, 0, 1, 1, 0, 1, 2, 1, 2, 3, 3, 3, 2, 1, 2, 2, 3, 3, 3, 2)",18625.462272 +"(0, 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2)",25649.086464 +"(1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 3, 1, 1, 1, 3, 3, 3, 3)",18333.499392 +"(1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 2, 3, 3, 2, 3, 3, 3, 2)",15489.957888 +"(1, 1, 0, 2, 0, 0, 0, 1, 0, 1, 1, 1, 2, 2, 0, 1, 1, 1, 2, 1, 3, 2, 3, 2)",23435.476992 +"(1, 1, 0, 2, 2, 1, 1, 0, 0, 1, 0, 1, 3, 2, 0, 3, 0, 3, 0, 2, 0, 2, 3, 3)",22592.618496 +"(1, 1, 0, 2, 0, 1, 0, 1, 0, 1, 2, 1, 2, 2, 3, 3, 1, 1, 2, 1, 3, 3, 3, 2)",20629.0944 +"(1, 1, 2, 1, 0, 0, 0, 1, 1, 0, 2, 1, 1, 3, 3, 1, 3, 1, 3, 1, 3, 3, 3, 2)",20212.678656 +"(1, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 1, 2, 2, 3, 3, 3, 2)",19267.780608 +"(1, 1, 0, 2, 1, 1, 0, 1, 0, 1, 2, 1, 2, 2, 3, 1, 0, 1, 2, 1, 3, 3, 3, 2)",21546.27072 +"(1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 1, 2, 2, 3, 3, 3, 2)",18815.3856 +"(1, 1, 0, 1, 0, 2, 0, 1, 0, 1, 2, 1, 3, 2, 3, 1, 0, 1, 3, 2, 3, 3, 3, 3)",20000.93184 +"(1, 1, 2, 2, 0, 0, 0, 1, 0, 1, 2, 1, 2, 3, 3, 3, 2, 1, 1, 2, 3, 2, 3, 2)",19890.634752 +"(1, 1, 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2)",18610.126848 +"(1, 1, 2, 2, 2, 0, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 2, 3, 3, 2, 3, 3, 3, 2)",15867.445248 +"(1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 3, 1, 2, 3, 2, 3, 3)",17946.574848 +"(1, 1, 2, 2, 0, 1, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 1, 2, 3, 3, 3, 2)",16834.756608 +"(1, 1, 0, 2, 1, 0, 1, 1, 0, 1, 2, 1, 2, 2, 3, 1, 1, 1, 1, 1, 3, 3, 3, 2)",21755.068416 +"(1, 1, 2, 2, 2, 1, 0, 1, 0, 1, 2, 1, 2, 2, 0, 3, 3, 1, 3, 1, 0, 3, 3, 2)",20739.981312 +"(1, 1, 2, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 2, 3, 2, 1, 3, 3, 3, 3)",18202.558464 +"(1, 1, 0, 2, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 3, 3, 2, 1, 2, 1, 3, 3, 3, 2)",20317.077504 +"(1, 1, 0, 2, 2, 0, 1, 1, 1, 1, 2, 1, 3, 2, 3, 3, 3, 3, 1, 2, 3, 3, 3, 2)",17306.615808 +"(1, 1, 0, 2, 1, 2, 1, 1, 1, 1, 2, 1, 2, 2, 3, 3, 3, 1, 2, 2, 3, 3, 3, 2)",17976.066048 +"(0, 1, 0, 2, 0, 0, 0, 1, 0, 1, 2, 1, 3, 2, 3, 1, 0, 1, 1, 1, 3, 3, 3, 2)",22310.0928 +"(1, 1, 0, 2, 2, 2, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 3, 1, 3, 2, 3, 3, 3, 3)",16082.731008 +"(1, 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"58 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "59 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"59 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "67 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"60 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "62 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"61 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "62 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"62 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "63 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"63 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "64 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"64 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "73 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"65 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "66 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"66 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"67 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "69 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"69 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "70 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"70 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "71 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"71 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "72 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"72 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "73 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"73 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "74 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"74 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "75 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"75 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "76 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"76 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "79 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"77 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "79 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"78 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "79 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"79 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "80 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"80 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "81 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"81 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "82 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"82 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "85 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"82 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "91 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"83 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "85 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"84 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "85 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"85 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "86 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"86 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "89 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"87 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "89 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"88 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "89 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"89 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "90 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"90 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "91 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"91 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "92 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"92 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "95 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"92 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"92 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "103 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"92 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "122 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"93 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "95 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"94 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "95 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"95 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "106 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"96 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "98 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"97 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "98 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"98 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "99 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"99 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "100 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"100 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "108 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"101 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "103 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"102 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "103 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"103 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "104 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"104 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "105 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"105 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "114 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"106 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "107 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"107 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "109 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"108 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "109 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"109 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "110 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"110 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "111 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"111 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "112 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"112 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "113 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"113 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "114 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"114 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "115 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"115 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "116 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"116 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "117 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"117 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "120 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"118 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "120 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"119 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "120 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"120 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "121 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"121 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "122 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"122 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "123 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"123 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"123 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "132 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"124 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"125 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "127 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"127 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "130 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"128 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "130 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"129 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "130 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"130 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "131 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"131 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "132 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"132 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "133 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"133 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "136 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"133 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "139 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"133 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "144 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"133 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "163 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"134 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "136 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"135 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "136 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"136 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "147 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"137 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "139 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"138 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "139 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"139 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "140 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"140 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "141 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"141 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "149 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"142 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "144 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"143 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "144 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"144 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "145 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"145 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "146 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"146 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"147 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "148 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"148 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "150 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"149 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "150 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"150 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "151 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"151 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "152 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"152 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "153 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"153 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "154 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"154 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "156 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"156 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "157 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"157 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "158 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"158 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "161 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"159 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "161 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"160 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "161 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"161 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "162 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"162 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "163 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"163 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "164 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"164 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "167 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"164 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "173 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"165 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "167 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"166 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "167 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"167 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "168 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"168 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "171 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"169 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "171 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"170 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "171 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"171 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "172 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"172 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "173 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"173 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "174 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"174 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"174 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "180 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"174 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"174 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "204 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"175 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "177 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"176 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "177 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"177 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "188 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"178 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "180 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"179 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "180 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"180 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "181 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"181 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "182 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"182 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "190 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"183 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "185 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"184 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "185 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"185 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "186 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"186 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "187 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"187 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "196 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"188 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "189 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"189 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "191 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"190 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "191 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"191 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "192 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"192 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "193 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"193 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "194 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"194 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "195 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"195 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "196 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"196 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "197 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"197 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "198 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"198 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "199 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"199 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "202 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"200 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "202 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"201 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "202 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"202 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "203 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"203 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "204 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"204 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "205 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"205 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"205 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"206 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "208 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"207 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "208 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"208 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"209 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "212 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"210 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "212 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"211 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "212 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"212 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "213 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"213 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "214 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"214 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "215 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"215 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"215 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "221 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"215 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "226 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"215 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "245 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"216 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "218 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"217 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "218 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "227 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"227 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "228 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"228 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "237 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "232 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"232 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "233 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"233 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "234 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "237 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"237 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "238 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"238 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "239 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"239 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "240 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"240 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "243 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"241 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "244 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"244 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "245 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"245 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "246 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"246 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "249 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"246 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "255 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"247 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "249 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"248 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "249 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"249 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "250 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"250 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "253 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"251 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "253 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"252 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "253 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"253 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "254 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"254 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "255 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"255 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "256 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"256 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "259 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"256 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "262 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"256 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "267 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"256 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "286 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"257 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "259 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"258 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "259 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "268 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"268 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "269 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"269 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "278 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"270 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "271 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"271 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "273 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"272 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "273 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"273 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "274 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"274 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "275 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"275 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "276 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"276 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "277 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"277 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "278 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"278 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "279 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"279 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "280 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"280 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "281 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"281 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "284 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"282 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "284 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"283 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "284 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"284 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "285 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"285 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "286 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"286 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "287 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"287 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "290 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"287 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "296 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"288 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "290 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"289 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "290 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"290 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "291 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"291 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "294 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"292 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "294 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"293 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "294 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"294 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "295 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"295 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "296 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"296 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "297 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"297 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"297 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "303 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"297 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "308 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"297 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "327 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"298 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"299 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "311 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"301 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "303 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"302 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "303 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"303 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "304 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"304 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "305 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"305 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "313 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"306 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "308 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"307 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "308 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"308 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "309 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"309 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "310 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"310 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "319 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"311 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "312 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"312 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "314 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"313 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "314 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"314 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "315 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"315 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "316 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"316 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "317 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"317 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "318 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"318 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "319 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"319 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "320 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"320 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "321 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"321 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "322 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"322 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "325 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"323 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "325 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"324 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "325 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"325 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "326 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"326 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "327 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"327 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "328 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"328 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "331 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"328 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "337 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"329 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "331 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"330 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "331 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"331 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "332 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"332 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "335 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"333 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "335 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"334 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "335 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"335 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "336 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"336 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "337 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"337 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "338 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"338 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "341 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"338 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "344 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"338 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "349 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"338 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "368 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"339 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "341 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"340 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "341 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"341 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "352 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"342 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "344 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"343 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "344 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"344 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "345 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"345 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "346 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"346 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "354 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"347 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "349 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"348 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "349 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"349 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "350 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"350 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "351 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"351 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "360 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"352 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "353 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"353 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "355 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"354 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "355 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"355 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "356 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"356 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "357 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"357 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "358 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"358 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "359 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"359 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "360 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"360 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "361 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"361 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "362 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"362 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "363 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"363 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "366 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"364 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "366 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"365 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "366 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"366 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "367 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"367 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "368 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"368 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "369 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"369 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "372 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"369 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "378 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"370 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "372 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"371 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "372 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"372 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "373 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"373 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "376 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"374 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "376 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"375 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "376 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"376 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "377 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"377 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "378 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"378 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "379 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"379 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "382 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"379 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "385 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"379 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "390 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"379 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "409 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"380 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "382 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"381 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "382 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"384 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "385 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"385 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "386 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"386 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "387 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"387 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "395 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"388 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "391 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"391 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "392 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"392 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "401 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"393 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "394 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"394 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "396 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"395 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "396 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"396 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "397 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"397 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "398 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"398 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "399 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"399 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "400 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"400 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "401 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"401 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "402 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"402 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "403 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"403 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "404 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"404 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "407 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"405 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "407 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"406 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "407 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"407 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "408 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"408 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "409 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"409 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "410 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"410 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "413 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"410 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "419 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"411 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "413 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"412 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "413 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"413 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "414 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"414 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "417 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"415 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "417 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"416 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "417 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"417 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "418 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"418 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "419 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"419 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "420 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"420 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "423 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"420 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "426 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"420 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "431 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"420 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "450 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"421 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "423 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"422 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "423 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "432 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"432 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "433 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"433 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "442 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"434 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "435 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"435 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "437 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"436 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "437 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"437 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "438 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"438 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "439 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"439 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "440 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"440 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "441 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"441 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "442 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"442 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "443 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"443 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "444 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"444 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "445 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"445 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "448 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"446 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "449 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"449 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "450 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"450 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "451 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"451 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "454 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"451 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "460 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"452 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "454 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"453 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "454 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"454 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "455 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"455 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "458 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"456 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "458 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"457 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "458 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"458 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "459 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"459 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "460 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"460 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" -> "461 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"461 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "464 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"461 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "467 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"461 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "472 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"461 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "491 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"462 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "464 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"463 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "464 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"464 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "475 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"465 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "467 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"466 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "467 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"467 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "468 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"468 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "469 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"469 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "477 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"470 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "473 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"473 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "474 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"474 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "483 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"475 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "476 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"476 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "478 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"477 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "478 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"478 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "479 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"479 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "480 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"480 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "481 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"481 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "482 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"482 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However, on May 3, 2013, the Florida legislature", + "56d6ef6a0d65d21400198260": "1985", + "56d6ef6a0d65d21400198262": "New Orleans", + "56d98f0ddc89441400fdb558": "October 16, 2012", + "56d98f0ddc89441400fdb559": "10", + "56d98f0ddc89441400fdb55a": "New Orleans", + "56d98f0ddc89441400fdb55b": "1985", + "56d98f0ddc89441400fdb55c": "the Florida legislature", + "56be5523acb8001400a5032c": "May 21, 2013", + "56be5523acb8001400a5032d": "NFL owners", + "56be5523acb8001400a5032e": "2014", + "56be5523acb8001400a5032f": "$1.2 billion", + "56be5523acb8001400a50330": "San Diego", + "56beb2153aeaaa14008c9225": "Boston", + "56beb2153aeaaa14008c9226": "May 21, 2013", + "56beb2153aeaaa14008c9227": "$1.2 billion", + "56beb2153aeaaa14008c9228": "Super Bowl XXXVII", + "56beb2153aeaaa14008c9229": "San Diego", + "56bf23363aeaaa14008c952f": "2013", + "56bf23363aeaaa14008c9530": "2014", + "56bf23363aeaaa14008c9531": "$1.2 billion", + "56bf23363aeaaa14008c9532": "1985", + "56bf23363aeaaa14008c9533": "Super 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XXXVIII", + "56d6f1190d65d21400198276": "six", + "56d99179dc89441400fdb56c": "one", + "56d99179dc89441400fdb56d": "four", + "56d99179dc89441400fdb570": "John Fox", + "56be59683aeaaa14008c9058": "DeAngelo Williams", + "56be59683aeaaa14008c9059": "Kelvin Benjamin", + "56be59683aeaaa14008c905a": "seventh", + "56beb3083aeaaa14008c923d": "1978", + "56beb3083aeaaa14008c923e": "Carolina Panthers", + "56beb3083aeaaa14008c923f": "Ten", + "56beb3083aeaaa14008c9240": "eight", + "56beb3083aeaaa14008c9241": "Carolina Panthers", + "56bf2afe3aeaaa14008c9543": "1978", + "56bf2afe3aeaaa14008c9544": "2009", + "56bf2afe3aeaaa14008c9545": "2011", + "56bf2afe3aeaaa14008c9547": "torn ACL", + "56d6f2000d65d2140019827c": "Kelvin Benjamin", + "56d6f2000d65d2140019827d": "DeAngelo Williams", + "56d6f2000d65d2140019827e": "1978", + "56d6f2000d65d2140019827f": "Ten", + "56d9943fdc89441400fdb576": "Carolina Panthers", + "56d9943fdc89441400fdb577": "1978", + "56d9943fdc89441400fdb578": "Carolina Panthers", + "56d9943fdc89441400fdb57a": "Ten", + "56beb3a03aeaaa14008c9247": "six", + "56beb3a03aeaaa14008c9248": "45", + "56beb3a03aeaaa14008c9249": "10", + "56beb3a03aeaaa14008c924a": "27", + "56beb3a03aeaaa14008c924b": "Greg Olsen", + "56bf6b303aeaaa14008c960b": "45", + "56bf6b303aeaaa14008c960c": "99.4", + "56bf6b303aeaaa14008c960d": "77", + "56bf6b303aeaaa14008c960e": "key receivers", + "56bf6b303aeaaa14008c960f": "Jonathan Stewart", + "56d6f2960d65d21400198286": "six", + "56d6f2960d65d21400198287": "Cam Newton", + "56d6f2960d65d21400198288": "3,837", + "56d6f2960d65d21400198289": "45", + "56d6f2960d65d2140019828a": "six", + "56d997cddc89441400fdb586": "500", + "56d997cddc89441400fdb587": "3,837", + "56d997cddc89441400fdb588": "45", + "56d997cddc89441400fdb589": "99.4", + "56d997cddc89441400fdb58a": "39", + "56beb4343aeaaa14008c925b": "308", + "56beb4343aeaaa14008c925c": "136", + "56beb4343aeaaa14008c925d": "118", + "56beb4343aeaaa14008c925e": "four", + "56beb4343aeaaa14008c925f": "Kawann Short", + "56d6f3500d65d21400198290": "24", + "56d6f3500d65d21400198291": "Kawann Short", + "56d6f3500d65d21400198292": "four", + "56d6f3500d65d21400198293": "four", + "56d6f3500d65d21400198294": "Josh Norman", + "56d9992fdc89441400fdb59c": "24", + "56d9992fdc89441400fdb59e": "Kony Ealy", + "56d9992fdc89441400fdb59f": "Kawann Short", + "56d9992fdc89441400fdb5a0": "four", + "56beb4e43aeaaa14008c9265": "John Fox", + "56beb4e43aeaaa14008c9266": "Brock Osweiler", + "56beb4e43aeaaa14008c9267": "Indianapolis Colts", + "56beb4e43aeaaa14008c9268": "San Diego Chargers", + "56beb4e43aeaaa14008c9269": "Wade Phillips", + "56bf301c3aeaaa14008c954d": "four", + "56bf301c3aeaaa14008c954e": "Gary Kubiak", + "56bf301c3aeaaa14008c954f": "Indianapolis Colts", + "56bf301c3aeaaa14008c9550": "39", + "56bf301c3aeaaa14008c9551": "plantar fasciitis", + "56d6f4030d65d2140019829a": "Gary Kubiak", + "56d6f4030d65d2140019829b": "Peyton Manning", + "56d6f4030d65d2140019829c": "plantar fasciitis", + "56d6f4030d65d2140019829d": "39", + "56d6f4030d65d2140019829e": "13\u20137", + "56d99b7bdc89441400fdb5c8": "John Fox", + "56d99b7bdc89441400fdb5c9": "Manning", + "56d99b7bdc89441400fdb5ca": "John Fox", + "56d99b7bdc89441400fdb5cb": "left", + "56d99b7bdc89441400fdb5cc": "Wade Phillips", + "56beb57b3aeaaa14008c9279": "67.9", + "56beb57b3aeaaa14008c927a": "2,249 yards", + "56beb57b3aeaaa14008c927b": "Demaryius Thomas", + "56beb57b3aeaaa14008c927c": "C. J. Anderson", + "56beb57b3aeaaa14008c927d": "10", + "56bf38383aeaaa14008c956b": "67.9", + "56bf38383aeaaa14008c956c": "2,249", + "56bf38383aeaaa14008c956d": "nine touchdowns", + "56bf38383aeaaa14008c956e": "Demaryius Thomas", + "56bf38383aeaaa14008c956f": "Veteran receiver", + "56d6fe0b0d65d214001982a4": "67.9", + "56d6fe0b0d65d214001982a5": "17", + "56d6fe0b0d65d214001982a6": "Demaryius Thomas", + "56d6fe0b0d65d214001982a7": "five", + "56d99c44dc89441400fdb5d6": "67.9", + "56d99c44dc89441400fdb5d7": "17", + "56d99c44dc89441400fdb5d8": "Emmanuel Sanders", + "56d99c44dc89441400fdb5d9": "C. J. Anderson", + "56d99c44dc89441400fdb5da": "4.7", + "56beb6533aeaaa14008c928d": "4,530", + "56beb6533aeaaa14008c928e": "5\u00bd", + "56beb6533aeaaa14008c9290": "Brandon Marshall", + "56beb6533aeaaa14008c9291": "three", + "56bf3e803aeaaa14008c9588": "Linebacker", + "56bf3e803aeaaa14008c9589": "Linebacker", + "56bf3e803aeaaa14008c958b": "Defensive ends", + "56d6fea90d65d214001982ae": "296", + "56d6fea90d65d214001982af": "Von Miller", + "56d6fea90d65d214001982b0": "Brandon Marshall", + "56d6fea90d65d214001982b2": "three", + "56d99da8dc89441400fdb5fd": "Von Miller", + "56d99da8dc89441400fdb5ff": "Brandon Marshall", + "56d99da8dc89441400fdb600": "Derek Wolfe and Malik Jackson", + "56beb6f23aeaaa14008c92a1": "Seattle Seahawks", + "56beb6f23aeaaa14008c92a2": "Arizona Cardinals", + "56beb6f23aeaaa14008c92a3": "487", + "56beb6f23aeaaa14008c92a4": "49\u201315", + "56beb6f23aeaaa14008c92a5": "31\u20130 halftime lead and then holding off a furious second half comeback attempt to win 31\u201324", + "56bf34293aeaaa14008c9559": "Arizona Cardinals", + "56bf34293aeaaa14008c955a": "49\u201315", + "56bf34293aeaaa14008c955b": "49\u201315", + "56d701280d65d214001982b8": "Seattle Seahawks", + "56d701280d65d214001982ba": "Seattle Seahawks", + "56d701280d65d214001982bc": "seven", + "56d99e78dc89441400fdb616": "Seattle Seahawks", + "56d99e78dc89441400fdb618": "49\u201315", + "56d99e78dc89441400fdb619": "Arizona Cardinals", + "56d99e78dc89441400fdb61a": "487", + "56beb7953aeaaa14008c92ab": "Pittsburgh Steelers", + "56beb7953aeaaa14008c92ac": "11", + "56beb7953aeaaa14008c92ad": "New England Patriots", + "56beb7953aeaaa14008c92ae": "20\u201318", + "56beb7953aeaaa14008c92af": "17 seconds", + "56bf36b93aeaaa14008c9561": "Pittsburgh Steelers", + "56bf36b93aeaaa14008c9562": "11 points", + "56bf36b93aeaaa14008c9563": "New England Patriots", + "56bf36b93aeaaa14008c9564": "17", + "56bf36b93aeaaa14008c9565": "Manning", + "56d7018a0d65d214001982c2": "Pittsburgh Steelers", + "56d7018a0d65d214001982c3": "11", + "56d7018a0d65d214001982c5": "New England Patriots", + "56d99f99dc89441400fdb628": "Pittsburgh Steelers", + "56d99f99dc89441400fdb629": "New England Patriots", + "56d99f99dc89441400fdb62c": "17", + "56beb7fd3aeaaa14008c92b5": "Thomas Davis", + "56beb7fd3aeaaa14008c92b6": "broken arm", + "56beb7fd3aeaaa14008c92b7": "three", + "56beb7fd3aeaaa14008c92b8": "11", + "56bf3a223aeaaa14008c9575": "ACL tears", + "56bf3a223aeaaa14008c9576": "broken arm", + "56bf3a223aeaaa14008c9577": "11", + "56bf3a223aeaaa14008c9579": "Super Bowl", + "56d703d10d65d214001982d6": "three", + "56d703d10d65d214001982d7": "broken arm", + "56d703d10d65d214001982d8": "11", + "56d9a026dc89441400fdb632": "Thomas Davis", + "56beb86b3aeaaa14008c92bd": "39", + "56beb86b3aeaaa14008c92be": "John Elway", + "56beb86b3aeaaa14008c92bf": "38", + "56beb86b3aeaaa14008c92c0": "Executive Vice President of Football Operations and General Manager", + "56beb86b3aeaaa14008c92c1": "Broncos", + "56bf3fd53aeaaa14008c9591": "Broncos", + "56bf3fd53aeaaa14008c9592": "John Elway", + "56bf3fd53aeaaa14008c9593": "38", + "56bf3fd53aeaaa14008c9594": "John Elway", + "56bf3fd53aeaaa14008c9595": "two", + "56d704430d65d214001982de": "two", + "56d704430d65d214001982e0": "Peyton Manning", + "56d704430d65d214001982e1": "Peyton Manning", + "56d704430d65d214001982e2": "Super Bowl XXXIII", + "56d9a0eadc89441400fdb63e": "Peyton Manning", + "56d9a0eadc89441400fdb63f": "39", + "56d9a0eadc89441400fdb640": "John Elway", + "56beb90c3aeaaa14008c92c7": "1998", + "56beb90c3aeaaa14008c92c8": "2011", + "56beb90c3aeaaa14008c92c9": "26", + "56beb90c3aeaaa14008c92ca": "26", + "56beb90c3aeaaa14008c92cb": "Newton", + "56bf41013aeaaa14008c959b": "Manning", + "56bf41013aeaaa14008c959c": "Newton", + "56bf41013aeaaa14008c959d": "26", + "56bf41013aeaaa14008c959e": "quarterback", + "56d7096b0d65d214001982fc": "1998", + "56d7096b0d65d214001982fd": "1998", + "56d7096b0d65d214001982fe": "Newton", + "56d9a199dc89441400fdb647": "2011", + "56d9a199dc89441400fdb648": "26", + "56d9a199dc89441400fdb649": "26", + "56beb97c3aeaaa14008c92db": "Super Bowl XX", + "56beb97c3aeaaa14008c92dc": "Chicago Bears", + "56beb97c3aeaaa14008c92dd": "linebacker", + "56beb97c3aeaaa14008c92de": "Elway", + "56beb97c3aeaaa14008c92df": "Broncos", + "56bf6c3e3aeaaa14008c9615": "linebacker", + "56bf6c3e3aeaaa14008c9617": "Elway", + "56d709ef0d65d21400198306": "Kubiak", + "56d709ef0d65d21400198307": "Super Bowl XX", + "56beba103aeaaa14008c92e5": "Justin Tucker", + "56beba103aeaaa14008c92e6": "Bermuda 419", + "56beba103aeaaa14008c92e7": "Ed Mangan", + "56beba103aeaaa14008c92e8": "Baltimore Ravens", + "56beba103aeaaa14008c92e9": "kicker", + "56bf467d3aeaaa14008c95a5": "Justin Tucker", + "56bf467d3aeaaa14008c95a6": "kicker", + "56bf467d3aeaaa14008c95a7": "Bermuda 419 turf", + "56d70adc0d65d21400198311": "Justin Tucker", + "56d70adc0d65d21400198312": "re-sodded the field with a new playing surface", + "56d70adc0d65d21400198313": "Bermuda 419 turf", + "56d70adc0d65d21400198314": "cleats", + "56d9a419dc89441400fdb678": "Justin Tucker", + "56d9a419dc89441400fdb679": "Bermuda 419 turf", + "56bebad93aeaaa14008c92f9": "Pittsburgh Steelers", + "56bebad93aeaaa14008c92fa": "34\u201319", + "56bebad93aeaaa14008c92fb": "Denver", + "56bebad93aeaaa14008c92fc": "white", + "56bebad93aeaaa14008c92fd": "Super Bowl XXXIII", + "56bf48cc3aeaaa14008c95ab": "Super Bowl XXXIII", + "56bf48cc3aeaaa14008c95ac": "34\u201319", + "56bf48cc3aeaaa14008c95ae": "Atlanta Falcons", + "56bf48cc3aeaaa14008c95af": "white", + "56d70ccc0d65d2140019831d": "white", + "56d70ccc0d65d2140019831f": "Pittsburgh Steelers", + "56d9a637dc89441400fdb697": "Super Bowl XXXIII", + "56d9a637dc89441400fdb698": "blue", + "56d9a637dc89441400fdb699": "orange", + "56d9a637dc89441400fdb69a": "blue", + "56bebb293aeaaa14008c9303": "Stanford", + "56bebb293aeaaa14008c9304": "Stanford University", + "56bebb293aeaaa14008c9305": "San Jose", + "56bebb293aeaaa14008c9306": "Santa Clara", + "56bf49993aeaaa14008c95b5": "San Jose Marriott", + "56bf49993aeaaa14008c95b6": "San Jose Marriott", + "56bf49993aeaaa14008c95b7": "San Jose Marriott", + "56bf49993aeaaa14008c95b8": "Stanford University", + "56d70d240d65d21400198326": "San Jose State practice facility", + "56d70d240d65d21400198327": "San Jose Marriott", + "56d70d240d65d21400198328": "Stanford University", + "56d70d240d65d21400198329": "Santa Clara Marriott", + "56d9a6b4dc89441400fdb6a0": "San Jose State practice facility", + "56d9a6b4dc89441400fdb6a1": "San Jose Marriott", + "56d9a6b4dc89441400fdb6a2": "Stanford University", + "56d9a6b4dc89441400fdb6a3": "Santa Clara Marriott", + "56bebbbf3aeaaa14008c9315": "June 4, 2014", + "56bebbbf3aeaaa14008c9316": "Super Bowl V", + "56bebbbf3aeaaa14008c9317": "Jaime Weston", + "56bebbbf3aeaaa14008c9318": "Super Bowl XLV", + "56bebbbf3aeaaa14008c9319": "Vince Lombardi", + "56bf4e1b3aeaaa14008c95bd": "2014", + "56bf4e1b3aeaaa14008c95be": "Super Bowl LI", + "56bf4e1b3aeaaa14008c95c0": "Super Bowl 50", + "56bf4e1b3aeaaa14008c95c1": "gold", + "56d70daa0d65d21400198332": "June 4, 2014", + "56d70daa0d65d21400198333": "Arabic numerals", + "56d70daa0d65d21400198334": "Arabic", + "56d70daa0d65d21400198335": "gold", + "56d70daa0d65d21400198336": "Super Bowl LI", + "56d9a7addc89441400fdb6a8": "Arabic", + "56d9a7addc89441400fdb6ab": "Super Bowl 50", + "56bebc383aeaaa14008c931f": "gold", + "56bebc383aeaaa14008c9320": "week 7", + "56bebc383aeaaa14008c9321": "50", + "56bf52483aeaaa14008c95c7": "gold", + "56bf52483aeaaa14008c95c8": "Gold", + "56d70e570d65d2140019833c": "Golden Super Bowl", + "56d70e570d65d2140019833e": "Gold footballs", + "56d70e570d65d2140019833f": "50", + "56d9b01fdc89441400fdb6d4": "gold", + "56bebcbe3aeaaa14008c9325": "Moscone Center", + "56bebcbe3aeaaa14008c9326": "San Francisco", + "56bebcbe3aeaaa14008c9327": "Ed Lee", + "56bebcbe3aeaaa14008c9328": "Jane Kim", + "56bebcbe3aeaaa14008c9329": "January 30", + "56bf53e73aeaaa14008c95cb": "More than 1 million", + "56bf53e73aeaaa14008c95cc": "Ed Lee", + "56bf53e73aeaaa14008c95cd": "Moscone Center", + "56bf53e73aeaaa14008c95ce": "Super Bowl City", + "56d7145c0d65d2140019834c": "Moscone Center", + "56d7145c0d65d2140019834d": "Super Bowl City", + "56d7145c0d65d2140019834f": "Ed Lee", + "56d9b389dc89441400fdb6ec": "Super Bowl City", + "56d9b389dc89441400fdb6ed": "More than 1 million", + "56d9b389dc89441400fdb6ee": "Ed Lee", + "56d9b389dc89441400fdb6ef": "$5 million", + "56d9b389dc89441400fdb6f0": "NFL Experience", + "56bebd713aeaaa14008c932f": "Santa Clara University", + "56bebd713aeaaa14008c9330": "$2 million", + "56bebd713aeaaa14008c9331": "week", + "56bf555e3aeaaa14008c95d3": "$2 million", + "56bf555e3aeaaa14008c95d4": "pep rally", + "56bf555e3aeaaa14008c95d5": "the city council", + "56d714cd0d65d21400198356": "Bellomy Field", + "56d714cd0d65d21400198358": "A professional fundraiser will aid in finding business sponsors and individual donors, but still may need the city council", + "56d714cd0d65d21400198359": "the city council", + "56d9b43edc89441400fdb700": "$2 million", + "56d9b43edc89441400fdb701": "city council", + "56bebde53aeaaa14008c9335": "February 1, 2016", + "56bebde53aeaaa14008c9336": "Tuesday afternoon", + "56bebde53aeaaa14008c9337": "SAP Center", + "56bebde53aeaaa14008c9338": "San Jose", + "56bebde53aeaaa14008c9339": "Golden Gate Bridge", + "56bf57043aeaaa14008c95d9": "Tuesday afternoon", + "56bf57043aeaaa14008c95da": "Tuesday", + "56bf57043aeaaa14008c95db": "Super Bowl Opening Night", + "56bf57043aeaaa14008c95dc": "SAP Center", + "56bf57043aeaaa14008c95dd": "San Jose", + "56d71bd80d65d2140019835e": "Tuesday afternoon", + "56d71bd80d65d21400198360": "Super Bowl Opening Night", + "56d71bd80d65d21400198361": "SAP Center in San Jose", + "56d71bd80d65d21400198362": "Golden Gate Bridge", + "56d9b4ebdc89441400fdb708": "Monday evening", + "56d9b4ebdc89441400fdb709": "Super Bowl Opening Night", + "56d9b4ebdc89441400fdb70a": "SAP Center in San Jose", + "56d9b4ebdc89441400fdb70b": "Golden Gate Bridge", + "56d9b4ebdc89441400fdb70c": "February 1, 2016", + "56bebe873aeaaa14008c933f": "Business Connect", + "56bebe873aeaaa14008c9340": "over $40 million", + "56bebe873aeaaa14008c9341": "Dignity", + "56bebe873aeaaa14008c9342": "Apple", + "56bebe873aeaaa14008c9343": "Apple, Google, Yahoo!, Intel, Gap, Chevron", + "56bf59523aeaaa14008c95e3": "Business Connect", + "56bf59523aeaaa14008c95e4": "over $40 million", + "56bf59523aeaaa14008c95e5": "through sponsors including Apple, Google, Yahoo!, Intel, Gap, Chevron, and Dignity Health", + "56d71cb60d65d21400198368": "Business Connect", + "56d9b5ffdc89441400fdb720": "Business Connect", + "56d9b5ffdc89441400fdb721": "over $40 million", + "56bebec43aeaaa14008c9349": "25 percent", + "56bebec43aeaaa14008c934a": "the 50 fund", + "56bf5abc3aeaaa14008c95e9": "25 percent", + "56bf5abc3aeaaa14008c95ea": "the 50 fund", + "56d71d150d65d2140019836e": "giving", + "56d71d150d65d2140019836f": "25 percent", + "56d71d150d65d21400198370": "the 50 fund", + "56d9b6a3dc89441400fdb72f": "25 percent", + "56d9b6a3dc89441400fdb730": "the 50 fund", + "56bec0353aeaaa14008c934d": "Vince Lombardi", + "56bec0353aeaaa14008c934e": "18", + "56bec0353aeaaa14008c934f": "33", + "56bec0353aeaaa14008c9350": "Tiffany & Co", + "56bec0353aeaaa14008c9351": "Tiffany & Co", + "56bf5b933aeaaa14008c95ed": "Vince Lombardi Trophy", + "56bf5b933aeaaa14008c95ef": "18-karat gold", + "56bf5b933aeaaa14008c95f1": "Tiffany & Co", + "56d71d9d0d65d21400198374": "Vince Lombardi Trophy", + "56d71d9d0d65d21400198377": "Tiffany & Co", + "56bec0dd3aeaaa14008c9357": "CBS", + "56bec0dd3aeaaa14008c9358": "Phil Simms", + "56bec0dd3aeaaa14008c9359": "Tracy Wolfson", + "56bec0dd3aeaaa14008c935a": "36", + "56bec0dd3aeaaa14008c935b": "5K", + "56bf5e7b3aeaaa14008c95f7": "three", + "56bf5e7b3aeaaa14008c95f8": "on the sidelines", + "56bf5e7b3aeaaa14008c95f9": "360", + "56bf5e7b3aeaaa14008c95fa": "5K resolution", + "56bf5e7b3aeaaa14008c95fb": "sidelines", + "56d71ed50d65d2140019837c": "CBS", + "56d71ed50d65d2140019837d": "three", + "56d9b7dcdc89441400fdb740": "CBS", + "56d9b7dcdc89441400fdb741": "Tracy Wolfson and Evan Washburn", + "56d9b7dcdc89441400fdb742": "Tracy Wolfson and Evan Washburn", + "56d9b7dcdc89441400fdb743": "5K resolution", + "56d9b7dcdc89441400fdb744": "5K resolution", + "56bec1823aeaaa14008c9361": "ESPN Deportes", + "56bec1823aeaaa14008c9362": "John Sutcliffe", + "56bec1823aeaaa14008c9363": "Alvaro Martin", + "56bec1823aeaaa14008c9364": "December 28, 2015", + "56bec1823aeaaa14008c9365": "Spanish", + "56bf6d343aeaaa14008c961b": "ESPN Deportes", + "56d71fc00d65d21400198386": "ESPN Deportes", + "56d71fc00d65d21400198389": "John Sutcliffe", + "56d9ba95dc89441400fdb754": "ESPN Deportes", + "56d9ba95dc89441400fdb757": "Alvaro Martin and Raul Allegre", + "56d9ba95dc89441400fdb758": "John Sutcliffe", + "56bec2013aeaaa14008c9371": "NFL Mobile", + "56bec2013aeaaa14008c9372": "WatchESPN", + "56bec2013aeaaa14008c9373": "CBSSports.com", + "56bec2013aeaaa14008c9374": "tablets, Windows 10", + "56bec2013aeaaa14008c9375": "10", + "56bf6e7a3aeaaa14008c961f": "CBSSports.com", + "56bf6e7a3aeaaa14008c9620": "Xbox One", + "56bf6e7a3aeaaa14008c9621": "Verizon Wireless", + "56bf6e7a3aeaaa14008c9622": "NFL Mobile service", + "56d7205e0d65d21400198391": "NFL", + "56d7205e0d65d21400198392": "NFL", + "56d9bc13dc89441400fdb75e": "digital streams", + "56d9bc13dc89441400fdb75f": "NFL Mobile service", + "56d9bc13dc89441400fdb760": "WatchESPN", + "56bec2573aeaaa14008c937b": "The Late Show", + "56bec2573aeaaa14008c937c": "Super Bowl 50", + "56bf6f743aeaaa14008c9631": "The Late Show", + "56bf6f743aeaaa14008c9632": "The Late Show", + "56d720c70d65d21400198396": "Super Bowl 50", + "56d720c70d65d21400198397": "the game", + "56d720c70d65d21400198398": "CBS broadcast special episodes of its late night talk shows", + "56bec3153aeaaa14008c9389": "$5,000,000", + "56bec3153aeaaa14008c938a": "Anheuser-Busch InBev", + "56bec3153aeaaa14008c938b": "Doritos", + "56bec3153aeaaa14008c938c": "20th", + "56bf717d3aeaaa14008c9635": "$5,000,000", + "56bf717d3aeaaa14008c9637": "Anheuser-Busch InBev", + "56bf717d3aeaaa14008c9638": "Doritos", + "56bf717d3aeaaa14008c9639": "Nintendo and The Pok\u00e9mon Company", + "56d721af0d65d2140019839e": "Pok\u00e9mon Company", + "56d721af0d65d2140019839f": "Anheuser-Busch InBev", + "56d721af0d65d214001983a0": "Doritos", + "56d9bdc1dc89441400fdb768": "Anheuser-Busch InBev", + "56d9bdc1dc89441400fdb769": "Anheuser-Busch InBev", + "56d9bdc1dc89441400fdb76a": "Crash the Super Bowl", + "56bec38b3aeaaa14008c9397": "Small Business Big Game", + "56bec38b3aeaaa14008c9398": "Death Wish Coffee", + "56bec38b3aeaaa14008c9399": "30-second", + "56bec38b3aeaaa14008c939a": "nine", + "56bf71e73aeaaa14008c963f": "Death Wish Coffee", + "56bf71e73aeaaa14008c9640": "nine", + "56d722330d65d214001983a6": "QuickBooks", + "56d722330d65d214001983a7": "Death Wish Coffee", + "56d722330d65d214001983a8": "nine", + "56d9be16dc89441400fdb770": "QuickBooks sponsored a \"Small Business Big Game\" contest, in which Death Wish Coffee", + "56d9be16dc89441400fdb771": "Death Wish Coffee", + "56bec4343aeaaa14008c93a9": "Jason Bourne", + "56bec4343aeaaa14008c93aa": "Gods of Egypt", + "56bec4343aeaaa14008c93ab": "Teenage Mutant Ninja Turtles: Out of the Shadows", + "56bec4343aeaaa14008c93ac": "Resurgence", + "56d723560d65d214001983ac": "Gods of Egypt", + "56d723560d65d214001983ad": "Teenage Mutant Ninja Turtles: Out of the Shadows", + "56d723560d65d214001983ae": "debut trailer for Jason Bourne", + "56d723560d65d214001983af": "Captain America: Civil War", + "56d9bf70dc89441400fdb77b": "Deadpool", + "56d9bf70dc89441400fdb77c": "Walt Disney Studios", + "56d9bf70dc89441400fdb77d": "Fox", + "56bec4a33aeaaa14008c93b1": "Westwood One", + "56bec4a33aeaaa14008c93b2": "Kevin Harlan", + "56bec4a33aeaaa14008c93b3": "Jim Gray", + "56bec4a33aeaaa14008c93b4": "Boomer Esiason", + "56bec4a33aeaaa14008c93b5": "James Lofton", + "56bf738b3aeaaa14008c9655": "Dan Fouts", + "56bf738b3aeaaa14008c9656": "Kevin Harlan", + "56d723ad0d65d214001983b4": "Westwood One", + "56d723ad0d65d214001983b5": "Kevin Harlan", + "56d723ad0d65d214001983b8": "Jim Gray", + "56d9c049dc89441400fdb78e": "Kevin Harlan", + "56d9c049dc89441400fdb78f": "Boomer Esiason and Dan Fouts", + "56d9c049dc89441400fdb790": "James Lofton and Mark Malone", + "56d9c049dc89441400fdb791": "pre-game and halftime coverage", + "56d9c049dc89441400fdb792": "North America", + "56bec5233aeaaa14008c93cf": "KRFX", + "56bec5233aeaaa14008c93d0": "Dave Logan", + "56bec5233aeaaa14008c93d1": "1110 AM", + "56bec5233aeaaa14008c93d2": "Chester", + "56bec5233aeaaa14008c93d3": "Dave Logan", + "56d724620d65d214001983be": "Dave Logan", + "56d724620d65d214001983bf": "Ed McCaffrey", + "56d724620d65d214001983c0": "WBT", + "56d724620d65d214001983c1": "Mick Mixon", + "56d9c203dc89441400fdb7a0": "KOA (850 AM) and KRFX (103.5 FM)", + "56d9c203dc89441400fdb7a3": "WBT", + "56bec5ff3aeaaa14008c93e3": "BBC Radio 5 Live", + "56bec5ff3aeaaa14008c93e4": "5 Live Sports Extra", + "56bec5ff3aeaaa14008c93e5": "Darren Fletcher", + "56d724ea0d65d214001983c8": "BBC Radio 5 Live and 5 Live Sports Extra will carry the contest. The BBC", + "56d724ea0d65d214001983c9": "Greg Brady", + "56bec6573aeaaa14008c93e9": "Bart Starr", + "56bec6573aeaaa14008c93ea": "Chuck Howley", + "56bec6573aeaaa14008c93eb": "Peyton Manning", + "56bec6573aeaaa14008c93ec": "2001", + "56bec6573aeaaa14008c93ed": "Peyton Manning", + "56d7251d0d65d214001983cc": "39", + "56d7251d0d65d214001983cd": "Peyton Manning", + "56d7251d0d65d214001983cf": "Harvey Martin", + "56d9c3a6dc89441400fdb7b4": "39", + "56d9c3a6dc89441400fdb7b5": "43", + "56d9c3a6dc89441400fdb7b6": "Bart Starr", + "56d9c3a6dc89441400fdb7b7": "Peyton Manning", + "56d9c3a6dc89441400fdb7b8": "Harvey Martin", + "56bec6ac3aeaaa14008c93fd": "Six", + "56bec6ac3aeaaa14008c93fe": "the national anthem", + "56bec6ac3aeaaa14008c93ff": "Academy Award", + "56bec6ac3aeaaa14008c9400": "American Sign Language", + "56bec6ac3aeaaa14008c9401": "American Sign Language", + "56d20650e7d4791d00902614": "Lady Gaga", + "56d20650e7d4791d00902615": "Marlee Matlin", + "56d7253b0d65d214001983d4": "Lady Gaga", + "56d7253b0d65d214001983d5": "Marlee Matlin", + "56d9c455dc89441400fdb7c4": "Lady Gaga", + "56d9c455dc89441400fdb7c5": "Six", + "56d9c455dc89441400fdb7c6": "Marlee Matlin", + "56bec7353aeaaa14008c940d": "December 3", + "56bec7353aeaaa14008c940e": "British", + "56bec7353aeaaa14008c940f": "Super Bowl XLVII", + "56bec7353aeaaa14008c9410": "Hymn for the Weekend", + "56bec7353aeaaa14008c9411": "Super Bowl XLVIII", + "56d725790d65d214001983d8": "Bruno Mars", + "56d725790d65d214001983da": "Pepsi", + "56d725790d65d214001983db": "Hymn for the Weekend", + "56d9c551dc89441400fdb7d0": "Bruno Mars", + "56d9c551dc89441400fdb7d1": "Beyonc\u00e9", + "56d9c551dc89441400fdb7d2": "Hymn for the Weekend", + "56d9c551dc89441400fdb7d3": "Bruno Mars", + "56bec7a63aeaaa14008c9417": "Denver", + "56bec7a63aeaaa14008c9418": "Owen Daniels", + "56bec7a63aeaaa14008c9419": "Ronnie Hillman", + "56bec7a63aeaaa14008c941a": "Brandon McManus", + "56bec7a63aeaaa14008c941b": "C. J. Anderson", + "56d728a10d65d21400198413": "18", + "56d728a10d65d21400198414": "Shaq Thompson", + "56d728a10d65d21400198415": "Brandon McManus", + "56d728a10d65d21400198416": "a deficit", + "56d9c5e7dc89441400fdb7d8": "Denver", + "56d9c5e7dc89441400fdb7d9": "Owen Daniels", + "56d9c5e7dc89441400fdb7da": "C. J. Anderson", + "56d9c5e7dc89441400fdb7db": "Shaq Thompson", + "56d9c5e7dc89441400fdb7dc": "a deficit", + "56bec8243aeaaa14008c942b": "Mike Carey", + "56bec8243aeaaa14008c942c": "Cam Newton", + "56bec8243aeaaa14008c942d": "linebacker Von Miller", + "56bec8243aeaaa14008c942e": "Malik Jackson", + "56bec8243aeaaa14008c942f": "Super Bowl XXVIII", + "56d728e00d65d2140019841c": "Cam Newton", + "56d728e00d65d2140019841d": "Mike Carey", + "56d728e00d65d2140019841e": "linebacker Von Miller", + "56d728e00d65d2140019841f": "Malik Jackson", + "56d728e00d65d21400198420": "1993", + "56d9c660dc89441400fdb7e7": "Mike Carey", + "56d9c660dc89441400fdb7e8": "linebacker Von Miller", + "56d9c660dc89441400fdb7e9": "Malik Jackson", + "56d9c660dc89441400fdb7ea": "1993 season", + "56bec8a13aeaaa14008c9435": "Jonathan Stewart", + "56bec8a13aeaaa14008c9436": "Jordan Norwood", + "56bec8a13aeaaa14008c9437": "28", + "56bec8a13aeaaa14008c9438": "61", + "56bec8a13aeaaa14008c9439": "33", + "56d729180d65d21400198426": "51", + "56d729180d65d21400198427": "Jonathan Stewart", + "56d729180d65d21400198428": "11:28", + "56d729180d65d21400198429": "Jordan Norwood", + "56d729180d65d2140019842a": "33", + "56d9c6e0dc89441400fdb7f0": "Jonathan Stewart", + "56d9c6e0dc89441400fdb7f4": "10\u20137", + "56bec9133aeaaa14008c9445": "Darian Stewart", + "56bec9133aeaaa14008c9446": "linebacker", + "56bec9133aeaaa14008c9447": "Kony Ealy", + "56bec9133aeaaa14008c9448": "DeMarcus Ware", + "56bec9133aeaaa14008c9449": "DeMarcus Ware", + "56d729ec0d65d21400198430": "Mike Tolbert", + "56d729ec0d65d21400198431": "Kony Ealy", + "56d729ec0d65d21400198432": "19", + "56d729ec0d65d21400198434": "Darian Stewart", + "56d9c79edc89441400fdb804": "Mike Tolbert", + "56d9c79edc89441400fdb805": "Danny Trevathan", + "56d9c79edc89441400fdb806": "Kony Ealy", + "56d9c79edc89441400fdb807": "The Panthers could not gain any yards with their possession and had to punt", + "56d9c79edc89441400fdb808": "DeMarcus Ware", + "56bec98e3aeaaa14008c9455": "Ted Ginn Jr.", + "56bec98e3aeaaa14008c9456": "Graham Gano", + "56bec98e3aeaaa14008c9457": "33", + "56bec98e3aeaaa14008c9458": "McManus", + "56bec98e3aeaaa14008c9459": "T. J. Ward", + "56d7282f0d65d21400198408": "Ted Ginn Jr.", + "56d7282f0d65d21400198409": "the uprights", + "56d7282f0d65d2140019840a": "safety T. J. Ward", + "56d7282f0d65d2140019840c": "Trevathan", + "56d9c92bdc89441400fdb80e": "Ted Ginn Jr.", + "56d9c92bdc89441400fdb80f": "26", + "56d9c92bdc89441400fdb810": "Graham Gano", + "56d9c92bdc89441400fdb811": "Emmanuel Sanders", + "56bec9e83aeaaa14008c945f": "Ealy", + "56bec9e83aeaaa14008c9460": "39", + "56bec9e83aeaaa14008c9461": "Devin Funchess", + "56bec9e83aeaaa14008c9462": "Stewart", + "56d7261e0d65d214001983e0": "41", + "56d7261e0d65d214001983e1": "Ealy", + "56d7261e0d65d214001983e2": "Carolina on the 50-yard line", + "56d7261e0d65d214001983e4": "punts", + "56d9ca0adc89441400fdb820": "Ealy", + "56d9ca0adc89441400fdb821": "50", + "56d9ca0adc89441400fdb822": "39", + "56d9ca0adc89441400fdb823": "one", + "56beca913aeaaa14008c946d": "24", + "56beca913aeaaa14008c946e": "Miller stripped the ball away from Newton", + "56beca913aeaaa14008c946f": "Josh Norman", + "56beca913aeaaa14008c9470": "Newton", + "56beca913aeaaa14008c9471": "Bennie Fowler", + "56d726b60d65d214001983ea": "Miller", + "56d726b60d65d214001983eb": "Ward", + "56d726b60d65d214001983ec": "Newton", + "56d726b60d65d214001983ed": "Josh Norman", + "56d726b60d65d214001983ee": "3:08", + "56d9cb47dc89441400fdb832": "4:51", + "56d9cb47dc89441400fdb833": "Miller stripped the ball away from Newton, and after several players dove for it, it took a long bounce backwards and was recovered by Ward", + "56d9cb47dc89441400fdb834": "Ward", + "56d9cb47dc89441400fdb835": "three", + "56d9cb47dc89441400fdb836": "Anderson", + "56becaf93aeaaa14008c9481": "five", + "56becaf93aeaaa14008c9482": "zero", + "56becaf93aeaaa14008c9483": "four", + "56becaf93aeaaa14008c9484": "Thomas Davis", + "56becaf93aeaaa14008c9485": "18 of 41 passes for 265 yards", + "56d7270c0d65d214001983f4": "one", + "56d7270c0d65d214001983f5": "zero", + "56d7270c0d65d214001983f6": "Anderson", + "56d7270c0d65d214001983f7": "Sanders", + "56d7270c0d65d214001983f8": "Thomas Davis", + "56d9ccacdc89441400fdb842": "Sanders", + "56d9ccacdc89441400fdb843": "Anderson", + "56d9ccacdc89441400fdb844": "11", + "56d9ccacdc89441400fdb845": "18 of 41 passes for 265 yards", + "56d9ccacdc89441400fdb846": "four", + "56becb823aeaaa14008c948b": "315 to 194", + "56becb823aeaaa14008c948c": "21 to 11", + "56becb823aeaaa14008c948d": "Baltimore Ravens", + "56becb823aeaaa14008c948e": "Jordan Norwood", + "56becb823aeaaa14008c948f": "Gary Kubiak", + "56d7277c0d65d214001983fe": "315 to 194", + "56d7277c0d65d214001983ff": "21 to 11", + "56d7277c0d65d21400198401": "Chicago Bears", + "56d7277c0d65d21400198402": "Baltimore Ravens", + "56d9cd9adc89441400fdb84c": "21 to 11", + "56d9cd9adc89441400fdb84d": "21 to 11", + "56d9cd9adc89441400fdb84e": "Baltimore Ravens", + "56d9cd9adc89441400fdb84f": "Chicago Bears", + "56d9cd9adc89441400fdb850": "two", + "5733a5f54776f41900660f45": "Nobel Prize", + "5733a5f54776f41900660f48": "1745", + "5733a5f54776f41900660f44": "Maria Sk\u0142odowska-Curie", + "5733a5f54776f41900660f46": "Famous musicians", + "5733a5f54776f41900660f47": "seven months", + "57336755d058e614000b5a3d": "100", + "57336755d058e614000b5a3f": "Krasi\u0144ski Palace Garden", + "57336755d058e614000b5a3c": "The Saxon Garden", + "57336755d058e614000b5a3e": "east", + "57336755d058e614000b5a40": "\u0141azienki Park", + "57337ddc4776f41900660bbb": "15 kilometres (9 miles)", + "57337ddc4776f41900660bbc": "otter, beaver and hundreds of bird species", + "57337ddc4776f41900660bba": "13", + "57337ddc4776f41900660bbd": "several", + "57337ddc4776f41900660bbe": "to clean them of plants and sediments", + "57337ea24776f41900660bd0": "foreign-born inhabitants", + "57337ea24776f41900660bd3": "833,500", + "57337ea24776f41900660bd2": "34%", + "57337ea24776f41900660bd1": "Jewish", + "57337ea24776f41900660bd4": "internal migration and urbanisation", + "57339555d058e614000b5df4": "Warsaw University of Technology", + "57339555d058e614000b5df5": "2,000", + "57339555d058e614000b5df6": "Medical University of Warsaw", + "57339555d058e614000b5df3": "1816", + "57339555d058e614000b5df7": "Fryderyk Chopin University of Music", + "57339902d058e614000b5e70": "1816", + "57339902d058e614000b5e71": "over two million", + "57339902d058e614000b5e72": "architects", + "57339902d058e614000b5e73": "Irena Bajerska", + "57339902d058e614000b5e74": "more than 10,000 m2", + "573399b54776f41900660e64": "infrastructure", + "573399b54776f41900660e65": "the initial Three-Year Plan", + "573399b54776f41900660e66": "solid economic growth", + "573399b54776f41900660e67": "improved markedly", + "57339a554776f41900660e74": "Warsaw", + "57339a554776f41900660e75": "Children's Memorial Health Institute", + "57339a554776f41900660e76": "Maria Sk\u0142odowska-Curie Institute of Oncology", + "57339a554776f41900660e77": "700", + "57339a554776f41900660e78": "developed", + "57339ad74776f41900660e86": "musical", + "57339ad74776f41900660e87": "events and festivals", + "57339ad74776f41900660e88": "Palace of Culture and Science", + "57339ad74776f41900660e89": "Warsaw", + "57339ad74776f41900660e8a": "events and festivals", + "57339c16d058e614000b5ec5": "Ogr\u00f3d Saski", + "57339c16d058e614000b5ec6": "Ogr\u00f3d Saski", + "57339c16d058e614000b5ec7": "from 1870 to 1939", + "57339c16d058e614000b5ec8": "Momus", + "57339c16d058e614000b5ec9": "Wojciech Bogus\u0142awski Theatre", + "57339dd94776f41900660ecc": "Wianki", + "57339dd94776f41900660ecd": "thousands", + "57339dd94776f41900660ece": "Midsummer\u2019s Night", + "57339dd94776f41900660ecf": "when they would be married, and to whom", + "57339dd94776f41900660ed0": "fern", + "57339eb9d058e614000b5ef6": "art posters", + "57339eb9d058e614000b5ef7": "60", + "57339eb9d058e614000b5ef8": "prestigious", + "57339eb9d058e614000b5ef9": "some paintings", + "57339eb9d058e614000b5efa": "arms", + "5733a1854776f41900660f0a": "Warsaw Uprising Museum", + "5733a1854776f41900660f0b": "Katy\u0144 Museum", + "5733a1854776f41900660f0c": "stereoscopic", + "5733a1854776f41900660f0d": "The Museum of Independence", + "5733a1854776f41900660f0e": "60", + "5733a2a9d058e614000b5f28": "Royal Ujazd\u00f3w Castle", + "5733a2a9d058e614000b5f29": "about 500", + "5733a2a9d058e614000b5f2a": "Zach\u0119ta National Gallery of Art", + "5733a2a9d058e614000b5f2b": "Polish and international artists", + "5733a2a9d058e614000b5f2c": "last weekend of September", + "5733a32bd058e614000b5f32": "Polonia Warsaw", + "5733a32bd058e614000b5f33": "1946", + "5733a32bd058e614000b5f34": "twice", + "5733a32bd058e614000b5f35": "Konwiktorska Street", + "5733a32bd058e614000b5f36": "disastrous financial situation", + "5733a45d4776f41900660f23": "syrenka", + "5733a45d4776f41900660f24": "The mermaid", + "5733a45d4776f41900660f25": "at least the mid-14th century", + "5733a45d4776f41900660f26": "1390", + "5733a45d4776f41900660f27": "a sword", + "5733a560d058e614000b5f77": "decided to stay on the coast of Denmark", + "5733a560d058e614000b5f78": "the depths of the oceans and seas", + "5733a560d058e614000b5f79": "on the coast of Denmark", + "5733a560d058e614000b5f7a": "Warszowa", + "5733a560d058e614000b5f7b": "heard her songs", + "5733a6ac4776f41900660f58": "Warsaw", + "5733a6ac4776f41900660f59": "1916", + "5733a6ac4776f41900660f5a": "Art Deco style in painting and art", + "5733a6ac4776f41900660f5b": "poet", + "5733a6ac4776f41900660f5c": "Isaac Bashevis Singer", + "573312fcd058e614000b56e6": "Economist Intelligence Unit", + "573312fcd058e614000b56e7": "2012", + "573312fcd058e614000b56e8": "FMCG manufacturing, metal processing, steel and electronic manufacturing and food processing", + "573312fcd058e614000b56e9": "Warsaw Stock Exchange", + "573312fcd058e614000b56ea": "Frontex", + "5733140a4776f419006606e0": "1313", + "5733140a4776f419006606e1": "Krak\u00f3w", + "5733140a4776f419006606e2": "1596", + "5733140a4776f419006606e3": "King Sigismund III Vasa", + "5733140a4776f419006606e4": "it has survived many wars, conflicts and invasions throughout its long history", + "573314e3d058e614000b56f0": "Roman Catholic", + "573314e3d058e614000b56f1": "Polish Academy of Sciences", + "573314e3d058e614000b56f2": "a UNESCO World Heritage Site", + "573314e3d058e614000b56f3": "architectural", + "573314e3d058e614000b56f4": "luxurious parks and royal gardens", + "57332442d058e614000b5720": "Warszawa", + "57332442d058e614000b5721": "belonging to Warsz", + "57332442d058e614000b5722": "a 12th/13th-century nobleman", + "57332442d058e614000b5723": "a village", + "57332442d058e614000b5724": "miasto sto\u0142eczne Warszawa", + "57332562d058e614000b5730": "Jazd\u00f3w", + "57332562d058e614000b5731": "The Prince of P\u0142ock", + "57332562d058e614000b5732": "1300", + "57332562d058e614000b5733": "1413", + "57332562d058e614000b5734": "1526", + "5733266d4776f41900660712": "General Sejm", + "5733266d4776f41900660713": "1569", + "5733266d4776f41900660714": "religious freedom in the Polish\u2013Lithuanian Commonwealth", + "5733266d4776f41900660715": "Due to its central location between the Commonwealth's capitals of Krak\u00f3w and Vilnius", + "5733266d4776f41900660716": "1596", + "57332a734776f41900660726": "until 1796", + "57332a734776f41900660727": "Kingdom of Prussia", + "57332a734776f41900660728": "Napoleon's army", + "57332a734776f41900660729": "Following the Congress of Vienna of 1815", + "57332a734776f4190066072a": "1816", + "57332b66d058e614000b5758": "4 August 1915 until November 1918", + "57332b66d058e614000b5759": "areas controlled by Russia", + "57332b66d058e614000b575a": "Pi\u0142sudski", + "57332b66d058e614000b575b": "1920", + "57332b66d058e614000b575c": "Red Army", + "57332c1e4776f4190066073a": "1 September 1939", + "57332c1e4776f4190066073b": "German Nazi", + "57332c1e4776f4190066073c": "several hundred thousand", + "57332c1e4776f4190066073d": "19 April 1943", + "57332c1e4776f4190066073e": "almost a month", + "57332e48d058e614000b5762": "the Red Army", + "57332e48d058e614000b5763": "Knowing that Stalin was hostile to the idea of an independent Poland", + "57332e48d058e614000b5764": "1 August 1944", + "57332e48d058e614000b5765": "63", + "57332e48d058e614000b5766": "between 150,000 and 200,000", + "57332f81d058e614000b5776": "Bricks for Warsaw", + "57332f81d058e614000b5777": "large prefabricated housing projects", + "57332f81d058e614000b5778": "an Eastern Bloc city", + "57332f81d058e614000b5779": "Palace of Culture and Science", + "57332f81d058e614000b577a": "UNESCO's World Heritage list", + "573330444776f41900660758": "John Paul II", + "573330444776f41900660759": "anti-communist fervor", + "573330444776f4190066075a": "less than a year", + "573330444776f4190066075b": "Victory Square", + "573330444776f4190066075c": "the incentive for the democratic changes", + "5733314e4776f4190066076a": "300", + "5733314e4776f4190066076b": "325", + "5733314e4776f4190066076c": "Vistula River", + "5733314e4776f4190066076d": "115.7 metres", + "5733314e4776f4190066076e": "right bank of the Vistula", + "57335c20d058e614000b58f9": "two", + "57335c20d058e614000b58fa": "the plain moraine plateau and the Vistula Valley", + "57335c20d058e614000b58fc": "moraine plateau", + "57335c20d058e614000b58fb": "The Vistula River", + "57335c20d058e614000b58fd": "Warsaw Escarpment", + "57335ddbd058e614000b592f": "plain moraine plateau", + "57335ddbd058e614000b5930": "former flooded terraces", + "57335ddbd058e614000b5931": "valleys and ground depressions", + "57335ddbd058e614000b5932": "the highest terrace", + "57335ddbd058e614000b5933": "pine forest", + "57335fcad058e614000b5970": "the turbulent history of the city and country", + "57335fcad058e614000b5971": "Second World War", + "57335fcad058e614000b5972": "After liberation", + "57335fcad058e614000b5973": "Leopold Kronenberg Palace", + "57335fcad058e614000b5974": "basic design typical of Eastern bloc countries", + "573361404776f4190066093c": "Gothic architecture", + "573361404776f4190066093d": "14th century", + "573361404776f4190066093e": "Masovian gothic style", + "573361404776f4190066093f": "Renaissance", + "573361404776f41900660940": "mannerist architecture", + "573362b94776f41900660974": "17th century", + "573362b94776f41900660975": "1688\u20131692", + "573362b94776f41900660976": "rococo", + "573362b94776f41900660977": "The neoclassical architecture", + "573362b94776f41900660978": "1775\u20131795", + "5733638fd058e614000b59e8": "bourgeois", + "5733638fd058e614000b59e9": "communist authorities after the war", + "5733638fd058e614000b59ea": "socialist realism", + "5733638fd058e614000b59eb": "Warsaw University of Technology building", + "5733638fd058e614000b59ec": "the most distinctive buildings", + "5733647e4776f419006609ae": "places", + "5733647e4776f419006609af": "Pawiak", + "5733647e4776f419006609b0": "The Warsaw Citadel", + "5733647e4776f419006609b1": "the children who served as messengers and frontline troops in the Warsaw Uprising", + "5733647e4776f419006609b2": "Warsaw Uprising Monument", + "573368044776f41900660a29": "green spaces", + "573368044776f41900660a2a": "New Orangery", + "573368044776f41900660a2b": "Pole Mokotowskie", + "573368044776f41900660a2c": "Park Ujazdowski", + "573368044776f41900660a2d": "1927", + "573368e54776f41900660a53": "the location of Warsaw within the border region of several big floral regions", + "573368e54776f41900660a54": "within the borders of Warsaw", + "573368e54776f41900660a55": "Masovian Primeval Forest", + "573368e54776f41900660a56": "Kabaty Forest", + "573368e54776f41900660a57": "two", + "57337f6ad058e614000b5bcb": "c. 1,300,000", + "57337f6ad058e614000b5bcc": "420,000", + "57337f6ad058e614000b5bcd": "1951", + "57337f6ad058e614000b5bce": "better", + "57337f6ad058e614000b5bcf": "residency registration", + "57338007d058e614000b5bda": "multi-cultural", + "57338007d058e614000b5bdb": "711,988", + "57338007d058e614000b5bdc": "56.2%", + "57338007d058e614000b5bdd": "2.8%", + "57338007d058e614000b5bde": "1944", + "573380e0d058e614000b5be9": "a commune", + "573380e0d058e614000b5bea": "counties or powiats", + "573380e0d058e614000b5beb": "Krak\u00f3w", + "57338160d058e614000b5bf9": "Warsaw City Council", + "57338160d058e614000b5bfa": "60", + "57338160d058e614000b5bfb": "every four years", + "57338160d058e614000b5bfc": "committees", + "57338160d058e614000b5bfd": "30", + "57338255d058e614000b5c0d": "President", + "57338255d058e614000b5c0e": "Jan Andrzej Menich", + "57338255d058e614000b5c0f": "1695\u20131696", + "57338255d058e614000b5c10": "the City council", + "57338255d058e614000b5c11": "Centrum", + "573382d24776f41900660c37": "\u015ar\u00f3dmie\u015bcie", + "573382d24776f41900660c38": "304,016", + "573382d24776f41900660c39": "emerging market", + "573382d24776f41900660c3a": "12%", + "573382d24776f41900660c3b": "191.766 billion PLN", + "5733834ed058e614000b5c26": "1817", + "5733834ed058e614000b5c27": "post-war communist control of the country and the reintroduction of a free-market economy", + "5733834ed058e614000b5c28": "April 1991", + "5733834ed058e614000b5c29": "374", + "5733834ed058e614000b5c2a": "Polish United Workers' Party (PZPR)", + "573383d0d058e614000b5c35": "1951", + "573383d0d058e614000b5c36": "Fiat 125p", + "573383d0d058e614000b5c37": "Daewoo", + "573383d0d058e614000b5c38": "AvtoZAZ", + "573383d0d058e614000b5c39": "The license for the production of the Aveo expired in February 2011 and has since not been renewed", + "573166ede6313a140071cef2": "Warszawa", + "573166ede6313a140071cef3": "Warsaw", + "573166ede6313a140071cef4": "Vistula River", + "573166ede6313a140071cef5": "1.740 million", + "573166ede6313a140071cef6": "9th", + "5732b6b5328d981900602021": "Warsaw", + "5732b6b5328d981900602022": "Vistula River", + "5732b6b5328d981900602023": "260 kilometres", + "5732b6b5328d981900602024": "2.666 million", + "5732b6b5328d981900602025": "9th", + "56ddde6b9a695914005b9628": "France", + "56ddde6b9a695914005b9629": "10th and 11th centuries", + "56ddde6b9a695914005b962a": "Denmark, Iceland and Norway", + "56ddde6b9a695914005b962b": "Rollo", + "56ddde6b9a695914005b962c": "10th", + "56dddf4066d3e219004dad5f": "William the Conqueror", + "56dddf4066d3e219004dad60": "Richard I of Normandy", + "56dddf4066d3e219004dad61": "Christian piety, becoming exponents of the Catholic orthodoxy", + "56dde0379a695914005b9636": "Normant", + "56dde0379a695914005b9637": "9th century", + "56dde0ba66d3e219004dad75": "911", + "56dde0ba66d3e219004dad76": "King Charles III of West Francia", + "56dde0ba66d3e219004dad77": "Seine", + "56dde1d966d3e219004dad8d": "Rollo", + "56dde27d9a695914005b9651": "Norse religion", + "56dde27d9a695914005b9652": "north", + "56dde2fa66d3e219004dad9b": "fighting horsemen", + "56dde3aa9a695914005b9660": "999", + "56dde3aa9a695914005b9661": "Archangel Michael", + "56dde3aa9a695914005b9662": "Monte Gargano", + "56de0daecffd8e1900b4b595": "Drogo", + "56de0daecffd8e1900b4b596": "William Iron Arm", + "56de0e25cffd8e1900b4b59a": "the Saracens", + "56de0e25cffd8e1900b4b59b": "1130", + "56de0e25cffd8e1900b4b59c": "Squillace", + "56de0ed14396321400ee2579": "Kitab Rudjdjar", + "56de0ed14396321400ee257a": "The Book of Roger", + "56de0ed14396321400ee257b": "meritocratic", + "56de0f6a4396321400ee257f": "the Pechenegs, the Bulgars, and especially the Seljuk Turks", + "56de0ffd4396321400ee258d": "1050s", + "56de0ffd4396321400ee258e": "1060s", + "56de0ffd4396321400ee258f": "Alexius Komnenos", + "56de10b44396321400ee2593": "Afranji", + "56de10b44396321400ee2594": "Oursel", + "56de10b44396321400ee2595": "Armenians", + "56de11154396321400ee25aa": "Italo-Norman", + "56de148dcffd8e1900b4b5bc": "Robert Guiscard", + "56de148dcffd8e1900b4b5bd": "February 1082", + "56de148dcffd8e1900b4b5be": "30,000", + "56de15104396321400ee25b7": "Deabolis", + "56de15104396321400ee25b8": "Bohemond", + "56de15104396321400ee25b9": "Deabolis", + "56de1563cffd8e1900b4b5c2": "1185", + "56de1563cffd8e1900b4b5c3": "Dyrrachium", + "56de1563cffd8e1900b4b5c4": "the Adriatic", + "56de15dbcffd8e1900b4b5c8": "Duke Richard II of Normandy", + "56de15dbcffd8e1900b4b5c9": "Duke Richard II of Normandy", + "56de15dbcffd8e1900b4b5ca": "Normandy", + "56de15dbcffd8e1900b4b5cb": "Sweyn Forkbeard", + "56de1645cffd8e1900b4b5d0": "Harthacnut", + "56de1645cffd8e1900b4b5d1": "1041", + "56de1645cffd8e1900b4b5d2": "Robert of Jumi\u00e8ges", + "56de16ca4396321400ee25c5": "Battle of Hastings", + "56de16ca4396321400ee25c6": "Duke William II of Normandy", + "56de16ca4396321400ee25c7": "1066", + "56de16ca4396321400ee25c8": "Anglo-Saxons", + "56de1728cffd8e1900b4b5d7": "Anglo-Saxon", + "56de179dcffd8e1900b4b5da": "1169", + "56de179dcffd8e1900b4b5db": "Bannow Bay", + "56de179dcffd8e1900b4b5dc": "Irish culture", + "56de17f9cffd8e1900b4b5e0": "Edgar", + "56de17f9cffd8e1900b4b5e1": "King Malcolm III", + "56de17f9cffd8e1900b4b5e2": "1072", + "56de17f9cffd8e1900b4b5e3": "Duncan", + "56de3cd0cffd8e1900b4b6be": "Sybilla of Normandy", + "56de3cd0cffd8e1900b4b6bf": "Norman culture", + "56de3d594396321400ee26ca": "Hereford", + "56de3d594396321400ee26cb": "the Welsh", + "56de3d594396321400ee26cc": "Edward the Confessor", + "56de3dbacffd8e1900b4b6d2": "Wales", + "56de3e414396321400ee26d8": "1018", + "56de3e414396321400ee26d9": "William of Montreuil", + "56de3ebc4396321400ee26e6": "1097", + "56de3ebc4396321400ee26e7": "Tancred", + "56de3ebc4396321400ee26e8": "Jerusalem", + "56de3efccffd8e1900b4b6fe": "380 years", + "56de3f784396321400ee26fa": "a storm", + "56de3f784396321400ee26fb": "Berengaria", + "56de3f784396321400ee26fc": "1191", + "56de3f784396321400ee26fd": "Isaac Komnenos", + "56de40da4396321400ee2708": "Conrad of Montferrat", + "56de40da4396321400ee2709": "silver", + "56de40da4396321400ee270a": "Guy de Lusignan", + "56de41504396321400ee2714": "King Sancho VI", + "56de41504396321400ee2715": "12 May 1191", + "56de41504396321400ee2716": "double coronation", + "56de48f34396321400ee2770": "1489", + "56de48f34396321400ee2771": "Knights Templar", + "56de49564396321400ee277a": "Africa", + "56de49a8cffd8e1900b4b7a7": "Bethencourt", + "56de49a8cffd8e1900b4b7a8": "Enrique P\u00e9rez de Guzm\u00e1n", + "56de49a8cffd8e1900b4b7a9": "Enrique P\u00e9rez de Guzm\u00e1n", + "56de4a474396321400ee2786": "the Channel Islands", + "56de4a474396321400ee2787": "two", + "56de4a89cffd8e1900b4b7bd": "unique Romanesque idiom", + "56de4a89cffd8e1900b4b7be": "rounded arches", + "56de4b074396321400ee2793": "Early Gothic", + "56de4b074396321400ee2794": "Early Gothic", + "56de4b074396321400ee2795": "Kingdom of Sicily", + "56de4b5c4396321400ee2799": "early 11th century", + "56de4b5c4396321400ee279a": "the dukes", + "56de4bb84396321400ee27a2": "16th century", + "56de4c324396321400ee27ab": "embroidery", + "56de4c324396321400ee27ac": "Bayeux Tapestry", + "56de4c324396321400ee27ad": "Odo, the Bishop of Bayeux and first Earl of Kent", + "56de51244396321400ee27ef": "sculptured fonts, capitals, and more importantly mosaics", + "56de51c64396321400ee27f7": "11th", + "56de51c64396321400ee27f8": "William of Volpiano and John of Ravenna", + "56de52614396321400ee27fb": "southern Italy", + "56de52614396321400ee27fc": "Sant'Eufemia", + "56de52614396321400ee27fd": "Robert Guiscard", + "56de52614396321400ee27fe": "singing", + "56df9e2838dc4217001520f6": "1856", + "56df9e2838dc4217001520f8": "Serbian American", + "56df9e2838dc4217001520f9": "1943", + "56e0b94b7aa994140058e6b7": "10 July 1856", + "56e0b94b7aa994140058e6b8": "1943", + "56e0b94b7aa994140058e6b9": "Serbian American", + "56e0b94b7aa994140058e6bb": "modern alternating current", + "56df9ee138dc421700152108": "1884", + "56df9ee138dc421700152109": "Thomas Edison", + "56df9ee138dc42170015210a": "George Westinghouse", + "56df9ee138dc42170015210b": "New York City", + "56df9ee138dc42170015210c": "War of Currents", + "56e0b9d57aa994140058e6c1": "1884", + "56e0b9d57aa994140058e6c2": "Thomas Edison", + "56e0b9d57aa994140058e6c3": "New York City", + "56e0b9d57aa994140058e6c4": "George Westinghouse", + "56e0b9d57aa994140058e6c5": "AC induction motor and transformer", + "56dfa01738dc42170015211d": "1893", + "56dfa01738dc42170015211e": "high-voltage", + "56dfa01738dc42170015211f": "mechanical oscillators/generators, electrical discharge tubes, and early X-ray imaging", + "56e0bab7231d4119001ac35b": "Colorado Springs", + "56e0bab7231d4119001ac35c": "1893", + "56e0bab7231d4119001ac35d": "wireless controlled boat", + "56e0bab7231d4119001ac35e": "Wardenclyffe Tower project", + "56dfa0d84a1a83140091ebb7": "1943", + "56dfa0d84a1a83140091ebb8": "SI unit of magnetic flux density", + "56dfa0d84a1a83140091ebb9": "New York hotels", + "56dfa0d84a1a83140091ebba": "mad scientist", + "56e0bb9f7aa994140058e6cb": "patents earned him a considerable amount of money, much of which was used to finance his own projects with varying degrees of success", + "56e0bb9f7aa994140058e6cc": "1943", + "56e0bb9f7aa994140058e6cd": "the SI unit of magnetic flux density", + "56e0bb9f7aa994140058e6ce": "1990s", + "56e0bb9f7aa994140058e6cf": "showmanship", + "56dfa13d4a1a83140091ebc1": "Croatia", + "56dfa13d4a1a83140091ebc2": "a Serbian Orthodox priest", + "56dfa13d4a1a83140091ebc3": "eidetic", + "56dfa13d4a1a83140091ebc4": "his mother's genetics and influence", + "56e0bcc0231d4119001ac36b": "Serbian Orthodox priest", + "56e0bcc0231d4119001ac36c": "Milutin Tesla", + "56e0bcc0231d4119001ac36d": "\u0110uka Tesla", + "56e0bcc0231d4119001ac36e": "making home craft tools, mechanical appliances, and the ability to memorize Serbian epic poems", + "56e0bcc0231d4119001ac36f": "western Serbia", + "56dfa1d34a1a83140091ebd4": "three", + "56dfa1d44a1a83140091ebd6": "German", + "56dfa1d44a1a83140091ebd7": "1862", + "56e0c0c7231d4119001ac375": "Dane", + "56e0c0c7231d4119001ac376": "Milka, Angelina and Marica", + "56e0c0c7231d4119001ac377": "killed in a horse-riding accident", + "56e0c0c7231d4119001ac378": "Gospi\u0107, Austrian Empire", + "56e0c0c7231d4119001ac379": "pastor", + "56dfa24a38dc421700152142": "Martin Sekuli\u0107", + "56dfa24a38dc421700152143": "German", + "56dfa24a38dc421700152144": "integral calculus", + "56dfa24a38dc421700152145": "cheating", + "56dfa24a38dc421700152146": "1873", + "56e0c1617aa994140058e6d5": "1870", + "56e0c1617aa994140058e6d6": "to attend school at the Higher Real Gymnasium", + "56e0c1617aa994140058e6d7": "Martin Sekuli\u0107", + "56e0c1617aa994140058e6d8": "German", + "56e0c1617aa994140058e6d9": "1873", + "56dfa2c54a1a83140091ebf2": "cholera", + "56dfa2c54a1a83140091ebf3": "nine months", + "56dfa2c54a1a83140091ebf4": "send him to the best engineering school", + "56dfa2c54a1a83140091ebf5": "enter the priesthood", + "56dfa2c54a1a83140091ebf6": "Smiljan", + "56e0c2307aa994140058e6df": "1873", + "56e0c2307aa994140058e6e0": "cholera", + "56e0c2307aa994140058e6e1": "nine months", + "56e0c2307aa994140058e6e2": "enter the priesthood", + "56e0c2307aa994140058e6e3": "send him to the best engineering school", + "56dfa3394a1a83140091ebfc": "Tomingaj", + "56dfa3394a1a83140091ebfd": "Mark Twain", + "56dfa3394a1a83140091ebfe": "the mountains in hunter's garb", + "56dfa3394a1a83140091ebff": "1874", + "56dfa3394a1a83140091ec00": "hunter's garb", + "56e0c2bc231d4119001ac389": "contact with nature made him stronger, both physically and mentally", + "56e0c2bc231d4119001ac38a": "1874", + "56e0c2bc231d4119001ac38b": "explored the mountains in hunter's garb", + "56e0c2bc231d4119001ac38c": "Mark Twain", + "56dfa3c338dc421700152154": "1875", + "56dfa3c338dc421700152155": "Austrian Polytechnic", + "56dfa3c338dc421700152156": "1879", + "56dfa3c338dc421700152157": "gambling", + "56dfa3c338dc421700152158": "never", + "56e0cbf3231d4119001ac3ab": "Graz", + "56e0cbf3231d4119001ac3ac": "1875", + "56e0cbf3231d4119001ac3ad": "1879", + "56e0cbf3231d4119001ac3ae": "gambling", + "56e0cbf3231d4119001ac3af": "Tesla would be killed through overwork", + "56dfa7887aa994140058dfa9": "severed all relations with his family", + "56dfa7887aa994140058dfaa": "to hide the fact that he dropped out of school", + "56dfa7887aa994140058dfab": "a draftsman", + "56dfa7887aa994140058dfac": "beg his son to return home", + "56dfa7887aa994140058dfad": "nervous breakdown", + "56e0ccaa7aa994140058e717": "December 1878", + "56e0ccaa7aa994140058e718": "he dropped out of school", + "56e0ccaa7aa994140058e719": "he had drowned in the Mur River", + "56e0ccaa7aa994140058e71a": "draftsman", + "56e0ccaa7aa994140058e71b": "nervous breakdown", + "56dfaa047aa994140058dfbd": "not having a residence permit", + "56dfaa047aa994140058dfbe": "24 March 1879", + "56dfaa047aa994140058dfbf": "60", + "56dfaa047aa994140058dfc0": "a stroke", + "56dfaa047aa994140058dfc1": "Higher Real Gymnasium", + "56e0cd33231d4119001ac3bf": "not having a residence permit", + "56e0cd33231d4119001ac3c0": "24 March 1879", + "56e0cd33231d4119001ac3c1": "Higher Real Gymnasium", + "56e0cd33231d4119001ac3c2": "stroke", + "56dfac8e231d4119001abc5b": "Prague", + "56dfac8e231d4119001abc5c": "he was illiterate in Czech", + "56dfac8e231d4119001abc5e": "lectures", + "56dfac8e231d4119001abc5f": "Charles-Ferdinand University", + "56e0cdb9231d4119001ac3c7": "Prague", + "56e0cdb9231d4119001ac3c8": "January 1880", + "56e0cdb9231d4119001ac3c9": "Gospi\u0107", + "56e0cdb9231d4119001ac3ca": "two of Tesla's uncles", + "56dfad0a7aa994140058dfc7": "Budapest", + "56dfad0a7aa994140058dfc8": "Budapest Telephone Exchange", + "56dfad0a7aa994140058dfc9": "chief electrician", + "56dfad0a7aa994140058dfca": "telephone repeater or amplifier", + "56dfad0a7aa994140058dfcb": "draftsman", + "56e0d402231d4119001ac3fc": "1881", + "56e0d402231d4119001ac3fd": "Budapest Telephone Exchange", + "56e0d402231d4119001ac3fe": "Budapest Telephone Exchange", + "56e0d402231d4119001ac3ff": "chief electrician", + "56dfb0c8231d4119001abc83": "1882", + "56dfb0c8231d4119001abc84": "France", + "56dfb0c8231d4119001abc85": "New York City", + "56dfb0c8231d4119001abc86": "Thomas Edison", + "56dfb0c8231d4119001abc87": "France", + "56e0d54a7aa994140058e769": "France", + "56e0d54a7aa994140058e76a": "France", + "56e0d54a7aa994140058e76b": "June 1884", + "56e0d54a7aa994140058e76c": "Thomas Edison", + "56e0d54a7aa994140058e76d": "Manhattan's lower east side", + "56dfb4be7aa994140058e00d": "fifty thousand dollars", + "56dfb4be7aa994140058e00e": "payment", + "56dfb4be7aa994140058e010": "months", + "56e0d6367aa994140058e773": "fifty thousand dollars", + "56e0d6367aa994140058e774": "\"Tesla, you don't understand our American humor", + "56e0d6367aa994140058e775": "$10 a week raise over Tesla's US$18 per week salary", + "56dfb5777aa994140058e021": "Robert Lane and Benjamin Vail", + "56dfb5777aa994140058e022": "Tesla Electric Light & Manufacturing", + "56dfb5777aa994140058e023": "installed electrical arc light based illumination systems", + "56dfb5777aa994140058e024": "dynamo electric machine commutators", + "56dfb5777aa994140058e025": "electrical arc light based illumination systems", + "56e0d6cf231d4119001ac420": "Robert Lane and Benjamin Vail", + "56e0d6cf231d4119001ac421": "1886", + "56e0d6cf231d4119001ac422": "Tesla Electric Light & Manufacturing", + "56e0d6cf231d4119001ac423": "installed electrical arc light based illumination systems", + "56e0d6cf231d4119001ac424": "Tesla", + "56dfb5f5231d4119001abcb5": "penniless", + "56dfb5f5231d4119001abcb6": "penniless", + "56dfb5f5231d4119001abcb8": "ditch digger", + "56dfb5f5231d4119001abcb9": "1886/1887", + "56e0d76d231d4119001ac42b": "penniless. He even lost control of the patents he had generated since he had assigned them to the company in lieu of stock", + "56e0d76d231d4119001ac42c": "ditch digger", + "56e0d76d231d4119001ac42d": "various electrical repair jobs", + "56dfb666231d4119001abcc0": "a Western Union superintendent", + "56dfb666231d4119001abcc1": "April 1887", + "56dfb666231d4119001abcc2": "89 Liberty Street", + "56dfb666231d4119001abcc3": "89 Liberty Street in Manhattan", + "56e0d810231d4119001ac432": "late 1886", + "56e0d810231d4119001ac433": "Western Union superintendent", + "56e0d810231d4119001ac434": "Alfred S. Brown", + "56e0d810231d4119001ac435": "89 Liberty Street in Manhattan", + "56e0d810231d4119001ac436": "Tesla Electric Company", + "56dfb6d17aa994140058e053": "an induction motor", + "56dfb6d17aa994140058e054": "May 1888", + "56dfb6d17aa994140058e055": "commutator", + "56dfb6d17aa994140058e056": "sparking and the high maintenance of constantly servicing and replacing mechanical brushes", + "56dfb6d17aa994140058e057": "simple self-starting", + "56e0d9e0231d4119001ac43c": "May 1888", + "56e0d9e0231d4119001ac43d": "long-distance, high-voltage transmission", + "56e0d9e0231d4119001ac43e": "commutator", + "56e0d9e0231d4119001ac43f": "May 1888", + "56e057e1231d4119001ac043": "a friend and publicist", + "56e057e1231d4119001ac044": "American Institute of Electrical Engineers", + "56e057e1231d4119001ac045": "1888", + "56e057e1231d4119001ac046": "Tesla's patent would probably control the market", + "56e057e1231d4119001ac047": "Thomas Commerford Martin", + "56e0dbb57aa994140058e779": "Thomas Commerford Martin", + "56e0dbb57aa994140058e77a": "George Westinghouse", + "56e0dbb57aa994140058e77b": "Galileo Ferraris", + "56e0dbb57aa994140058e77c": "physicist", + "56e0dbb57aa994140058e77d": "Westinghouse Electric & Manufacturing Company", + "56e05900231d4119001ac04d": "1888", + "56e05900231d4119001ac04e": "$60,000", + "56e05900231d4119001ac04f": "George Westinghouse", + "56e05900231d4119001ac051": "consultant", + "56e0dc667aa994140058e783": "$60,000", + "56e0dc667aa994140058e784": "July 1888", + "56e0dc667aa994140058e785": "$2,000", + "56e0dc667aa994140058e786": "Pittsburgh", + "56e059c8231d4119001ac057": "Pittsburgh", + "56e059c8231d4119001ac058": "alternating current system to power the city's streetcars", + "56e059c8231d4119001ac059": "60", + "56e059c8231d4119001ac05a": "DC traction motor", + "56e0e518231d4119001ac444": "power the city's streetcars", + "56e0e518231d4119001ac445": "DC traction motor", + "56e05a78231d4119001ac062": "Thomas Edison and George Westinghouse", + "56e05a78231d4119001ac063": "rival lighting systems", + "56e05a78231d4119001ac064": "AC development", + "56e05a78231d4119001ac065": "General Electric", + "56e0e5f37aa994140058e78b": "AC", + "56e0e5f37aa994140058e78c": "Thomas Edison", + "56e0e5f37aa994140058e78d": "1888", + "56e0e5f37aa994140058e78e": "the financial strain of buying up patents", + "56e0e5f37aa994140058e78f": "General Electric", + "56e07c86231d4119001ac1cd": "George Westinghouse", + "56e07c86231d4119001ac1ce": "Chicago", + "56e07c86231d4119001ac1cf": "General Electric", + "56e07c86231d4119001ac1d0": "Tesla Polyphase System", + "56e07c86231d4119001ac1d1": "Tesla Polyphase System", + "56e0ecd37aa994140058e7d5": "George Westinghouse", + "56e0ecd37aa994140058e7d6": "Chicago", + "56e0ecd37aa994140058e7d7": "1893, George Westinghouse won the bid to light the 1893", + "56e0ecd37aa994140058e7d8": "AC power", + "56e0812c231d4119001ac213": "Richard Dean Adams", + "56e0812c231d4119001ac214": "Niagara Falls Cataract Construction Company sought Tesla's opinion on what system would be best to transmit power generated at the falls", + "56e0812c231d4119001ac215": "Westinghouse Electric", + "56e0812c231d4119001ac216": "General Electric", + "56e0812c231d4119001ac217": "two-phased system", + "56e0ee12231d4119001ac459": "Richard Dean Adams", + "56e0ee12231d4119001ac45a": "1893", + "56e0ee12231d4119001ac45b": "two-phased", + "56e0ee12231d4119001ac45c": "there was a Westinghouse system to light incandescent bulbs using two-phase alternating current", + "56e089ab231d4119001ac285": "1896", + "56e089ab231d4119001ac287": "$216,000", + "56e089ab231d4119001ac288": "$2.50 per AC horsepower", + "56e089ab231d4119001ac289": "$200,000", + "56e0ef0c231d4119001ac462": "J. P. Morgan", + "56e0ef0c231d4119001ac463": "$200,000", + "56e0ef0c231d4119001ac464": "$216,000", + "56e08a1f7aa994140058e5da": "35", + "56e08a1f7aa994140058e5db": "South Fifth Avenue laboratory", + "56e08a1f7aa994140058e5dc": "electric lamps", + "56e08a1f7aa994140058e5dd": "Tesla coil", + "56e0ef90231d4119001ac468": "30 July 1891", + "56e0ef90231d4119001ac469": "Tesla coil", + "56e0ef90231d4119001ac46a": "35", + "56e0ef90231d4119001ac46b": "wireless", + "56e08aa0231d4119001ac299": "American Institute of Electrical Engineers", + "56e08aa0231d4119001ac29a": "American Institute of Electrical Engineers", + "56e08aa0231d4119001ac29d": "1894", + "56e0f019231d4119001ac470": "vice president", + "56e0f019231d4119001ac471": "1892 to 1894", + "56e0f019231d4119001ac472": "Institute of Radio Engineers", + "56e08b3c231d4119001ac2a4": "he had noticed damaged film", + "56e08b3c231d4119001ac2a5": "the 5th Avenue laboratory fire", + "56e08b3c231d4119001ac2a6": "December 1895", + "56e08b3c231d4119001ac2a7": "metal locking screw", + "56e0f32d231d4119001ac4c8": "1894", + "56e0f32d231d4119001ac4c9": "Roentgen rays\" or \"X-Rays", + "56e0f32d231d4119001ac4ca": "lost in the 5th Avenue laboratory fire of March 1895", + "56e0f32d231d4119001ac4cb": "X-ray", + "56e0f32d231d4119001ac4cc": "Mark Twain", + "56e08d32231d4119001ac2ad": "X-ray imaging", + "56e08d32231d4119001ac2ae": "March 1896", + "56e08d32231d4119001ac2af": "radiography", + "56e08d32231d4119001ac2b0": "X-rays", + "56e08d32231d4119001ac2b1": "Tesla Coil", + "56e0f5a6231d4119001ac4d4": "March 1896", + "56e0f5a6231d4119001ac4d5": "Tesla Coil", + "56e0f5a6231d4119001ac4d6": "radiography", + "56e08f4a231d4119001ac2b7": "longitudinal waves", + "56e08f4a231d4119001ac2b8": "various causes", + "56e08f4a231d4119001ac2b9": "ozone generated in contact with the skin", + "56e08f4a231d4119001ac2ba": "his circuit and single-node X-ray-producing devices", + "56e08f4a231d4119001ac2bb": "in force-free magnetic fields", + "56e0f6aa231d4119001ac4ee": "ozone generated in contact with the skin, and to a lesser extent, by nitrous acid", + "56e0f6aa231d4119001ac4ef": "longitudinal waves", + "56e0f6aa231d4119001ac4f0": "plasmas", + "56e0f6aa231d4119001ac4f1": "Roentgen rays", + "56e0e69b7aa994140058e795": "Benjamin Lamme", + "56e0e69b7aa994140058e796": "1893", + "56e0e69b7aa994140058e797": "Westinghouse Electric", + "56e0ed557aa994140058e7dd": "the Egg of Columbus", + "56e0ed557aa994140058e7e0": "Tesla", + "56e0fa5b7aa994140058e859": "11 July 1934", + "56e0fa5b7aa994140058e85a": "break off the cathode, pass out of the tube, and physically strike him", + "56e0fa5b7aa994140058e85b": "a minute particle would break off the cathode, pass out of the tube", + "56e0fa5b7aa994140058e85c": "bits of metal", + "56e0fb14231d4119001ac525": "National Electric Light Association", + "56e0fb14231d4119001ac526": "Tesla Coil", + "56e0fb14231d4119001ac527": "Franklin Institute", + "56e0fb887aa994140058e869": "1898", + "56e0fb887aa994140058e86a": "teleautomaton", + "56e0fb887aa994140058e86b": "Madison Square Garden", + "56e0fb887aa994140058e86c": "an electrical exhibition at Madison Square Garden", + "56e0fb887aa994140058e86d": "monkey", + "56e0fc3f7aa994140058e877": "1900", + "56e0fc3f7aa994140058e878": "Guglielmo Marconi", + "56e0fc3f7aa994140058e879": "1901", + "56e0fc3f7aa994140058e87a": "1943", + "56e0fc3f7aa994140058e87b": "Supreme Court of the United States", + "56e0fd167aa994140058e881": "1899", + "56e0fd167aa994140058e882": "Pikes Peak to Paris", + "56e0fd167aa994140058e883": "15 June 1899", + "56e0fd167aa994140058e884": "five inches long", + "56e0fde0cd28a01900c673ea": "atmospheric", + "56e0fde0cd28a01900c673eb": "stationary waves", + "56e0fde0cd28a01900c673ec": "resonant frequency", + "56e0fe85e3433e1400422a6a": "lightning", + "56e0fe85e3433e1400422a6b": "up to 135 feet", + "56e0fe85e3433e1400422a6c": "15 miles away", + "56e0fe85e3433e1400422a6d": "glowed even when turned off", + "56e0fe85e3433e1400422a6e": "electrified", + "56e0ff5dcd28a01900c673fb": "power outage", + "56e0ff5dcd28a01900c673fc": "burned out", + "56e0ff5dcd28a01900c673fd": "powerful high frequency currents set up in them", + "56e0ff5dcd28a01900c673fe": "jump through the windings and destroy", + "56e10043e3433e1400422a84": "communications from another planet", + "56e10043e3433e1400422a85": "Mars", + "56e10043e3433e1400422a86": "Collier's Weekly", + "56e10043e3433e1400422a87": "communications from another planet", + "56e10043e3433e1400422a88": "July 1899", + "56e100b6cd28a01900c67403": "$100,000", + "56e100b6cd28a01900c67404": "Colorado Springs experiments", + "56e100b6cd28a01900c67405": "Colorado Springs experiments", + "56e100b6cd28a01900c67406": "1899", + "56e1011ecd28a01900c6740b": "7 January 1900", + "56e1011ecd28a01900c6740c": "torn down", + "56e1011ecd28a01900c6740d": "1904", + "56e1011ecd28a01900c6740e": "sold", + "56e10179cd28a01900c67413": "trans-Atlantic wireless telecommunications facility", + "56e10179cd28a01900c67414": "trans-Atlantic wireless telecommunications facility", + "56e10179cd28a01900c67415": "Shoreham, Long Island", + "56e101f4e3433e1400422a8e": "Morgan", + "56e101f4e3433e1400422a8f": "Morgan still owed Tesla money on the original agreement", + "56e101f4e3433e1400422a91": "shocked", + "56e10296cd28a01900c67423": "over 50", + "56e10296cd28a01900c67424": "to complete the construction of Wardenclyffe", + "56e10296cd28a01900c67425": "terminating Tesla's relationship with Morgan", + "56e10296cd28a01900c67426": "187 feet", + "56e10325cd28a01900c67435": "200", + "56e10325cd28a01900c67436": "100\u20135,000 hp", + "56e10325cd28a01900c67437": "1906", + "56e10325cd28a01900c67438": "100\u20135,000 hp", + "56e10412e3433e1400422aba": "steam", + "56e10412e3433e1400422abb": "Houston Street lab", + "56e10412e3433e1400422abc": "speed grew, it is said that the machine oscillated at the resonance frequency of his own building and, belatedly realizing the danger", + "56e10412e3433e1400422abd": "World Today", + "56e10412e3433e1400422abe": "set the earth's crust into such a state of vibration that it would rise and fall hundreds of feet and practically destroy civilization", + "56e1066be3433e1400422ae4": "application of electricity", + "56e1066be3433e1400422ae5": "saturating them unconsciously with electricity", + "56e1066be3433e1400422ae6": "William H. Maxwell", + "56e1066be3433e1400422ae7": "superintendent of New York City schools", + "56e1075ae3433e1400422afa": "overseas", + "56e1075ae3433e1400422afb": "lost", + "56e1075ae3433e1400422afc": "sold", + "56e1075ae3433e1400422afd": "$20,000", + "56e1075ae3433e1400422afe": "Edison Medal", + "56e108abe3433e1400422b0c": "Electrical Experimenter", + "56e108abe3433e1400422b0d": "on a fluorescent screen", + "56e108abe3433e1400422b0e": "modern radar", + "56e108abe3433e1400422b0f": "\u00c9mile Girardeau", + "56e1097dcd28a01900c6748f": "Thomas Edison and Nikola Tesla", + "56e1097dcd28a01900c67490": "Thomas Edison and Nikola Tesla", + "56e1097dcd28a01900c67491": "he has made known his intention to refuse the reward", + "56e1097dcd28a01900c67492": "he is announced a winner", + "56e10a28cd28a01900c674b1": "their animosity toward each other", + "56e10aa5cd28a01900c674b3": "38", + "56e10aa5cd28a01900c674b4": "Edison", + "56e10aa5cd28a01900c674b5": "1937", + "56e10b6ee3433e1400422b24": "1,655,114", + "56e10b6ee3433e1400422b25": "biplane capable of taking off vertically (VTOL aircraft", + "56e10b6ee3433e1400422b26": "less than $1,000", + "56e10b6ee3433e1400422b27": "turbine", + "56e10c61e3433e1400422b36": "$125 per month", + "56e10c61e3433e1400422b37": "$125 per month as well as paying his rent at the Hotel New Yorker, expenses the Company would pay for the rest of Tesla's life", + "56e10c61e3433e1400422b38": "the rest of Tesla's life", + "56e10c61e3433e1400422b39": "bad publicity", + "56e10d2dcd28a01900c674d7": "mechanical energy", + "56e10d2dcd28a01900c674d8": "any terrestrial distance", + "56e10d2dcd28a01900c674d9": "minimal loss", + "56e10d2dcd28a01900c674da": "mineral deposits", + "56e10d2dcd28a01900c674db": "1935", + "56e10ddce3433e1400422b48": "refused medical aid", + "56e10ddce3433e1400422b49": "a doctor", + "56e10ddce3433e1400422b4a": "broken", + "56e10ddce3433e1400422b4b": "early 1938", + "56e10ddce3433e1400422b4c": "fall of 1937", + "56e10e73cd28a01900c674eb": "teleforce", + "56e10e73cd28a01900c674ec": "Van de Graaff generator", + "56e10e73cd28a01900c674ed": "infantry", + "56e10e73cd28a01900c674ee": "anti-aircraft purposes", + "56e10e73cd28a01900c674ef": "death ray", + "56e10f14e3433e1400422b5c": "1937", + "56e10f14e3433e1400422b5d": "luncheon", + "56e10f14e3433e1400422b5e": "tungsten", + "56e10f14e3433e1400422b5f": "high voltage", + "56e10f14e3433e1400422b60": "a little", + "56e10fbacd28a01900c67509": "charged particle beam weapons", + "56e10fbacd28a01900c6750a": "Nikola Tesla Museum archive", + "56e10fbacd28a01900c6750b": "Belgrade", + "56e10fbacd28a01900c6750c": "millions", + "56e10fbacd28a01900c6750d": "all war", + "56e11044e3433e1400422b76": "steal", + "56e11044e3433e1400422b77": "the blueprint for the teleforce weapon was all in his mind", + "56e11044e3433e1400422b78": "papers", + "56e110c3cd28a01900c67531": "86", + "56e110c3cd28a01900c67532": "7 January 1943", + "56e110c3cd28a01900c67533": "maid Alice Monaghan", + "56e110c3cd28a01900c67534": "\"do not disturb\" sign", + "56e110c3cd28a01900c67535": "coronary thrombosis", + "56e11161e3433e1400422b86": "seize", + "56e11161e3433e1400422b87": "John G. Trump", + "56e11161e3433e1400422b89": "nothing", + "56e11161e3433e1400422b8a": "Manhattan Storage and Warehouse Company", + "56e111e5e3433e1400422b90": "Fiorello La Guardia", + "56e111e5e3433e1400422b91": "Louis Adamic", + "56e111e5e3433e1400422b92": "12 January", + "56e111e5e3433e1400422b93": "two thousand", + "56e111e5e3433e1400422b94": "Ferncliff Cemetery", + "56e1127bcd28a01900c67549": "Belgrade", + "56e1127bcd28a01900c6754a": "Sava Kosanovi\u0107", + "56e1127bcd28a01900c6754b": "Charlotte Muzar", + "56e1127bcd28a01900c6754c": "Nikola Tesla Museum", + "56e1127bcd28a01900c6754d": "1957", + "56e11996e3433e1400422bde": "278", + "56e11996e3433e1400422bdf": "26", + "56e11996e3433e1400422be0": "Canada", + "56e11996e3433e1400422be1": "patent archives", + "56e11a16cd28a01900c675b5": "8:10 p.m.", + "56e11a16cd28a01900c675b6": "8:10 p.m.", + "56e11a16cd28a01900c675b7": "3:00 a.m", + "56e11a16cd28a01900c675b8": "the headwaiter", + "56e11a73e3433e1400422bf0": "8 to 10 miles", + "56e11a73e3433e1400422bf1": "it stimulated his brain cells", + "56e11a73e3433e1400422bf2": "squished his toes one hundred times", + "56e11a73e3433e1400422bf3": "his brain cells", + "56e11afbcd28a01900c675c7": "telepathy", + "56e11afbcd28a01900c675c8": "newspaper editor", + "56e11afbcd28a01900c675c9": "one", + "56e11ba9cd28a01900c675d7": "pigeons", + "56e11ba9cd28a01900c675d8": "over $2,000", + "56e11ba9cd28a01900c675d9": "injured", + "56e11ba9cd28a01900c675da": "the park", + "56e11ba9cd28a01900c675db": "hotel room", + "56e11c24e3433e1400422c18": "142 pounds", + "56e11c24e3433e1400422c19": "6 feet 2 inches", + "56e11c24e3433e1400422c1a": "1888 to about 1926", + "56e11c24e3433e1400422c1b": "New York City", + "56e11cedcd28a01900c675e7": "eight", + "56e11cedcd28a01900c675e8": "blinding flashes of light would appear before his eyes, often accompanied by visions", + "56e11cedcd28a01900c675e9": "picture thinking", + "56e11cedcd28a01900c675ea": "blinding flashes of light", + "56e11cedcd28a01900c675eb": "photographic", + "56e11d8ecd28a01900c675f1": "more than 48 hours", + "56e11d8ecd28a01900c675f2": "84 hours", + "56e11d8ecd28a01900c675f3": "Graz", + "56e11d8ecd28a01900c675f4": "Kenneth Swezey", + "56e11d8ecd28a01900c675f5": "journalist", + "56e11e57e3433e1400422c28": "chastity", + "56e11e57e3433e1400422c29": "women", + "56e11e57e3433e1400422c2a": "toward the end of his life", + "56e11f05e3433e1400422c2e": "Dorothy Skerrit", + "56e11f05e3433e1400422c2f": "Robert Underwood Johnson", + "56e11f05e3433e1400422c30": "seclude", + "56e11f05e3433e1400422c31": "distinguished sweetness, sincerity, modesty, refinement, generosity, and force", + "56e11f05e3433e1400422c32": "friend", + "56e11f83cd28a01900c67611": "Francis Marion Crawford", + "56e11f83cd28a01900c67612": "his lab", + "56e11f83cd28a01900c67613": "late 1920s", + "56e12005cd28a01900c67617": "overweight people", + "56e12005cd28a01900c67618": "a secretary", + "56e12005cd28a01900c67619": "her weight", + "56e12005cd28a01900c6761a": "change her dress", + "56e120a1e3433e1400422c38": "atoms", + "56e120a1e3433e1400422c39": "atoms", + "56e120a1e3433e1400422c3a": "transmitted electrical energy", + "56e120a1e3433e1400422c3b": "19th", + "56e12110e3433e1400422c4a": "Einstein", + "56e12110e3433e1400422c4b": "antagonistic", + "56e12110e3433e1400422c4c": "theory of relativity", + "56e121b7e3433e1400422c50": "dynamic theory of gravity", + "56e121b7e3433e1400422c51": "1892", + "56e121b7e3433e1400422c52": "curved", + "56e121b7e3433e1400422c53": "81", + "56e122dacd28a01900c67639": "eugenics", + "56e122dacd28a01900c6763a": "ruthless workings of nature", + "56e122dacd28a01900c6763b": "pity", + "56e122dacd28a01900c6763c": "1937", + "56e1239acd28a01900c67641": "Queen Bees", + "56e1239acd28a01900c67642": "1926", + "56e1239acd28a01900c67643": "Queen Bees", + "56e12477e3433e1400422c5e": "post-World War I", + "56e12477e3433e1400422c5f": "Science and Discovery", + "56e12477e3433e1400422c60": "20 December 1914", + "56e12477e3433e1400422c61": "League of Nations", + "56e124f1cd28a01900c6764f": "Orthodox Christian", + "56e124f1cd28a01900c67650": "fanaticism", + "56e124f1cd28a01900c67651": "Buddhism and Christianity", + "56e1254ae3433e1400422c66": "A Machine to End War", + "56e1254ae3433e1400422c67": "uncertain", + "56e1254ae3433e1400422c68": "War", + "56e125b6e3433e1400422c6c": "Tesla Papers", + "56e125b6e3433e1400422c6d": "Ben Johnston", + "56e125b6e3433e1400422c6e": "Ben Johnston", + "56e1262fcd28a01900c67655": "the web", + "56e1262fcd28a01900c67656": "1900", + "56e1262fcd28a01900c67657": "The Problem of Increasing Human Energy", + "56e126dae3433e1400422c7c": "science fiction", + "56e126dae3433e1400422c7d": "books, films, radio, TV, music, live theater, comics and video games", + "56e126dae3433e1400422c7e": "several", + "56e127bccd28a01900c6765b": "Time", + "56e127bccd28a01900c6765c": "75th birthday", + "56e127bccd28a01900c6765d": "electrical power generation", + "56e127bccd28a01900c6765e": "Albert Einstein", + "56e127bccd28a01900c6765f": "more than 70", + "56e16182e3433e1400422e28": "Computational complexity theory", + "56e16182e3433e1400422e29": "inherent difficulty", + "56e16182e3433e1400422e2a": "A computational problem", + "56e16839cd28a01900c67887": "significant resources", + "56e16839cd28a01900c67888": "mathematical models of computation", + "56e16839cd28a01900c67889": "time and storage", + "56e16839cd28a01900c6788a": "number of gates", + "56e16839cd28a01900c6788b": "to determine the practical limits on what computers can and cannot do", + "56e17644e3433e1400422f40": "analysis of algorithms and computability theory", + "56e17644e3433e1400422f41": "computational complexity theory", + "56e17644e3433e1400422f42": "computational complexity theory", + "56e17644e3433e1400422f43": "theoretical computer science are analysis of algorithms and computability theory", + "56e17a7ccd28a01900c679a1": "a problem instance", + "56e17a7ccd28a01900c679a2": "a problem", + "56e17a7ccd28a01900c679a3": "concrete", + "56e17a7ccd28a01900c679a4": "solution", + "56e17a7ccd28a01900c679a5": "solution", + "56e17e6ee3433e1400422f7f": "2000", + "56e17e6ee3433e1400422f80": "asking for a round trip through all sites in Milan", + "56e17e6ee3433e1400422f81": "computational problems", + "56e181d9e3433e1400422fa0": "bitstrings", + "56e181d9e3433e1400422fa1": "binary alphabet", + "56e181d9e3433e1400422fa2": "bitstrings", + "56e181d9e3433e1400422fa3": "binary notation", + "56e181d9e3433e1400422fa4": "adjacency matrices", + "56e190bce3433e1400422fc8": "Decision problems", + "56e190bce3433e1400422fc9": "yes or no, or alternately either 1 or 0", + "56e190bce3433e1400422fca": "yes or no, or alternately either 1 or 0", + "56e190bce3433e1400422fcb": "yes", + "56e190bce3433e1400422fcc": "yes", + "56e19557e3433e1400422fee": "arbitrary", + "56e19557e3433e1400422ff0": "formal language", + "56e19557e3433e1400422ff1": "binary strings", + "56e19724cd28a01900c679f6": "computational problem", + "56e19724cd28a01900c679f7": "single", + "56e19724cd28a01900c679f8": "computational", + "56e19724cd28a01900c679f9": "integer factorization problem", + "56e19724cd28a01900c679fa": "more complex", + "56e1a0dccd28a01900c67a2e": "decision problems", + "56e1a0dccd28a01900c67a2f": "triples", + "56e1a38de3433e140042305c": "the size of the input in bits", + "56e1a38de3433e140042305d": "the instance", + "56e1a38de3433e140042305e": "as a function of the size of the instance", + "56e1a38de3433e140042305f": "bits", + "56e1a38de3433e1400423060": "input size", + "56e1a564cd28a01900c67a48": "Cobham", + "56e1a564cd28a01900c67a49": "the time taken", + "56e1a564cd28a01900c67a4a": "worst-case time complexity T(n)", + "56e1a564cd28a01900c67a4b": "the maximum time taken over all inputs of size n", + "56e1a564cd28a01900c67a4c": "polynomial time algorithm", + "56e1aba0e3433e1400423094": "A Turing machine", + "56e1aba0e3433e1400423095": "an algorithm", + "56e1aba0e3433e1400423097": "Turing machine", + "56e1aba0e3433e1400423098": "manipulates symbols", + "56e1aff7cd28a01900c67a68": "deterministic Turing machine", + "56e1aff7cd28a01900c67a69": "fixed set of rules to determine its future actions", + "56e1aff7cd28a01900c67a6a": "probabilistic Turing machine", + "56e1aff7cd28a01900c67a6b": "non-deterministic Turing machine", + "56e1aff7cd28a01900c67a6c": "randomized algorithms", + "56e1b00ce3433e140042309e": "complexity classes", + "56e1b00ce3433e140042309f": "when resources (such as time or space) are bounded", + "56e1b00ce3433e14004230a1": "quantum Turing machines, symmetric Turing machines and alternating Turing machines", + "56e1b169cd28a01900c67a72": "random access machines", + "56e1b169cd28a01900c67a73": "time and memory consumption", + "56e1b169cd28a01900c67a74": "time and memory", + "56e1b169cd28a01900c67a75": "the machines operate deterministically", + "56e1b355e3433e14004230b0": "non-deterministic", + "56e1b355e3433e14004230b1": "more unusual resources", + "56e1b355e3433e14004230b2": "mathematical models", + "56e1b355e3433e14004230b3": "non-deterministic time", + "56e1b62ecd28a01900c67aa3": "\"yes\" or \"no\"", + "56e1b62ecd28a01900c67aa4": "their difficulty", + "56e1b62ecd28a01900c67aa5": "DTIME(f(n)", + "56e1b62ecd28a01900c67aa6": "time f(n) if there exists a Turing machine operating in time f(n)", + "56e1b754cd28a01900c67abc": "complexity", + "56e1b754cd28a01900c67abd": "computational", + "56e1b754cd28a01900c67abe": "Blum complexity axioms", + "56e1b754cd28a01900c67abf": "complexity measures", + "56e1b754cd28a01900c67ac0": "complexity measures", + "56e1b8f3e3433e14004230e6": "best, worst and average", + "56e1b8f3e3433e14004230e7": "time complexity", + "56e1b8f3e3433e14004230e8": "different inputs of the same size", + "56e1b8f3e3433e14004230e9": "time complexity (or any other complexity measure) of different inputs", + "56e1ba41cd28a01900c67ae0": "quicksort", + "56e1ba41cd28a01900c67ae1": "worst-case", + "56e1ba41cd28a01900c67ae2": "O(n2)", + "56e1bc3ae3433e1400423104": "the most efficient algorithm solving a given problem", + "56e1bc3ae3433e1400423105": "analysis of algorithms", + "56e1bc3ae3433e1400423106": "proving lower bounds", + "56e1bc3ae3433e1400423107": "lower", + "56e1bc3ae3433e1400423108": "all possible algorithms", + "56e1bd4acd28a01900c67afc": "big O notation", + "56e1bd4acd28a01900c67afd": "constant factors and smaller terms", + "56e1bd4acd28a01900c67afe": "in big O notation", + "56e1bd4acd28a01900c67aff": "computational model", + "56e1c0f6cd28a01900c67b2c": "complexity classes", + "56e1c0f6cd28a01900c67b2d": "complicated definitions that do not fit into this framework", + "56e1c0f6cd28a01900c67b2e": "complicated definitions", + "56e1c2eee3433e1400423134": "the chosen machine model", + "56e1c2eee3433e1400423135": "quadratic time", + "56e1c2eee3433e1400423136": "single-tape", + "56e1c2eee3433e1400423137": "Cobham-Edmonds thesis", + "56e1c2eee3433e1400423138": "complexity class P", + "56e1c3e1e3433e1400423148": "time or space", + "56e1c3e1e3433e1400423149": "bound", + "56e1c3e1e3433e140042314a": "complexity classes", + "56e1c4fce3433e140042314e": "BPP, ZPP and RP", + "56e1c4fce3433e140042314f": "Boolean", + "56e1c4fce3433e1400423150": "quantum", + "56e1c4fce3433e1400423151": "#P", + "56e1c4fce3433e1400423152": "Interactive", + "56e1c720e3433e140042316a": "computation time", + "56e1c720e3433e140042316b": "n2", + "56e1c720e3433e140042316c": "time and space hierarchy theorems", + "56e1c720e3433e140042316d": "a proper hierarchy", + "56e1c720e3433e140042316e": "quantitative", + "56e1c7e2cd28a01900c67b74": "time and space hierarchy theorems", + "56e1c7e2cd28a01900c67b75": "strictly contained in EXPTIME", + "56e1c7e2cd28a01900c67b76": "PSPACE", + "56e1c9bfe3433e1400423192": "a reduction", + "56e1c9bfe3433e1400423193": "another problem", + "56e1c9bfe3433e1400423194": "no more difficult", + "56e1c9bfe3433e1400423195": "Cook reductions, Karp reductions and Levin reductions", + "56e1c9bfe3433e1400423196": "bound on the complexity of reductions", + "56e1cbe2cd28a01900c67bac": "polynomial-time reduction", + "56e1cbe2cd28a01900c67bad": "multiplying two integers", + "56e1cbe2cd28a01900c67bae": "reduction process takes polynomial time", + "56e1cbe2cd28a01900c67baf": "input to both inputs", + "56e1cbe2cd28a01900c67bb0": "multiplication", + "56e1ce08e3433e14004231a4": "the type of reduction being used", + "56e1ce08e3433e14004231a5": "an algorithm for X allows us to solve any problem in C", + "56e1ce08e3433e14004231a6": "solve any problem in C", + "56e1ce08e3433e14004231a8": "the set of NP-hard problems", + "56e1d9fee3433e14004231cb": "NP-complete", + "56e1d9fee3433e14004231cc": "difficult", + "56e1d9fee3433e14004231cd": "there is no known polynomial-time solution", + "56e1d9fee3433e14004231ce": "the set", + "56e1dc62cd28a01900c67bca": "P", + "56e1dc62cd28a01900c67bcb": "Cobham\u2013Edmonds thesis", + "56e1dc62cd28a01900c67bcc": "P", + "56e1dc62cd28a01900c67bcd": "Boolean satisfiability problem, the Hamiltonian path problem and the vertex cover problem", + "56e1dc62cd28a01900c67bce": "deterministic Turing machines", + "56e1ddfce3433e14004231d5": "more efficient solutions", + "56e1ddfce3433e14004231d6": "protein structure prediction", + "56e1ddfce3433e14004231d8": "US$1,000,000", + "56e1ded7cd28a01900c67bd4": "Ladner", + "56e1ded7cd28a01900c67bd5": "NP-intermediate problems", + "56e1ded7cd28a01900c67bd6": "graph isomorphism problem, the discrete logarithm problem and the integer factorization problem", + "56e1e9dfe3433e14004231fc": "The graph isomorphism problem", + "56e1e9dfe3433e14004231fd": "NP-complete", + "56e1e9dfe3433e14004231fe": "polynomial hierarchy", + "56e1e9dfe3433e14004231ff": "second", + "56e1e9dfe3433e1400423200": "Laszlo Babai and Eugene Luks", + "56e1ec83cd28a01900c67c0a": "The integer factorization problem", + "56e1ec83cd28a01900c67c0b": "k", + "56e1ec83cd28a01900c67c0c": "RSA algorithm", + "56e1ec83cd28a01900c67c0e": "general number field sieve", + "56e1ee4de3433e1400423210": "collapse to one class", + "56e1ee4de3433e1400423211": "P \u2286 NP \u2286 PP \u2286 PSPACE, but it is possible that P = PSPACE", + "56e1ee4de3433e1400423212": "PSPACE", + "56e1ee4de3433e1400423214": "Proving that any of these classes are unequal", + "56e1efa0e3433e140042321a": "co-NP", + "56e1efa0e3433e140042321b": "reversed", + "56e1efa0e3433e140042321c": "NP is not equal to co-NP", + "56e1efa0e3433e140042321d": "P is not equal to NP", + "56e1f10ee3433e1400423222": "L", + "56e1f10ee3433e1400423223": "complexity classes", + "56e1f10ee3433e1400423224": "complexity classes", + "56e1f10ee3433e1400423225": "NL and NC", + "56e1f10ee3433e1400423226": "it is not known if they are distinct or equal classes", + "56e1fc57e3433e140042322c": "intractable problems", + "56e1fc57e3433e140042322f": "complexity theory", + "56e1fc57e3433e1400423230": "NP-complete problems", + "56e1febfe3433e1400423236": "Presburger arithmetic", + "56e1febfe3433e1400423237": "algorithms", + "56e1febfe3433e1400423238": "NP-complete knapsack problem", + "56e1febfe3433e1400423239": "over a wide range of sizes in less than quadratic time", + "56e1febfe3433e140042323a": "NP-complete Boolean satisfiability problem", + "56e200e4cd28a01900c67c14": "Turing machines", + "56e200e4cd28a01900c67c15": "Alan Turing", + "56e200e4cd28a01900c67c16": "Turing machines", + "56e200e4cd28a01900c67c17": "1936", + "56e200e4cd28a01900c67c18": "a very robust and flexible simplification of a computer", + "56e202e9e3433e1400423240": "On the Computational Complexity of Algorithms", + "56e202e9e3433e1400423241": "Juris Hartmanis and Richard Stearns", + "56e202e9e3433e1400423242": "1965", + "56e202e9e3433e1400423243": "time and space complexity", + "56e202e9e3433e1400423244": "1965", + "56e2042ecd28a01900c67c1e": "John Myhill", + "56e2042ecd28a01900c67c1f": "1961", + "56e2042ecd28a01900c67c20": "Hisao Yamada", + "56e20a27cd28a01900c67c24": "input encoding", + "56e20a27cd28a01900c67c25": "encoding", + "56e20a3ae3433e140042324a": "Manuel Blum", + "56e20a3ae3433e140042324b": "speed-up theorem", + "56e20a3ae3433e140042324d": "Reducibility Among Combinatorial Problems", + "56e20a3ae3433e140042324e": "21", + "56e7477700c9c71400d76f23": "the curriculum", + "56e7477700c9c71400d76f24": "pedagogy", + "56e7477700c9c71400d76f25": "a university or college", + "56e7477700c9c71400d76f26": "a lesson plan", + "56e7477700c9c71400d76f27": "a school or other place of formal education", + "56e748a200c9c71400d76f37": "among cultures", + "56e748a200c9c71400d76f38": "numeracy", + "56e748a200c9c71400d76f39": "craftsmanship", + "56e748a200c9c71400d76f3a": "Teachers may provide instruction in literacy and numeracy", + "56e749dd00c9c71400d76f51": "a teacher occupying a transient or ongoing role, such as a family member", + "56e749dd00c9c71400d76f52": "formal education", + "56e749dd00c9c71400d76f53": "formal", + "56e749dd00c9c71400d76f54": "transient", + "56e749dd00c9c71400d76f55": "family member, or by anyone with knowledge or skills", + "56e74af500c9c71400d76f65": "gurus, mullahs, rabbis, pastors/youth pastors and lamas", + "56e74af500c9c71400d76f66": "religious", + "56e74af500c9c71400d76f67": "the Quran, Torah or Bible", + "56e74af500c9c71400d76f68": "Religious and spiritual teachers", + "56e74bf937bdd419002c3e33": "homeschooling", + "56e74bf937bdd419002c3e34": "paid professionals", + "56e74bf937bdd419002c3e35": "Chartered", + "56e74bf937bdd419002c3e36": "homeschooling, or in the wider community", + "56e74bf937bdd419002c3e37": "paid professionals", + "56e74d1f00c9c71400d76f6e": "school functions", + "56e74d1f00c9c71400d76f6f": "extracurricular", + "56e74d1f00c9c71400d76f70": "extracurricular activities", + "56e74d1f00c9c71400d76f71": "teachers", + "56e74e4800c9c71400d76f76": "teacher's colleges", + "56e74e4800c9c71400d76f77": "to serve and protect the public interest", + "56e74e4800c9c71400d76f78": "public interest", + "56e74e4800c9c71400d76f79": "public interest", + "56e74e4800c9c71400d76f7a": "standards of practice", + "56e74faf00c9c71400d76f94": "complaints involving members", + "56e74faf00c9c71400d76f95": "complaints involving members", + "56e74faf00c9c71400d76f96": "the college", + "56e74faf00c9c71400d76f97": "teacher's colleges", + "56e74faf00c9c71400d76f98": "teacher's colleges", + "56e7504437bdd419002c3e5b": "outdoors", + "56e7504437bdd419002c3e5c": "a tutor", + "56e7504437bdd419002c3e5d": "academy", + "56e7504437bdd419002c3e5e": "facilitate student learning", + "56e751fb00c9c71400d76fa8": "a course of study and lesson plan", + "56e751fb00c9c71400d76fa9": "pedagogy", + "56e751fb00c9c71400d76faa": "pedagogy", + "56e751fb00c9c71400d76fab": "increasing use of technology", + "56e751fb00c9c71400d76fac": "the internet", + "56e7535037bdd419002c3e6f": "a course of study, lesson plan, or a practical skill", + "56e7535037bdd419002c3e70": "the relevant authority", + "56e7535037bdd419002c3e71": "learning disabilities", + "56e7535037bdd419002c3e72": "infants to adults", + "56e7535037bdd419002c3e73": "standardized", + "56e7542f00c9c71400d76fbc": "particular skills", + "56e7542f00c9c71400d76fbd": "self-study and problem solving", + "56e7542f00c9c71400d76fbe": "pressure the lazy, inspire the bored, deflate the cocky", + "56e7542f00c9c71400d76fbf": "pressure the lazy, inspire the bored, deflate", + "56e7542f00c9c71400d76fc0": "to pressure the lazy", + "56e7550700c9c71400d76fc6": "the relationship between teachers and children", + "56e7550700c9c71400d76fc7": "the whole curriculum", + "56e7550700c9c71400d76fc8": "different subject specialists", + "56e7550700c9c71400d76fc9": "primary school", + "56e7550700c9c71400d76fca": "specialist teacher and surrogate parent", + "56e7560937bdd419002c3e8b": "alternative", + "56e7560937bdd419002c3e8c": "platoon\" system", + "56e7560937bdd419002c3e8d": "staying with the same group of peers for all classes", + "56e7560937bdd419002c3e8e": "more knowledgeable", + "56e7560937bdd419002c3e8f": "United States", + "56e756bc37bdd419002c3e95": "Co-teaching", + "56e756bc37bdd419002c3e96": "two or more", + "56e756bc37bdd419002c3e97": "learning", + "56e756bc37bdd419002c3e98": "in sync", + "56e756bc37bdd419002c3e99": "social networking", + "56e7578a37bdd419002c3ea9": "corporal punishment", + "56e7578a37bdd419002c3eaa": "a substitute parent", + "56e7578a37bdd419002c3eab": "parental discipline", + "56e7578a37bdd419002c3eac": "most", + "56e7578a37bdd419002c3ead": "While a child was in school", + "56e7586d37bdd419002c3eb3": "one of the most common", + "56e7586d37bdd419002c3eb4": "Most Western countries, and some others, have now banned it, but it remains lawful in the United States", + "56e7586d37bdd419002c3eb5": "United States", + "56e7586d37bdd419002c3eb6": "US", + "56e7586d37bdd419002c3eb7": "physical pain", + "56e7591b00c9c71400d76fec": "30", + "56e7591b00c9c71400d76fed": "in the classroom or hallway", + "56e7591b00c9c71400d76fee": "declining", + "56e7591b00c9c71400d76fef": "wooden paddle", + "56e7591b00c9c71400d76ff0": "in the classroom or hallway, but nowadays the punishment is usually given privately in the principal's office", + "56e759bb00c9c71400d77000": "caning", + "56e759bb00c9c71400d77001": "Asian, African and Caribbean", + "56e759bb00c9c71400d77002": "School corporal punishment.", + "56e75a9037bdd419002c3ec7": "detention", + "56e75a9037bdd419002c3ec8": "detention", + "56e75a9037bdd419002c3ec9": "at a given time in the school day", + "56e75a9037bdd419002c3eca": "quietly", + "56e75a9037bdd419002c3ecb": "lines or a punishment essay", + "56e75b8237bdd419002c3ed1": "assertive", + "56e75b8237bdd419002c3ed2": "immediate and fair punishment", + "56e75b8237bdd419002c3ed3": "clear", + "56e75b8237bdd419002c3ed4": "clear boundaries define what is appropriate and inappropriate behavior", + "56e75b8237bdd419002c3ed5": "respect", + "56e75d5037bdd419002c3ef5": "teachers and parents", + "56e75d5037bdd419002c3ef6": "East Asia", + "56e75d5037bdd419002c3ef7": "weakness in school discipline", + "56e75d5037bdd419002c3ef8": "assertive and confrontational", + "56e75e4500c9c71400d7702c": "Japan", + "56e75e4500c9c71400d7702d": "Japan", + "56e75e4500c9c71400d7702e": "Japan", + "56e75e4500c9c71400d7702f": "Japan", + "56e75f5500c9c71400d7703a": "40 to 50 students", + "56e75f5500c9c71400d7703b": "instruction, leaving little opportunity for concentration and focus on what is being taught", + "56e75f5500c9c71400d7703c": "motivated students", + "56e75f5500c9c71400d7703d": "motivated students, ignoring attention-seeking and disruptive students", + "56e75f5500c9c71400d7703e": "motivated students", + "56e7611500c9c71400d77054": "dictatorial", + "56e7611500c9c71400d77055": "dictatorial authority for governments and schools", + "56e7611500c9c71400d77056": "persuasion and negotiation", + "56e7611500c9c71400d77057": "easier and more efficient", + "56e7611500c9c71400d77058": "rules and regulations", + "56e761d037bdd419002c3f13": "enthusiasm", + "56e761d037bdd419002c3f14": "passion", + "56e761d037bdd419002c3f15": "attempt to find new invigoration for the course materials on a daily basis", + "56e761d037bdd419002c3f17": "higher", + "56e762fe00c9c71400d77072": "teacher enthusiasm", + "56e762fe00c9c71400d77073": "read lecture material", + "56e762fe00c9c71400d77074": "nonverbal expressions of enthusiasm", + "56e762fe00c9c71400d77075": "Controlled, experimental", + "56e762fe00c9c71400d77076": "higher", + "56e763e800c9c71400d77086": "self-determined", + "56e763e800c9c71400d77087": "enthusiasm", + "56e763e800c9c71400d77088": "emotional contagion", + "56e763e800c9c71400d77089": "Teacher enthusiasm", + "56e764e200c9c71400d7708e": "student-teacher relationships", + "56e764e200c9c71400d7708f": "beneficial", + "56e764e200c9c71400d77090": "the goals he receives from his superior", + "56e764e200c9c71400d77091": "aligning his personal goals with his academic goals", + "56e764e200c9c71400d77092": "student motivation and attitudes towards school", + "56e765ba00c9c71400d770a2": "teachers who are friendly and supportive", + "56e765ba00c9c71400d770a4": "friendly and supportive", + "56e765ba00c9c71400d770a5": "interacting and working directly with students", + "56e765ba00c9c71400d770a6": "Effective", + "56e7667e37bdd419002c3f49": "enthusiasm about the subject matter", + "56e7667e37bdd419002c3f4a": "enthusiastic", + "56e7667e37bdd419002c3f4b": "excitement in the student", + "56e7667e37bdd419002c3f4c": "very influential", + "56e7667e37bdd419002c3f4d": "being around their students", + "56e7673a37bdd419002c3f53": "sexual misconduct", + "56e7673a37bdd419002c3f54": "9.6%", + "56e7673a37bdd419002c3f55": "United States", + "56e7673a37bdd419002c3f56": "sometime during their educational career", + "56e7673a37bdd419002c3f57": "American Association of University Women", + "56e7683d00c9c71400d770ca": "A study in England", + "56e7683d00c9c71400d770cb": "a group that included priests, religious leaders, and case workers as well as teachers", + "56e7683d00c9c71400d770cd": "2,869", + "56e7683d00c9c71400d770ce": "AAUW study", + "56e768ce37bdd419002c3f67": "In the United States", + "56e768ce37bdd419002c3f69": "increased scrutiny on teacher misconduct", + "56e769dc00c9c71400d770e8": "Fears of being labelled a pedophile or hebephile", + "56e769dc00c9c71400d770e9": "Chris Keates", + "56e769dc00c9c71400d770ea": "child protection and parental rights groups", + "56e769dc00c9c71400d770eb": "a shortage", + "56e769dc00c9c71400d770ec": "sex offenders register", + "56e76abf37bdd419002c3f75": "occupational stress", + "56e76abf37bdd419002c3f76": "long hours", + "56e76abf37bdd419002c3f77": "occupational burnout", + "56e76abf37bdd419002c3f78": "Stress", + "56e76abf37bdd419002c3f79": "occupational stress", + "56e76b8337bdd419002c3f7f": "42%", + "56e76b8337bdd419002c3f80": "UK", + "56e76b8337bdd419002c3f81": "twice", + "56e76b8337bdd419002c3f82": "2012", + "56e76b8337bdd419002c3f83": "average workers", + "56e76c6a00c9c71400d7710e": "several", + "56e76c6a00c9c71400d7710f": "Organizational interventions", + "56e76c6a00c9c71400d77110": "Individual-level interventions", + "56e76c6a00c9c71400d77111": "occupational stress", + "56e76c6a00c9c71400d77112": "Organizational", + "56e76d6537bdd419002c3f93": "a university or college", + "56e76d6537bdd419002c3f94": "certification by a recognized body", + "56e76d6537bdd419002c3f95": "elementary school education certificate", + "56e76d6537bdd419002c3f96": "background check and psychiatric evaluation", + "56e76d6537bdd419002c3f97": "US", + "56e76de800c9c71400d77122": "individual states and territories", + "56e76de800c9c71400d77123": "three", + "56e76de800c9c71400d77124": "secondary schools/high schools", + "56e76de800c9c71400d77125": "universities and/or TAFE colleges", + "56e76de800c9c71400d77126": "primary education", + "56e76ea737bdd419002c3f9d": "post-secondary degree Bachelor's Degree", + "56e76ea737bdd419002c3f9e": "a second Bachelor's Degree", + "56e76ea737bdd419002c3fa1": "businesses and sponsors", + "56e76f7000c9c71400d7712c": "civil servants", + "56e76f7000c9c71400d7712d": "special university classes", + "56e76f7000c9c71400d7712e": "Grundschule", + "56e76f7000c9c71400d7712f": "civil servants' salary index scale", + "56e76f7000c9c71400d77130": "Hauptschule", + "56e7714a00c9c71400d77137": "Extra pay", + "56e7714a00c9c71400d77138": "\u20ac27,814 p.a.", + "56e7714a00c9c71400d77139": "\u20ac53,423", + "56e7714a00c9c71400d7713a": "over \u20ac90,000", + "56e7721500c9c71400d77140": "Teaching Council", + "56e7721500c9c71400d77141": "Section 30", + "56e7721500c9c71400d77142": "2001", + "56e7721500c9c71400d77143": "Oireachtas funds", + "56e772bf37bdd419002c3fbb": "2006", + "56e772bf37bdd419002c3fbc": "non-teaching posts", + "56e772bf37bdd419002c3fbe": "on a phased basis", + "56e772bf37bdd419002c3fbf": "those who refuse vetting", + "56e773fa00c9c71400d7714a": "\u00a341,004", + "56e773fa00c9c71400d7714b": "experience and extra responsibilities", + "56e773fa00c9c71400d7714c": "\u00a320,980", + "56e773fa00c9c71400d7714d": "bachelor's degree", + "56e773fa00c9c71400d7714e": "September 2007", + "56e7752337bdd419002c3fd5": "alternative licensing programs", + "56e7752337bdd419002c3fd6": "hard-to-fill", + "56e7752337bdd419002c3fd7": "opportunities will vary by geographic area and subject taught", + "56e7752337bdd419002c3fd8": "Excellent job opportunities", + "56e7752337bdd419002c3fd9": "secondary school teachers", + "56e775ec00c9c71400d7715c": "General Teaching Council for Scotland", + "56e775ec00c9c71400d7715d": "Teaching", + "56e775ec00c9c71400d7715e": "seven", + "56e775ec00c9c71400d7715f": "\"Provisional Registration", + "56e775ec00c9c71400d77160": "a year", + "56e7770037bdd419002c3fdf": "April 2008", + "56e7770037bdd419002c3fe0": "\u00a320,427", + "56e7770037bdd419002c3fe1": "\u00a332,583", + "56e7770037bdd419002c3fe2": "teaching, but could then go on to earn up to \u00a339,942 as they complete the modules", + "56e7770037bdd419002c3fe3": "trade unions", + "56e777e500c9c71400d77176": "Wales", + "56e777e500c9c71400d77177": "Welsh", + "56e777e500c9c71400d77178": "until the age of 16", + "56e777e500c9c71400d77179": "22 per cent", + "56e777e500c9c71400d7717a": "all age groups", + "56e7788200c9c71400d77180": "trade unions", + "56e7788200c9c71400d77181": "falling", + "56e7788200c9c71400d77182": "between 2005 and 2010", + "56e7788200c9c71400d77183": "trade unions", + "56e7788200c9c71400d77184": "attacks on teachers in Welsh schools which reached an all-time high", + "56e7796637bdd419002c3ffd": "each state", + "56e7796637bdd419002c3ffe": "ten years", + "56e7796637bdd419002c3fff": "a bachelor's degree", + "56e7796637bdd419002c4000": "Many charter schools", + "56e7796637bdd419002c4001": "No Child Left Behind", + "56e77a8700c9c71400d7718a": "relatively low salaries", + "56e77a8700c9c71400d7718b": "average teacher salaries", + "56e77a8700c9c71400d7718c": "state, relative cost of living, and grade taught", + "56e77a8700c9c71400d7718d": "elementary school teachers", + "56e77a8700c9c71400d7718e": "TeachersPayTeachers.com", + "56e77b8c00c9c71400d77194": "many", + "56e77b8c00c9c71400d77196": "Protestant", + "56e77b8c00c9c71400d77197": "not always a bishop", + "56e77b8c00c9c71400d77198": "Roman) Catholic, (Eastern) Orthodox Catholic, and Protestant/Non-Denominational", + "56e77c6737bdd419002c401d": "LDS Church", + "56e77c6737bdd419002c401e": "a trusted friend", + "56e77c6737bdd419002c401f": "spiritual", + "56e77c6737bdd419002c4020": "the husband and father", + "56e77c6737bdd419002c4021": "the father of the house", + "56e77cee00c9c71400d771a8": "guru", + "56e77cee00c9c71400d771a9": "extremely high", + "56e77cee00c9c71400d771aa": "the lives of their disciples", + "56e77cee00c9c71400d771ab": "West", + "56e77da237bdd419002c403b": "a Lama", + "56e77da237bdd419002c403c": "reborn", + "56e77da237bdd419002c403d": "Tulku", + "56e77da237bdd419002c403e": "many times", + "56e77da237bdd419002c403f": "phowa and siddhi", + "56e77e4a00c9c71400d771b0": "ulemas", + "56e77e4a00c9c71400d771b1": "ulemas", + "56e77e4a00c9c71400d771b2": "Sufism", + "56e77e4a00c9c71400d771b3": "actions-oriented", + "56e77e4a00c9c71400d771b4": "Qutb", + "56f7c651aef2371900625bf5": "German", + "56f7c651aef2371900625bf6": "18 February 1546", + "56f7c651aef2371900625bf7": "the Late Medieval Catholic Church", + "56f7c651aef2371900625bf8": "freedom from God's punishment for sin", + "56f7c651aef2371900625bf9": "excommunication", + "56f7c8aba6d7ea1400e1727a": "as a free gift of God's grace through faith in Jesus Christ as redeemer from sin", + "56f7c8aba6d7ea1400e1727b": "faith in Jesus Christ", + "56f7c8aba6d7ea1400e1727c": "the Pope", + "56f7c8aba6d7ea1400e1727d": "the Bible", + "56f7c8aba6d7ea1400e1727e": "a holy priesthood", + "56f7cb10a6d7ea1400e17284": "the Bible", + "56f7cb10a6d7ea1400e17285": "development of a standard version", + "56f7cb10a6d7ea1400e17286": "the Tyndale Bible", + "56f7cb10a6d7ea1400e17287": "singing in churches", + "56f7cb10a6d7ea1400e17288": "Protestant clergy to marry", + "56f7cdc2a6d7ea1400e1728e": "10 November 1483", + "56f7cdc2a6d7ea1400e1728f": "Eisleben, Saxony", + "56f7cdc2a6d7ea1400e17290": "Holy Roman Empire", + "56f7cdc2a6d7ea1400e17291": "Catholic", + "56f7cdc2a6d7ea1400e17292": "lawyer", + "56f7e9caaef2371900625c56": "University of Erfurt", + "56f7e9caaef2371900625c57": "a beerhouse and whorehouse", + "56f7e9caaef2371900625c58": "four", + "56f7e9caaef2371900625c59": "a day of rote learning and often wearying spiritual exercises.\"", + "56f7e9caaef2371900625c5a": "1505", + "56f7eba8a6d7ea1400e172cd": "law school", + "56f7eba8a6d7ea1400e172ce": "uncertainty", + "56f7eba8a6d7ea1400e172cf": "theology and philosophy", + "56f7eba8a6d7ea1400e172d0": "by experience", + "56f7eba8a6d7ea1400e172d1": "men and institutions", + "56f7eddca6d7ea1400e172d7": "death and divine judgment", + "56f7eddca6d7ea1400e172d8": "2 July 1505", + "56f7eddca6d7ea1400e172d9": "Erfurt", + "56f7eddca6d7ea1400e172da": "deaths of two friends", + "56f7eddca6d7ea1400e172db": "Luther's education", + "56f7ef96aef2371900625c74": "Augustinian order", + "56f7ef96aef2371900625c75": "deep spiritual despair", + "56f7ef96aef2371900625c76": "the jailer and hangman of my poor soul", + "56f7ef96aef2371900625c77": "Johann von Staupitz", + "56f7ef96aef2371900625c78": "a change of heart", + "56f7f15aa6d7ea1400e172eb": "1507", + "56f7f15aa6d7ea1400e172ec": "von Staupitz", + "56f7f15aa6d7ea1400e172ed": "1508", + "56f7f15aa6d7ea1400e172ee": "9 March 1508", + "56f7f15aa6d7ea1400e172ef": "theology", + "56f7f2e0aef2371900625cb0": "19 October 1512", + "56f7f2e0aef2371900625cb1": "21 October 1512", + "56f7f2e0aef2371900625cb2": "Doctor in Bible", + "56f7f2e0aef2371900625cb3": "University of Wittenberg", + "56f7f2e0aef2371900625cb4": "Doctor of Theology", + "56f7fde8a6d7ea1400e17367": "1516", + "56f7fde8a6d7ea1400e17368": "to sell indulgences to raise money to rebuild St. Peter's Basilica in Rome", + "56f7fde8a6d7ea1400e17369": "Roman Catholic theology", + "56f7fde8a6d7ea1400e1736a": "active in charity and good works", + "56f7fde8a6d7ea1400e1736b": "active in charity and good works", + "56f7ffadaef2371900625d5e": "31 October 1517", + "56f7ffadaef2371900625d5f": "Albert of Mainz", + "56f7ffadaef2371900625d60": "Ninety-Five Theses", + "56f7ffadaef2371900625d61": "Hans Hillerbrand", + "56f7ffadaef2371900625d62": "Thesis 86", + "56f80143aef2371900625d68": "Johann Tetzel", + "56f80143aef2371900625d69": "As soon as the coin in the coffer rings", + "56f80143aef2371900625d6a": "Luther", + "56f80143aef2371900625d6b": "Johann Tetzel", + "56f802c6a6d7ea1400e17377": "God's alone to grant, those who claimed that indulgences absolved buyers from all punishments and granted them salvation were in error. Christians", + "56f802c6a6d7ea1400e17378": "salvation", + "56f802c6a6d7ea1400e17379": "all punishments", + "56f802c6a6d7ea1400e1737a": "indulgences absolved buyers from all punishments and granted them salvation were in error", + "56f802c6a6d7ea1400e1737b": "Christ", + "56f8046faef2371900625d71": "Tetzel", + "56f8046faef2371900625d72": "a reflection of his capacity to exaggerate", + "56f8046faef2371900625d73": "indulgences for the dead", + "56f8046faef2371900625d74": "Catholic dogma of the time", + "56f80604a6d7ea1400e17387": "the posting on the door", + "56f80604a6d7ea1400e17388": "the posting on the door", + "56f80604a6d7ea1400e17389": "Philipp Melanchthon", + "56f80604a6d7ea1400e1738a": "Wittenberg", + "56f80604a6d7ea1400e1738b": "little foundation in truth", + "56f8074faef2371900625d79": "January 1518", + "56f8074faef2371900625d7a": "printing press", + "56f8074faef2371900625d7b": "friends", + "56f8074faef2371900625d7c": "two weeks", + "56f8074faef2371900625d7d": "two months", + "56f8094aa6d7ea1400e17391": "1519", + "56f8094aa6d7ea1400e17392": "Students", + "56f8094aa6d7ea1400e17393": "Psalms", + "56f8094aa6d7ea1400e17394": "1520", + "56f8094aa6d7ea1400e17395": "the Freedom of a Christian", + "56f80ad1a6d7ea1400e1739b": "lectured on the Psalms", + "56f80ad1a6d7ea1400e1739c": "penance and righteousness", + "56f80ad1a6d7ea1400e1739d": "penance and righteousness", + "56f80ad1a6d7ea1400e1739e": "several of the central truths of Christianity", + "56f80ad1a6d7ea1400e1739f": "doctrine of justification", + "56f80ccfaef2371900625d83": "God", + "56f80ccfaef2371900625d84": "1525", + "56f80ccfaef2371900625d85": "a gift from God", + "56f80ccfaef2371900625d86": "Smalcald Articles", + "56f80ccfaef2371900625d87": "faith", + "56f80e1daef2371900625d8d": "Christ and His salvation", + "56f80e1daef2371900625d8e": "Christ and His salvation", + "56f80e1daef2371900625d8f": "His railing against the sale of indulgences", + "56f80e1daef2371900625d90": "two", + "56f80fdfaef2371900625d95": "Archbishop Albrecht of Mainz and Magdeburg", + "56f80fdfaef2371900625d96": "Rome", + "56f80fdfaef2371900625d97": "a papal dispensation", + "56f80fdfaef2371900625d98": "one half", + "56f80fdfaef2371900625d99": "December 1517", + "56f811bdaef2371900625d9f": "Pope Leo X", + "56f811bdaef2371900625da0": "a series of papal theologians and envoys", + "56f811bdaef2371900625da1": "October 1518", + "56f811bdaef2371900625da2": "he did not consider the papacy part of the biblical Church because historistical interpretation of Bible prophecy concluded that the papacy was the Antichrist", + "56f811bdaef2371900625da3": "a series of papal theologians and envoys", + "56f81393aef2371900625da9": "January 1519", + "56f81393aef2371900625daa": "remain silent", + "56f81393aef2371900625dab": "Johann Eck", + "56f81393aef2371900625dac": "Matthew 16:18", + "56f81393aef2371900625dad": "Jan Hus", + "56f81537aef2371900625db3": "15 June 1520", + "56f81537aef2371900625db4": "recanted 41 sentences drawn from his writings", + "56f81537aef2371900625db5": "60 days", + "56f81537aef2371900625db6": "Karl von Miltitz", + "56f81537aef2371900625db7": "3 January 1521", + "56f8225ea6d7ea1400e173f1": "secular authorities", + "56f8225ea6d7ea1400e173f2": "18 April 1521", + "56f8225ea6d7ea1400e173f3": "the estates of the Holy Roman Empire", + "56f8225ea6d7ea1400e173f4": "Emperor Charles V", + "56f8225ea6d7ea1400e173f5": "Prince Frederick III", + "56f82454a6d7ea1400e173fb": "Johann Eck", + "56f82454a6d7ea1400e173fc": "Archbishop of Trier", + "56f82454a6d7ea1400e173fd": "whether he stood by their contents", + "56f82454a6d7ea1400e173fe": "the next day", + "56f82454a6d7ea1400e173ff": "He prayed", + "56f82549a6d7ea1400e17415": "raised his arm", + "56f82549a6d7ea1400e17416": "traditional salute of a knight winning a bout", + "56f82549a6d7ea1400e17417": "Michael Mullett", + "56f82549a6d7ea1400e17418": "world classic of epoch-making oratory", + "56f826a7a6d7ea1400e17427": "recant his writings", + "56f826a7a6d7ea1400e17428": "Luther", + "56f826a7a6d7ea1400e17429": "consider the evidence for these words to be unreliable", + "56f826a7a6d7ea1400e1742a": "dramatic", + "56f827caa6d7ea1400e17439": "private conferences were held to determine Luther's fate. The Emperor presented the final draft of the Edict of Worms", + "56f827caa6d7ea1400e1743a": "25 May 1521", + "56f827caa6d7ea1400e1743b": "The Emperor", + "56f827caa6d7ea1400e1743c": "requiring his arrest", + "56f827caa6d7ea1400e1743d": "kill", + "56f82989aef2371900625e6b": "disappearance", + "56f82989aef2371900625e6c": "Wartburg Castle at Eisenach", + "56f82989aef2371900625e6d": "my Patmos", + "56f82989aef2371900625e6e": "New Testament", + "56f82989aef2371900625e6f": "in his episcopates", + "56f82b25a6d7ea1400e17457": "a sin", + "56f82b25a6d7ea1400e17458": "cannot be earned", + "56f82b25a6d7ea1400e17459": "1 August 1521", + "56f82b25a6d7ea1400e1745a": "trust in Christ", + "56f82b25a6d7ea1400e1745b": "justice resides", + "56f84485aef2371900625f71": "summer of 1521", + "56f84485aef2371900625f72": "idolatry", + "56f84485aef2371900625f73": "a gift", + "56f84485aef2371900625f74": "private confession and absolution", + "56f84485aef2371900625f75": "without sin", + "56f845dba6d7ea1400e17519": "prophetic faith", + "56f845dba6d7ea1400e1751a": "1521", + "56f845dba6d7ea1400e1751b": "Daniel 8:9\u201312, 23\u201325", + "56f845dba6d7ea1400e1751c": "the Little Horn", + "56f845dba6d7ea1400e1751d": "antichrist of 2 Thessalonians 2", + "56f84760aef2371900625f81": "Gabriel Zwilling", + "56f84760aef2371900625f82": "June 1521", + "56f84760aef2371900625f83": "disturbances", + "56f84760aef2371900625f84": "Augustinian friars", + "56f84760aef2371900625f85": "the town council", + "56f848e0a6d7ea1400e1752f": "6 March 1522", + "56f848e0a6d7ea1400e17530": "trust God's word", + "56f848e0a6d7ea1400e17531": "preached eight sermons", + "56f848e0a6d7ea1400e17532": "Invocavit Sermons", + "56f848e0a6d7ea1400e17533": "trust God's word rather than violence", + "56f84a60aef2371900625f9d": "immediate", + "56f84a60aef2371900625f9e": "Jerome Schurf", + "56f84a60aef2371900625f9f": "sixth", + "56f84a60aef2371900625fa0": "misguided people into the way of the truth", + "56f84a60aef2371900625fa1": "misguided people", + "56f84b68aef2371900625fa7": "public order", + "56f84b68aef2371900625fa8": "conservative", + "56f84b68aef2371900625fa9": "Zwickau prophets", + "56f84b68aef2371900625faa": "social unrest and violence", + "56f84b68aef2371900625fab": "reformers", + "56f84d33aef2371900625fb1": "Zwickau prophet", + "56f84d33aef2371900625fb2": "German Peasants' War", + "56f84d33aef2371900625fb3": "1524\u201325", + "56f84d33aef2371900625fb4": "support an attack on the upper classes in general", + "56f84d33aef2371900625fb5": "the upper classes", + "56f84e63aef2371900625fc1": "temporal authorities", + "56f84e63aef2371900625fc2": "Thuringia", + "56f84e63aef2371900625fc3": "mad dogs", + "56f84e63aef2371900625fc4": "the devil's work", + "56f84e63aef2371900625fc5": "the nobles", + "56f8507fa6d7ea1400e1754b": "three", + "56f8507fa6d7ea1400e1754c": "Render unto Caesar the things that are Caesar's\"", + "56f8507fa6d7ea1400e1754d": "God", + "56f8507fa6d7ea1400e1754e": "Divine Right of Kings", + "56f8507fa6d7ea1400e1754f": "death in body and soul", + "56f851b1a6d7ea1400e1755d": "laid down their weapons", + "56f851b1a6d7ea1400e1755e": "Swabian League", + "56f851b1a6d7ea1400e1755f": "15 May 1525", + "56f851b1a6d7ea1400e17560": "M\u00fcntzer's execution", + "56f851b1a6d7ea1400e17561": "secular powers", + "56f852fba6d7ea1400e1756d": "Katharina von Bora", + "56f852fba6d7ea1400e1756e": "herring barrels", + "56f852fba6d7ea1400e1756f": "26", + "56f852fba6d7ea1400e17570": "41", + "56f852fba6d7ea1400e17571": "April 1523", + "56f8541da6d7ea1400e17577": "13 June 1525", + "56f8541da6d7ea1400e17578": "evening", + "56f8541da6d7ea1400e17579": "wedding banquet", + "56f8541da6d7ea1400e1757a": "27 June", + "56f8541da6d7ea1400e1757b": "Bugenhagen", + "56f855caaef2371900625ff3": "clerical marriage", + "56f855caaef2371900625ff4": "clerical", + "56f855caaef2371900625ff5": "on Biblical grounds", + "56f855caaef2371900625ff6": "celibacy", + "56f855caaef2371900625ff7": "reckless", + "56f8575aaef2371900625ffd": "1525\u201332", + "56f8575aaef2371900625ffe": "a wedding present from the new elector John the Steadfast", + "56f8575aaef2371900625fff": "six", + "56f8575aaef2371900626000": "the riches of Croesus", + "56f8575aaef2371900626001": "farming the land", + "56f8599aa6d7ea1400e175af": "His Biblical ideal of congregations' choosing their own ministers", + "56f8599aa6d7ea1400e175b0": "a supervisory church body, laid down a new form of worship service", + "56f8599aa6d7ea1400e175b1": "a supervisory church body", + "56f8599aa6d7ea1400e175b2": "two catechisms", + "56f8599aa6d7ea1400e175b3": "revolutionary", + "56f85bb8aef237190062600f": "extreme change", + "56f85bb8aef2371900626010": "Electorate of Saxony", + "56f85bb8aef2371900626011": "adviser", + "56f85bb8aef2371900626012": "John the Steadfast", + "56f85bb8aef2371900626013": "questionable", + "56f85cf0aef2371900626019": "early 1526", + "56f85cf0aef237190062601a": "his 1523 adaptation of the Latin Mass", + "56f85cf0aef237190062601b": "the \"simple people\", a \"public stimulation for people to believe and become Christians", + "56f85cf0aef237190062601c": "Mass vestments, altar, and candles", + "56f85cf0aef237190062601d": "freedom", + "56f85e71a6d7ea1400e175c3": "1527", + "56f85e71a6d7ea1400e175c4": "Electorate of Saxony", + "56f85e71a6d7ea1400e175c5": "Christian", + "56f85e71a6d7ea1400e175c6": "Christian doctrine", + "56f85e71a6d7ea1400e175c7": "teaching", + "56f86680a6d7ea1400e175cd": "catechism", + "56f86680a6d7ea1400e175ce": "1529", + "56f86680a6d7ea1400e175cf": "pastors and teachers", + "56f86680a6d7ea1400e175d0": "pastors and teachers", + "56f86680a6d7ea1400e175d1": "questions and answers", + "56f867e3a6d7ea1400e175d7": "The catechism", + "56f867e3a6d7ea1400e175d8": "Saturnian hunger", + "56f867e3a6d7ea1400e175d9": "the Catechism", + "56f867e3a6d7ea1400e175da": "The Small Catechism", + "56f867e3a6d7ea1400e175db": "the Bible", + "56f86966aef2371900626053": "Small Catechism", + "56f86966aef2371900626054": "Catechism", + "56f86966aef2371900626055": "German vernacular", + "56f86966aef2371900626056": "not as a doctrine to be learned, but as persons to be known", + "56f86966aef2371900626057": "Father", + "56f86b44a6d7ea1400e175f5": "1522", + "56f86b44a6d7ea1400e175f6": "1534", + "56f86b44a6d7ea1400e175f7": "translation of the Old Testament", + "56f86b44a6d7ea1400e175f8": "alone\" after \"faith", + "56f86b44a6d7ea1400e175f9": "Faith alone", + "56f86d30a6d7ea1400e17605": "Saxon chancellery", + "56f86d30a6d7ea1400e17606": "northern and southern Germans", + "56f86d30a6d7ea1400e17607": "everyday Germans", + "56f86d30a6d7ea1400e17608": "for we are removing impediments and difficulties", + "56f86d30a6d7ea1400e17609": "impediments and difficulties", + "56f86e91aef2371900626067": "German-language publications", + "56f86e91aef2371900626068": "Bible translation", + "56f86e91aef2371900626069": "evolution of the German language and literature", + "56f86e91aef237190062606a": "Lucas Cranach", + "56f86e91aef237190062606b": "William Tyndale", + "56f87000aef2371900626071": "hymn-writer", + "56f87000aef2371900626072": "high art and folk music", + "56f87000aef2371900626073": "German hymns", + "56f87000aef2371900626074": "a lute", + "56f87000aef2371900626075": "waldzither", + "56f8720eaef237190062608f": "his learning of the execution of Johann Esch and Heinrich Voes, the first individuals to be martyred by the Roman Catholic Church for Lutheran views", + "56f8720eaef2371900626090": "Lutheran views", + "56f8720eaef2371900626091": "Ein neues Lied wir heben an\"", + "56f8720eaef2371900626092": "John C. Messenger", + "56f8720eaef2371900626093": "Ein neues Lied wir heben an\" (\"A new song we raise\"", + "56f87392aef2371900626099": "1524", + "56f87392aef237190062609a": "Luther's 1529 three-part explanation of the Apostles' Creed in the Small Catechism", + "56f87392aef237190062609b": "Small Catechism", + "56f87392aef237190062609c": "German creedal", + "56f87392aef237190062609d": "perceived difficulty of its tune", + "56f87531a6d7ea1400e1766f": "1538", + "56f87531a6d7ea1400e17670": "Small Catechism", + "56f87531a6d7ea1400e17671": "specific catechism questions", + "56f87531a6d7ea1400e17672": "multiple revisions", + "56f87531a6d7ea1400e17673": "Luther's tune", + "56f87760aef23719006260cc": "1523", + "56f87760aef23719006260cd": "Psalm 130", + "56f87760aef23719006260ce": "write psalm-hymns for use in German worship", + "56f87760aef23719006260cf": "Achtliederbuch", + "56f87760aef23719006260d0": "essential Reformation doctrine", + "56f879bdaef23719006260de": "Hauptlied", + "56f879bdaef23719006260df": "Veni redemptor gentium", + "56f879bdaef23719006260e0": "main hymn", + "56f879bdaef23719006260e1": "two", + "56f879bdaef23719006260e2": "German Te Deum", + "56f87e95aef237190062610a": "baptism", + "56f87e95aef237190062610b": "Johann Walter", + "56f87e95aef237190062610c": "prayer for grace", + "56f87e95aef237190062610d": "J. S. Bach", + "56f87e95aef237190062610e": "Halle", + "56f88025aef237190062611e": "early Lutheran hymnals", + "56f88025aef237190062611f": "four of eight", + "56f88025aef2371900626120": "18 of 26", + "56f88025aef2371900626121": "24", + "56f88025aef2371900626122": "Achtliederbuch", + "56f881e3a6d7ea1400e176f3": "Johann Sebastian Bach", + "56f881e3a6d7ea1400e176f4": "chorale cantatas", + "56f881e3a6d7ea1400e176f5": "1707", + "56f881e3a6d7ea1400e176f6": "1707", + "56f881e3a6d7ea1400e176f7": "1707", + "56f8837aa6d7ea1400e176fd": "sleeps", + "56f8837aa6d7ea1400e176fe": "torments", + "56f8837aa6d7ea1400e176ff": "penitential suffering", + "56f8837aa6d7ea1400e17700": "rejected the existence of Purgatory, which involved Christian souls undergoing penitential suffering after death", + "56f8837aa6d7ea1400e17701": "in their graves and in heaven", + "56f884cba6d7ea1400e17707": "Franz Pieper", + "56f884cba6d7ea1400e17708": "Franz Pieper", + "56f884cba6d7ea1400e17709": "Franz Pieper", + "56f884cba6d7ea1400e1770a": "1755", + "56f88690a6d7ea1400e17723": "Genesis", + "56f88690a6d7ea1400e17724": "Francis Blackburne", + "56f88690a6d7ea1400e17725": "1765", + "56f88690a6d7ea1400e17726": "Gottfried Fritschel", + "56f88690a6d7ea1400e17727": "dreams", + "56f88c37aef2371900626176": "October 1529", + "56f88c37aef2371900626177": "Landgrave of Hesse", + "56f88c37aef2371900626178": "doctrinal unity in the emerging Protestant states", + "56f88c37aef2371900626179": "fourteen", + "56f88c37aef237190062617a": "the nature of the Eucharist \u2013 the sacrament of the Lord's Supper", + "56f88eafaef2371900626194": "the significance of the words spoken by Jesus", + "56f88eafaef2371900626195": "the Real Presence of the body and blood of Christ", + "56f88eafaef2371900626196": "sacramental union", + "56f88eafaef2371900626197": "only spiritually or symbolically present", + "56f88eafaef2371900626198": "confrontational", + "56f8907faef23719006261b2": "1530", + "56f8907faef23719006261b3": "Marburg Colloquy", + "56f8907faef23719006261b4": "Schmalkaldic League", + "56f8907faef23719006261b5": "The Swiss cities", + "56f8907faef23719006261b6": "George, Margrave of Brandenburg-Ansbach", + "56f895339e9bad19000a0177": "antithetical", + "56f895339e9bad19000a0178": "reason", + "56f895339e9bad19000a0179": "no way", + "56f895339e9bad19000a017a": "reason", + "56f895339e9bad19000a017b": "their different epistemological spheres", + "56f897059b226e1400dd0c5d": "venom", + "56f897059b226e1400dd0c5e": "large-scale Jewish conversion to Christianity", + "56f897059b226e1400dd0c5f": "the Jews", + "56f897059b226e1400dd0c60": "Anabaptists", + "56f897059b226e1400dd0c61": "1543", + "56f8989f9e9bad19000a01a5": "a scourge sent to punish Christians by God", + "56f8989f9e9bad19000a01a6": "to punish Christians by God", + "56f8989f9e9bad19000a01a7": "punish Christians", + "56f8989f9e9bad19000a01a8": "the papacy", + "56f8989f9e9bad19000a01a9": "non-religious war", + "56f89a959b226e1400dd0c9d": "a Latin translation of the Qur'an", + "56f89a959b226e1400dd0c9e": "critical pamphlets on Islam", + "56f89a959b226e1400dd0c9f": "critical pamphlets on Islam", + "56f89a959b226e1400dd0ca0": "a tool of the devil", + "56f89a959b226e1400dd0ca1": "exposed to scrutiny", + "56f8a2969e9bad19000a022b": "God's wrath to Christians", + "56f8a2969e9bad19000a022c": "Agricola", + "56f8a2969e9bad19000a022d": "the law is no longer to be taught to Christians", + "56f8a2969e9bad19000a022e": "with six series of theses", + "56f8a2969e9bad19000a022f": "On the Councils and the Church", + "56f8a4e99e9bad19000a0251": "second use of the law", + "56f8a4e99e9bad19000a0252": "to work sorrow over sin in man's heart", + "56f8a4e99e9bad19000a0253": "everything that is used to work sorrow over sin", + "56f8a4e99e9bad19000a0254": "eliminate the accusing law", + "56f8a4e99e9bad19000a0255": "essentially holy people", + "56f8a6969e9bad19000a025b": "how the Christian ought to live", + "56f8a6969e9bad19000a025c": "the Ten Commandments", + "56f8a6969e9bad19000a025d": "third", + "56f8a6969e9bad19000a025e": "an illustration of the Ten Commandments", + "56f8a6969e9bad19000a025f": "vocations", + "56f8aa749b226e1400dd0da7": "sacrament of baptism", + "56f8aa749b226e1400dd0da8": "The Ten Commandments", + "56f8aa749b226e1400dd0da9": "sacrament of baptism", + "56f8ac579e9bad19000a02b9": "marry one of his wife's ladies-in-waiting", + "56f8ac579e9bad19000a02ba": "the bigamy", + "56f8ac579e9bad19000a02bb": "one of his wife's ladies-in-waiting", + "56f8ac579e9bad19000a02bc": "the landgrave himself", + "56f8ac579e9bad19000a02bd": "lasting damage", + "56f8ae099e9bad19000a02eb": "expelled", + "56f8ae099e9bad19000a02ec": "Jews", + "56f8ae099e9bad19000a02ed": "murder of Christ", + "56f8ae099e9bad19000a02ee": "the divinity of Jesus", + "56f8ae099e9bad19000a02ef": "convert them to Christianity", + "56f8afbc9b226e1400dd0e05": "Von den Juden und Ihren L\u00fcgen", + "56f8afbc9b226e1400dd0e06": "1543", + "56f8afbc9b226e1400dd0e07": "three years", + "56f8afbc9b226e1400dd0e08": "the devil's people", + "56f8afbc9b226e1400dd0e09": "vile", + "56f8b2499b226e1400dd0e3b": "Jews", + "56f8b2499b226e1400dd0e3c": "Martin Luther", + "56f8b2499b226e1400dd0e3d": "\"that priest whose name was Martin Luther\u2014may his body and soul be bound up in hell!\u2014", + "56f8b2499b226e1400dd0e3e": "Luther's anti-Jewish works", + "56f8b2499b226e1400dd0e3f": "1580s", + "56f8b4d79b226e1400dd0e75": "Luther", + "56f8b4d79b226e1400dd0e76": "anti-Jewish rhetoric", + "56f8b4d79b226e1400dd0e77": "attacks on Jews", + "56f8b4d79b226e1400dd0e78": "Luther", + "56f8b4d79b226e1400dd0e79": "the most radically anti-Semitic tract ever published", + "56f8b7189e9bad19000a0389": "17 December 1941", + "56f8b7189e9bad19000a038a": "Luther", + "56f8b7189e9bad19000a038b": "Diarmaid MacCulloch", + "56f8b7189e9bad19000a038c": "Protestant regional church confederations", + "56f8b7189e9bad19000a038d": "leading Protestant churchman", + "56f8b9839e9bad19000a03bf": "opportunistic", + "56f8b9839e9bad19000a03c0": "Biographer", + "56f8b9839e9bad19000a03c1": "modern hatred of the Jews", + "56f8b9839e9bad19000a03c2": "18th and 19th centuries", + "56f8b9839e9bad19000a03c3": "entirely religious and in no respect racial", + "56f8bbb09e9bad19000a03db": "a new", + "56f8bbb09e9bad19000a03dc": "Ronald Berger", + "56f8bbb09e9bad19000a03dd": "hysterical and demonizing mentality", + "56f8bbb09e9bad19000a03de": "Christopher J. Probst in his book Demonizing the Jews: Luther and the Protestant Church", + "56f8bbb09e9bad19000a03df": "hostile publications towards the Jews and their Jewish religion", + "56f8bd509b226e1400dd0eed": "a declining state of mind", + "56f8bd509b226e1400dd0eee": "health", + "56f8bd509b226e1400dd0eef": "vulgarity and violence", + "56f8bd509b226e1400dd0ef0": "the Jews and in diatribes against \"Turks\" (Muslims) and Catholics", + "56f8bd509b226e1400dd0ef1": "Luther's Last Battles: Politics and Polemics", + "56f8c0cd9b226e1400dd0f35": "Since the 1980s", + "56f8c0cd9b226e1400dd0f36": "the least prejudiced", + "56f8c0cd9b226e1400dd0f37": "Professor Richard (Dick) Geary", + "56f8c0cd9b226e1400dd0f38": "1928-1933", + "56f8c2ee9b226e1400dd0f45": "deteriorated further", + "56f8c2ee9b226e1400dd0f46": "Philip of Hesse incident", + "56f8c2ee9b226e1400dd0f47": "kidney and bladder stones, and arthritis", + "56f8c2ee9b226e1400dd0f48": "M\u00e9ni\u00e8re's disease, vertigo, fainting, tinnitus, and a cataract in one eye", + "56f8c2ee9b226e1400dd0f49": "angina", + "56f8c43d9b226e1400dd0f61": "poor physical health", + "56f8c43d9b226e1400dd0f62": "physical", + "56f8c43d9b226e1400dd0f63": "short-tempered and even harsher", + "56f8c43d9b226e1400dd0f64": "Katharina", + "56f8c43d9b226e1400dd0f65": "three", + "56f8c5909b226e1400dd0f7d": "Eisleben", + "56f8c5909b226e1400dd0f7e": "15 February 1546", + "56f8c5909b226e1400dd0f7f": "obdurate Jews", + "56f8c5909b226e1400dd0f80": "three days before his death", + "56f8c5909b226e1400dd0f81": "Christian love", + "56f8c7029e9bad19000a04a0": "Mansfeld", + "56f8c7029e9bad19000a04a1": "negotiations for a settlement", + "56f8c7029e9bad19000a04a2": "late 1545", + "56f8c7029e9bad19000a04a3": "early 1546", + "56f8c7029e9bad19000a04a4": "his siblings' families", + "56f8c8469e9bad19000a04c6": "17 February 1546", + "56f8c8469e9bad19000a04c7": "chest pains", + "56f8c8469e9bad19000a04c8": "the common prayer of the dying", + "56f8c8469e9bad19000a04c9": "the common prayer of the dying", + "56f8c8469e9bad19000a04ca": "1 a.m", + "56f8c9719e9bad19000a04e0": "An apoplectic stroke", + "56f8c9719e9bad19000a04e1": "2:45 a.m. on 18 February 1546", + "56f8c9719e9bad19000a04e2": "18 February 1546", + "56f8c9719e9bad19000a04e3": "Castle Church in Wittenberg", + "56f8c9719e9bad19000a04e4": "Johannes Bugenhagen and Philipp Melanchthon", + "56f8ca289b226e1400dd1007": "his last statement", + "56f8ca289b226e1400dd1008": "Latin", + "56f8ca289b226e1400dd1009": "\"We are beggars,\"", + "56f8cc399e9bad19000a0514": "printed", + "56f8cc399e9bad19000a0515": "a stout man with a \"double chin, strong mouth, piercing deep-set eyes, fleshy face, and squat neck.\"", + "56f8cc399e9bad19000a0516": "a stout man with a \"double chin, strong mouth, piercing deep-set eyes, fleshy face, and squat neck.\"", + "56f8cc399e9bad19000a0517": "frail Catholic saints", + "56f8cc399e9bad19000a0518": "1530s and 1540s", + "56f8ce779b226e1400dd103d": "18 February", + "56f8ce779b226e1400dd103e": "Lutheran", + "56f8ce779b226e1400dd103f": "31 October", + "56f8ce779b226e1400dd1040": "Lutheran Calendar of Saints", + "56f8ce779b226e1400dd1041": "a commemoration in the Lutheran Calendar of Saints and in the Episcopal (United States) Calendar of Saints", + "5705e26d75f01819005e76d4": "SoCal", + "5705e26d75f01819005e76d5": "10", + "5705e26d75f01819005e76d6": "economic center", + "5705e26d75f01819005e76d7": "demographics and economic", + "5705e26d75f01819005e76d8": "historical political divisions", + "5705e33f52bb89140068964c": "greater Southern California Megaregion", + "5705e33f52bb89140068964d": "11", + "5705e33f52bb89140068964e": "Las Vegas, Nevada", + "5705e33f52bb89140068964f": "Tijuana", + "5705e33f52bb891400689650": "Las Vegas, Nevada", + "5705e3f252bb89140068966a": "Pacific coast", + "5705e3f252bb89140068966b": "seven", + "5705e3f252bb89140068966c": "over 12 million", + "5705e3f252bb89140068966d": "El Centro area", + "5705e3f252bb89140068966e": "17.5 million", + "5705e4fe75f01819005e7704": "Colorado Desert", + "5705e4fe75f01819005e7705": "Colorado Desert", + "5705e4fe75f01819005e7706": "Mojave Desert", + "5705e4fe75f01819005e7707": "Mexico\u2013United States border", + "5705e63175f01819005e7720": "southern California", + "5705e63175f01819005e7721": "3,792,621", + "5705e63175f01819005e7722": "Los Angeles", + "5705e63175f01819005e7723": "San Diego", + "5705e63175f01819005e7724": "south", + "5705e99452bb891400689688": "Los Angeles", + "5705e99452bb891400689689": "United States", + "5705e99452bb89140068968a": "the five most populous", + "5705e99452bb89140068968b": "15", + "5705e99452bb89140068968c": "Los Angeles, Orange, San Diego, San Bernardino, and Riverside", + "5705eb3375f01819005e7764": "Hollywood", + "5705eb3375f01819005e7765": "Los Angeles", + "5705eb3375f01819005e7766": "Walt Disney Company", + "5705eb3375f01819005e7767": "music", + "5705eb3375f01819005e7768": "Sony", + "5705ec1675f01819005e776e": "skateboard", + "5705ec1675f01819005e776f": "Tony Hawk", + "5705ec1675f01819005e7770": "Shaun White", + "5705ec1675f01819005e7771": "Oahu", + "5705ec1675f01819005e7772": "Transpacific Yacht Race", + "5705eccb52bb8914006896b8": "Palm Springs", + "5705eccb52bb8914006896b9": "for its popular beaches", + "5705eccb52bb8914006896ba": "desert", + "5705eccb52bb8914006896bb": "nearby open spaces", + "5705edcd52bb8914006896ca": "37\u00b0 9' 58.23", + "5705edcd52bb8914006896cb": "11", + "5705edcd52bb8914006896cc": "ten", + "5705edcd52bb8914006896cd": "the Tehachapi Mountains", + "5705edcd52bb8914006896ce": "northern", + "5705eee952bb8914006896de": "Mexico", + "5705eee952bb8914006896df": "Alta California", + "5705eee952bb8914006896e0": "Monterey", + "5705eee952bb8914006896e1": "the Compromise", + "5705eee952bb8914006896e2": "free state", + "5705f09e75f01819005e77a4": "inequitable taxes", + "5705f09e75f01819005e77a5": "Cow Counties", + "5705f09e75f01819005e77a6": "three", + "5705f09e75f01819005e77a7": "75%", + "5705f09e75f01819005e77a8": "Milton Latham", + "5705f13d52bb8914006896f0": "Los Angeles Times", + "5705f13d52bb8914006896f1": "1900", + "5705f13d52bb8914006896f2": "1999", + "5705f13d52bb8914006896f3": "Imperial", + "5705f13d52bb8914006896f4": "seven", + "5705f36452bb891400689718": "regional tourism groups", + "5705f36452bb891400689719": "California State Automobile Association", + "5705f36452bb89140068971a": "three-region", + "5705f36452bb89140068971b": "Tehachapis", + "5705f36452bb89140068971c": "southern California region", + "5705f7c875f01819005e77dc": "third", + "5705f7c875f01819005e77dd": "vast areas", + "5705f7c875f01819005e77de": "suburban communities and use of automobiles and highways", + "5705f7c875f01819005e77df": "highways", + "5705f7c875f01819005e77e0": "largest urban areas", + "5705fb7f52bb891400689750": "Camp Pendleton", + "5705fb7f52bb891400689751": "the Inland Empire", + "5705fb7f52bb891400689752": "the United States Census Bureau", + "5705fb7f52bb891400689753": "Orange", + "5705fb7f52bb891400689754": "1990s", + "5705fc3a52bb89140068976a": "Mediterranean", + "5705fc3a52bb89140068976b": "rain", + "5705fc3a52bb89140068976c": "90-60's", + "5705fc3a52bb89140068976d": "rare", + "5705fc3a52bb89140068976e": "90-60's", + "5705fd8475f01819005e7841": "Pacific Ocean islands", + "5705fd8475f01819005e7840": "geologic, topographic, and natural ecosystem", + "5705fd8475f01819005e7842": "geologic, topographic", + "5705fd8475f01819005e7843": "Peninsular", + "5705fd8475f01819005e7844": "Transverse and Peninsular Ranges", + "5705fec152bb89140068977a": "10,000", + "5705fec152bb89140068977b": "10,000", + "5705fec152bb89140068977c": "6.7", + "5705fec152bb89140068977d": "property", + "5705fec152bb89140068977e": "$20 billion", + "5705ffde52bb891400689784": "San Andreas Fault", + "5705ffde52bb891400689785": "6.7+", + "5705ffde52bb891400689786": "Puente Hills Fault", + "5705ffde52bb891400689787": "The USGS", + "5705ffde52bb891400689788": "Earthquake occurrence", + "570602fa52bb89140068979e": "its own culture and atmosphere", + "570602fa52bb89140068979f": "global", + "570602fa52bb8914006897a0": "economic", + "570603c475f01819005e7882": "2010", + "570603c475f01819005e7883": "high growth rates", + "570603c475f01819005e7884": "10.0%", + "570603c475f01819005e7885": "tech-oriented", + "570603c475f01819005e7886": "Sacramento region", + "5706074552bb8914006897d4": "Greater Los Angeles Area at 17,786,419, and San Diego\u2013Tijuana", + "5706074552bb8914006897d5": "two", + "5706074552bb8914006897d6": "five million", + "5706074552bb8914006897d7": "Southern Border Region", + "5706074552bb8914006897d8": "17,786,419", + "570607f575f01819005e78b4": "Los Angeles", + "570607f575f01819005e78b5": "San Diego", + "570607f575f01819005e78b6": "twelve cities with more than 200,000 residents and 34", + "570607f575f01819005e78b7": "100,000", + "570607f575f01819005e78b8": "Riverside", + "5706094b52bb8914006897de": "petroleum", + "5706094b52bb8914006897df": "Hollywood", + "5706094b52bb8914006897e0": "housing bubble", + "5706094b52bb8914006897e1": "diverse", + "5706094b52bb8914006897e2": "heavily impacted", + "57060a1175f01819005e78d2": "1920s", + "57060a1175f01819005e78d3": "richest", + "57060a1175f01819005e78d5": "citrus", + "57060a1175f01819005e78d4": "citrus", + "57060a1175f01819005e78d6": "aerospace", + "57060a6e52bb8914006897f8": "business districts", + "57060a6e52bb8914006897f9": "Central business districts", + "57060a6e52bb8914006897fa": "Downtown Los Angeles, Downtown San Diego, Downtown San Bernardino, Downtown Bakersfield, South Coast Metro and Downtown Riverside", + "57060cc352bb89140068980e": "business districts", + "57060cc352bb89140068980f": "Los Angeles", + "57060cc352bb891400689810": "San Fernando Valley", + "57060cc352bb891400689811": "Los Angeles", + "57060df252bb891400689820": "business", + "57060df252bb891400689821": "Downtown Riverside", + "57060df252bb891400689822": "Hospitality Business/Financial Centre", + "57060eaf75f01819005e7910": "Orange County", + "57060eaf75f01819005e7911": "University of California, Irvine", + "57060eaf75f01819005e7912": "Irvine Tech Center", + "57060eaf75f01819005e7913": "South Coast Metro", + "57060eaf75f01819005e7914": "rapidly", + "57060f3e75f01819005e7922": "Downtown San Diego", + "57060f3e75f01819005e7923": "Northern San Diego and some within North County regions", + "57060f3e75f01819005e7924": "North County", + "57060f3e75f01819005e7925": "Downtown San Diego", + "570610b275f01819005e792a": "Los Angeles International Airport", + "570610b275f01819005e792b": "passenger volume", + "570610b275f01819005e792c": "third", + "570610b275f01819005e792d": "San Diego International Airport", + "570610b275f01819005e792e": "Van Nuys Airport", + "5706111a52bb89140068984c": "Metrolink", + "5706111a52bb89140068984d": "Six", + "5706111a52bb89140068984e": "Six", + "5706111a52bb89140068984f": "Orange", + "570611c475f01819005e793c": "Port of Los Angeles", + "570611c475f01819005e793d": "Port of Long Beach", + "570611c475f01819005e793e": "Southern California", + "5706139252bb891400689864": "The Tech Coast", + "5706139252bb891400689865": "research", + "5706139252bb891400689866": "private", + "5706139252bb891400689867": "5", + "5706139252bb891400689868": "12", + "5706143575f01819005e7950": "NFL", + "5706143575f01819005e7951": "NBA", + "5706143575f01819005e7952": "MLB", + "5706143575f01819005e7953": "Los Angeles Kings", + "5706143575f01819005e7954": "LA Galaxy", + "5706149552bb891400689880": "Chivas", + "5706149552bb891400689881": "two", + "5706149552bb891400689882": "2014", + "5706149552bb891400689883": "StubHub Center", + "5706149552bb891400689884": "2018", + "570614ff52bb89140068988a": "College sports", + "570614ff52bb89140068988b": "USC Trojans", + "570614ff52bb89140068988c": "UCLA Bruins", + "570614ff52bb89140068988d": "Pac-12 Conference", + "570614ff52bb89140068988e": "UCLA Bruins and the USC Trojans", + "5706155352bb891400689894": "Rugby", + "5706155352bb891400689895": "high school", + "5706155352bb891400689896": "an official school sport", + "57092322efce8f15003a7db0": "BSkyB", + "57092322efce8f15003a7db1": "BSkyB", + "57092322efce8f15003a7db2": "2014", + "57092322efce8f15003a7db3": "British Sky Broadcasting Group plc", + "57092322efce8f15003a7db4": "British Sky Broadcasting Limited to Sky UK Limited", + "57094a79efce8f15003a7dc4": "2006", + "57094a79efce8f15003a7dc5": "two", + "57094a79efce8f15003a7dc6": "Setanta Sports", + "57094a79efce8f15003a7dc7": "\u00a31.3bn", + "57094b4f9928a814004714f6": "ONdigital consortium", + "57094b4f9928a814004714f7": "ONdigital consortium", + "57094b4f9928a814004714f8": "three", + "57094b4f9928a814004714f9": "Sky Three", + "57094b4f9928a814004714fa": "Pick TV", + "57094ca7efce8f15003a7dd6": "using a Sky+ PVR", + "57094ca7efce8f15003a7dd7": "September 2007", + "57094ca7efce8f15003a7dd8": "a monthly fee", + "57094ca7efce8f15003a7dd9": "January 2010", + "57094ca7efce8f15003a7dda": "non-HD variant of its Multiroom box", + "57094d489928a8140047150a": "VideoGuard pay-TV scrambling system", + "57094d489928a8140047150b": "NDS, a Cisco Systems company", + "57094d489928a8140047150c": "Cisco Systems company", + "57094d489928a8140047150d": "BSkyB", + "57094d489928a8140047150e": "Sky+", + "570953a7efce8f15003a7dff": "basic channels", + "570953a7efce8f15003a7dfe": "2007", + "570953a7efce8f15003a7e00": "increased the asking price", + "570953a7efce8f15003a7e01": "Video On Demand content", + "570953a7efce8f15003a7e02": "HD channels", + "570960cf200fba1400367f01": "July 2013", + "570960cf200fba1400367f02": "2013", + "570960cf200fba1400367f03": "SkyDrive cloud storage service", + "570960cf200fba1400367f04": "SkyDrive cloud storage service", + "570960cf200fba1400367f05": "cloud storage", + "570961aa200fba1400367f15": "Sam Chisholm and Rupert Murdoch", + "570961aa200fba1400367f16": "Astra", + "570961aa200fba1400367f17": "27 September 2001", + "570961aa200fba1400367f18": "Sky Digital", + "570961aa200fba1400367f19": "3.5 million", + "570963a5200fba1400367f33": "British Sky Broadcasting", + "570963a5200fba1400367f34": "telecommunications", + "570963a5200fba1400367f35": "11 million", + "570963a5200fba1400367f36": "Freeview", + "57096505ed30961900e84082": "Sky Q Hub", + "57096505ed30961900e84083": "Sky Q Silver set top boxes", + "57096505ed30961900e84084": "share recordings and other media", + "57096505ed30961900e84085": "2016", + "57096505ed30961900e84086": "2016", + "570966e0200fba1400367f4f": "MPEG-2", + "570966e0200fba1400367f50": "Dolby Digital soundtracks", + "570966e0200fba1400367f51": "MPEG-4", + "570966e0200fba1400367f52": "OpenTV", + "570966e0200fba1400367f53": "DVB-S2", + "570967c4ed30961900e840ba": "1998", + "570967c4ed30961900e840bb": "Astra 2A", + "570967c4ed30961900e840bc": "Astra 2A", + "570967c4ed30961900e840bd": "hundreds", + "570967c4ed30961900e840be": "28.5\u00b0E", + "5709686c200fba1400367f77": "22 May 2006", + "5709686c200fba1400367f78": "40,000", + "5709686c200fba1400367f79": "Thomson", + "5709686c200fba1400367f7a": "17,000", + "5709686c200fba1400367f7b": "4,222,000", + "57096b66200fba1400367fa7": "8 February 2007", + "57096b66200fba1400367fa8": "March", + "57096b66200fba1400367fa9": "digital terrestrial", + "57096b66200fba1400367faa": "Virgin Media", + "57096b66200fba1400367fab": "English Premier League Football", + "57096c95200fba1400367fbb": "free-to-view", + "57096c95200fba1400367fbc": "a monthly subscription", + "57096c95200fba1400367fbd": "VideoGuard UK", + "57096c95200fba1400367fbe": "universal Ku band LNB", + "57096c95200fba1400367fbf": "Sky service", + "57096e1ced30961900e84102": "autumn of 1991", + "57096e1ced30961900e84103": "ITV", + "57096e1ced30961900e84104": "\u00a334m", + "57096e1ced30961900e84105": "The BBC", + "57096e1ced30961900e84106": "\u00a3304m", + "57096f37200fba1400367fe5": "Ofcom", + "57096f37200fba1400367fe6": "\u00a315\u2013100,000", + "57096f37200fba1400367fe7": "no", + "57096f37200fba1400367fe8": "BSkyB does not", + "57096f37200fba1400367fe9": "BSkyB does not", + "57097051ed30961900e84132": "1 October 1998", + "57097051ed30961900e84133": "Sky Digital", + "57097051ed30961900e84134": "Sky Active", + "57097051ed30961900e84135": "ONdigital", + "57097051ed30961900e84136": "over 100,000", + "57097141200fba1400367ff9": "2007", + "57097141200fba1400367ffa": "Virgin Media", + "57097141200fba1400367ffb": "Video On Demand service", + "57097141200fba1400367ffc": "BBC HD", + "57097141200fba1400367ffd": "Channel 4 HD", + "57097b50200fba140036804d": "10 million", + "57097b50200fba140036804e": "36%", + "57097b50200fba140036804f": "August 2004", + "57097b50200fba1400368050": "36%", + "57097b50200fba1400368051": "flattened", + "57097c8fed30961900e841f2": "Welfare Cash Card", + "57097c8fed30961900e841f3": "\"essentials", + "57097c8fed30961900e841f4": "damaging", + "57097c8fed30961900e841f5": "Sky TV bills", + "57097c8fed30961900e841f6": "betray a man's presence in the household", + "57097d63ed30961900e841fc": "\u00a330m", + "57097d63ed30961900e841fd": "no indication", + "57097d63ed30961900e841fe": "Virgin Media", + "57097d63ed30961900e841ff": "BSkyB", + "57097d63ed30961900e84200": "the carriage of their respective basic channels", + "570d2417fed7b91900d45c3d": "highly diversified", + "570d2417fed7b91900d45c3e": "second", + "570d2417fed7b91900d45c3f": "fourth", + "570d2417fed7b91900d45c40": "Melbourne", + "570d2417fed7b91900d45c41": "Melbourne Cricket Ground", + "570d2556fed7b91900d45c47": "Bendigo", + "570d2556fed7b91900d45c48": "New South Wales", + "570d2556fed7b91900d45c49": "Buckland Valley near Bright", + "570d2556fed7b91900d45c4a": "1,000", + "570d2556fed7b91900d45c4b": "cramped and unsanitary", + "570d26efb3d812140066d48f": "multi-member proportional representation system", + "570d26efb3d812140066d490": "eight", + "570d26efb3d812140066d491": "five", + "570d26efb3d812140066d492": "four years", + "570d26efb3d812140066d493": "November every four years", + "570d28bdb3d812140066d4a3": "Labor", + "570d28bdb3d812140066d4a4": "The Liberals", + "570d28bdb3d812140066d4a5": "The Nationals", + "570d28bdb3d812140066d4a6": "The Greens", + "570d28bdb3d812140066d4a7": "Australian Greens", + "570d29c2b3d812140066d4bd": "61.1%", + "570d29c2b3d812140066d4be": "26.7%", + "570d29c2b3d812140066d4bf": "Buddhism", + "570d29c2b3d812140066d4c0": "168,637", + "570d29c2b3d812140066d4c1": "168,637", + "570d2af0fed7b91900d45c93": "south-east", + "570d2af0fed7b91900d45c94": "second-most populous state overall", + "570d2af0fed7b91900d45c95": "second-most", + "570d2af0fed7b91900d45c96": "Melbourne", + "570d2af0fed7b91900d45c97": "second-largest", + "570d2c20fed7b91900d45ca7": "Koori", + "570d2c20fed7b91900d45ca8": "1788", + "570d2c20fed7b91900d45ca9": "Sullivan Bay", + "570d2c20fed7b91900d45caa": "Sullivan Bay", + "570d2c20fed7b91900d45cab": "1803", + "570d2d68fed7b91900d45cbb": "More than 26,000 square kilometres (10,000 sq mi)", + "570d2d68fed7b91900d45cbc": "50%", + "570d2d68fed7b91900d45cbd": "6,000 square kilometres", + "570d2d68fed7b91900d45cbe": "90%", + "570d2d68fed7b91900d45cbf": "270,000", + "570d2f5bfed7b91900d45ccf": "1855 colonial constitution, passed by the United Kingdom Parliament as the Victoria Constitution Act 1855", + "570d2f5bfed7b91900d45cd0": "the 1855 colonial constitution", + "570d2f5bfed7b91900d45cd1": "Parliament of Victoria", + "570d2f5bfed7b91900d45cd2": "\"entrenched\" provisions that require either an absolute majority in both houses", + "570d2f5bfed7b91900d45cd3": "Victoria Constitution Act 1855", + "570d30fdfed7b91900d45ce3": "hot winds blowing from nearby semi-deserts", + "570d30fdfed7b91900d45ce4": "32 \u00b0C (90 \u00b0F)", + "570d30fdfed7b91900d45ce5": "hot winds blowing from nearby semi-deserts", + "570d30fdfed7b91900d45ce6": "48.8 \u00b0C", + "570d30fdfed7b91900d45ce7": "7 February 2009", + "570d32e4fed7b91900d45d01": "state or government schools", + "570d32e4fed7b91900d45d02": "Victoria Department of Education", + "570d32e4fed7b91900d45d03": "extra costs are levied", + "570d32e4fed7b91900d45d04": "Roman Catholic Church", + "570d32e4fed7b91900d45d05": "government-set curriculum standards", + "570d3468b3d812140066d543": "Australia will no longer be a base for the global car industry", + "570d3468b3d812140066d544": "October 2016", + "570d3468b3d812140066d545": "May 2013", + "570d3468b3d812140066d546": "October 2016", + "570d3468b3d812140066d547": "Ford", + "570d35b7b3d812140066d54d": "2,000 m (6,600 ft)", + "570d35b7b3d812140066d54e": "Mount Bogong", + "570d35b7b3d812140066d54f": "1,986 m", + "570d35b7b3d812140066d550": "river systems", + "570d35b7b3d812140066d551": "helmeted honeyeater", + "570d391fb3d812140066d575": "Victorian Alps in the northeast", + "570d391fb3d812140066d576": "Great Dividing Range mountain system", + "570d391fb3d812140066d577": "east-west", + "570d391fb3d812140066d578": "0 \u00b0C (32 \u00b0F)", + "570d391fb3d812140066d579": "\u221211.7 \u00b0C", + "570d4030fed7b91900d45d9f": "government", + "570d4030fed7b91900d45da0": "Metro Trains Melbourne", + "570d4030fed7b91900d45da1": "Victorian Government", + "570d4030fed7b91900d45da2": "freight services", + "570d4030fed7b91900d45da3": "extensive, electrified, passenger system", + "570d418dfed7b91900d45dbd": "37", + "570d418dfed7b91900d45dbe": "12", + "570d418dfed7b91900d45dbf": "Legislative Assembly", + "570d418dfed7b91900d45dc0": "Legislative Assembly (the lower house) and the Legislative Council", + "570d418dfed7b91900d45dc1": "Linda Dessau", + "570d4329fed7b91900d45dd7": "1 July 1851", + "570d4329fed7b91900d45dd8": "1851", + "570d4329fed7b91900d45dd9": "one of the largest gold rushes", + "570d4329fed7b91900d45dda": "sevenfold", + "570d4329fed7b91900d45ddb": "20 million ounces", + "570d44abb3d812140066d5fd": "1,548", + "570d44abb3d812140066d5fe": "489", + "570d44abb3d812140066d5ff": "540,800", + "570d44abb3d812140066d600": "63,519", + "570d44abb3d812140066d601": "Over 61", + "570d4606b3d812140066d619": "Victoria", + "570d4606b3d812140066d61a": "3 million", + "570d4606b3d812140066d61b": "60%", + "570d4606b3d812140066d61c": "two-thirds", + "570d4606b3d812140066d61d": "Asia", + "570d47b8b3d812140066d62d": "1,600 mm (5 ft 3 in) broad gauge", + "570d47b8b3d812140066d62e": "1,435 mm (4 ft 8 1\u20442 in) standard gauge", + "570d47b8b3d812140066d62f": "760 mm", + "570d47b8b3d812140066d630": "mountainous areas", + "570d47b8b3d812140066d631": "five", + "570d4a6bfed7b91900d45e13": "1788", + "570d4a6bfed7b91900d45e14": "New South Wales", + "570d4a6bfed7b91900d45e15": "New Holland", + "570d4a6bfed7b91900d45e16": "Sydney", + "570d4c3bfed7b91900d45e31": "1854", + "570d4c3bfed7b91900d45e33": "miners", + "570d4c3bfed7b91900d45e32": "Eureka Stockade", + "570d4c3bfed7b91900d45e34": "mining licence fees", + "570d4c3bfed7b91900d45e35": "Colony of Victoria Act 1855", + "570d4e6cb3d812140066d66d": "political party or coalition", + "570d4e6cb3d812140066d66e": "The Premier is the public face of government and, with cabinet", + "570d4e6cb3d812140066d66f": "representatives elected to either house of parliament", + "570d4e6cb3d812140066d670": "Daniel Andrews", + "570d4e6cb3d812140066d671": "Cabinet consists of representatives elected to either house of parliament", + "570d50a5fed7b91900d45e7d": "$8.7 billion", + "570d50a5fed7b91900d45e7e": "17%", + "570d50a5fed7b91900d45e7f": "32,463", + "570d50a5fed7b91900d45e80": "136,000 square kilometres (52,500 sq mi) of Victorian land. This comprises more than 60%", + "570d50a5fed7b91900d45e81": "60%", + "570d529fb3d812140066d6bb": "tourism", + "570d529fb3d812140066d6bc": "sports tourism", + "570d529fb3d812140066d6bd": "Melbourne", + "570d529fb3d812140066d6be": "regional cities", + "570d529fb3d812140066d6bf": "SurfClassic", + "57105da9a58dae1900cd699e": "southern and central parts of France", + "57105da9a58dae1900cd699f": "one-eighth", + "57105da9a58dae1900cd69a0": "1562 to 1598", + "57105da9a58dae1900cd69a1": "Edict of Nantes", + "57105da9a58dae1900cd69a2": "granted the Huguenots substantial religious, political and military autonomy", + "57106185b654c5140001f8db": "derision", + "57106185b654c5140001f8dd": "Geneva", + "57106185b654c5140001f8dc": "Besan\u00e7on Hugues", + "57106185b654c5140001f8de": "Amboise plot", + "57106185b654c5140001f8df": "1560", + "57106644b654c5140001f8e5": "The availability of the Bible in vernacular languages", + "57106644b654c5140001f8e6": "1294", + "57106644b654c5140001f8e7": "Guyard de Moulin", + "57106644b654c5140001f8e8": "1487", + "57106644b654c5140001f8e9": "Paris", + "57106d2fb654c5140001f8ef": "villes de s\u00fbret\u00e9", + "57106d2fb654c5140001f8f0": "Montpellier", + "57106d2fb654c5140001f8f2": "Edict of 1598", + "57106d2fb654c5140001f8f1": "1622", + "57106d2fb654c5140001f8f3": "1598", + "571077ecb654c5140001f909": "Cape of Good Hope", + "571077ecb654c5140001f90a": "Cape Town", + "571077ecb654c5140001f90b": "Maria de la Queillerie", + "571077ecb654c5140001f90c": "Dutch East India Company", + "571077ecb654c5140001f90d": "1700", + "57107932a58dae1900cd69ca": "1624", + "57107932a58dae1900cd69cb": "Jess\u00e9 de Forest", + "57107932a58dae1900cd69cc": "L'\u00c9glise fran\u00e7aise \u00e0 la Nouvelle-Amsterdam", + "57107932a58dae1900cd69cd": "L'Eglise du Saint-Esprit", + "57107932a58dae1900cd69ce": "Brooklyn", + "57107a3ea58dae1900cd69df": "Charleston", + "57107a3ea58dae1900cd69e1": "Edmund Bellinger", + "57107a3ea58dae1900cd69e2": "Pons", + "57107a3ea58dae1900cd69e0": "1697", + "57107a3ea58dae1900cd69de": "Charleston", + "57107c24a58dae1900cd69e8": "William III of Orange", + "57107c24a58dae1900cd69e9": "King of England", + "57107c24a58dae1900cd69ea": "League of Augsburg", + "57107c24a58dae1900cd69eb": "Dutch Republic", + "57107c24a58dae1900cd69ec": "1672", + "57107d73b654c5140001f91d": "Edict of Fontainebleau", + "57107d73b654c5140001f91e": "1685", + "57107d73b654c5140001f91f": "Huguenots", + "57107d73b654c5140001f920": "500,000", + "57107e6ca58dae1900cd69f2": "The Catholic Church in France", + "57107e6ca58dae1900cd69f3": "St. Bartholomew's Day massacre", + "57107e6ca58dae1900cd69f4": "5,000 to 30,000", + "57107e6ca58dae1900cd69f5": "their own militia", + "57107e6ca58dae1900cd69f6": "political reasons", + "57108073b654c5140001f927": "between 1621 and 1629", + "57108073b654c5140001f926": "southwestern France", + "57108073b654c5140001f928": "Henry IV", + "57108073b654c5140001f929": "Louis XIII", + "57108073b654c5140001f925": "Huguenot rebellions", + "57108198b654c5140001f937": "Approximately one million", + "57108198b654c5140001f938": "2%", + "57108198b654c5140001f939": "Alsace", + "57108198b654c5140001f93a": "C\u00e9vennes mountain region", + "57108198b654c5140001f93b": "Australia", + "57108c95b654c5140001f979": "New Rochelle", + "57108c95b654c5140001f97a": "New Paltz", + "57108c95b654c5140001f97b": "Huguenot Street Historic District", + "57108c95b654c5140001f97c": "Huguenot Street Historic District", + "57108c95b654c5140001f97d": "Staten Island", + "57108d69b654c5140001f983": "the Dutch Republic", + "57108d69b654c5140001f984": "75,000 to 100,000", + "57108d69b654c5140001f985": "ca. 2 million", + "57108d69b654c5140001f986": "Amsterdam and the area of West Frisia", + "57108d69b654c5140001f987": "Edict of Nantes", + "57108ee6a58dae1900cd6a1a": "Huguon", + "57108ee6a58dae1900cd6a1b": "Huguon", + "57108ee6a58dae1900cd6a1c": "le roi Huguet", + "57108ee6a58dae1900cd6a1d": "pr\u00e9tendus r\u00e9form\u00e9s", + "57108ee6a58dae1900cd6a1e": "night", + "571090abb654c5140001f995": "Canterbury", + "571090abb654c5140001f996": "The Weavers", + "571090abb654c5140001f997": "the variety of occupations necessary to sustain the community as distinct from the indigenous population", + "571090abb654c5140001f998": "Sandwich, Faversham and Maidstone", + "571090abb654c5140001f999": "a restaurant", + "57109180a58dae1900cd6a41": "Cork City", + "57109180a58dae1900cd6a40": "Dublin, Cork, Youghal and Waterford", + "57109180a58dae1900cd6a42": "Dublin", + "57109180a58dae1900cd6a43": "a High Sheriff and one of the founders of the Bank of Ireland", + "57109180a58dae1900cd6a44": "1696", + "57109275b654c5140001f99f": "brain drain", + "57109275b654c5140001f9a0": "British colonies", + "57109275b654c5140001f9a1": "non-Catholics", + "57109275b654c5140001f9a2": "Seven Years' War", + "57109275b654c5140001f9a3": "1759-60", + "571093aba58dae1900cd6a5c": "Henry of Navarre", + "571093aba58dae1900cd6a5d": "1598", + "571093aba58dae1900cd6a5e": "reaffirmed Catholicism as the state religion of France", + "571093aba58dae1900cd6a5f": "the founding of new Protestant churches", + "571093aba58dae1900cd6a60": "Roman Catholicism", + "571094b7a58dae1900cd6a66": "education", + "571094b7a58dae1900cd6a67": "prohibited emigration", + "571094b7a58dae1900cd6a68": "Four thousand", + "571094b7a58dae1900cd6a69": "new converts", + "571094b7a58dae1900cd6a6a": "New York and Virginia", + "571095a8a58dae1900cd6a76": "Switzerland and the Netherlands", + "571095a8a58dae1900cd6a77": "1555", + "571095a8a58dae1900cd6a78": "France Antarctique", + "571095a8a58dae1900cd6a79": "1560", + "571095a8a58dae1900cd6a7a": "the Guanabara Confession of Faith", + "5710968aa58dae1900cd6a86": "Afrikaans", + "5710968aa58dae1900cd6a87": "wine", + "5710968aa58dae1900cd6a88": "Western Cape province", + "5710968aa58dae1900cd6a89": "surnames", + "571097baa58dae1900cd6a98": "Paul Revere", + "571097baa58dae1900cd6a99": "Henry Laurens", + "571097baa58dae1900cd6a9a": "Charleston", + "571097baa58dae1900cd6a9b": "Manakin Episcopal Church", + "571097baa58dae1900cd6a9c": "Texas", + "571098f8a58dae1900cd6ab2": "British lace", + "571098f8a58dae1900cd6ab3": "Bucks Point", + "571098f8a58dae1900cd6ab4": "Bucks Point", + "571098f8a58dae1900cd6ab5": "first half of the eighteenth century", + "571099b2b654c5140001f9b3": "Dorotheenstadt and Friedrichstadt", + "571099b2b654c5140001f9b4": "one-fifth", + "571099b2b654c5140001f9b5": "protest against the occupation of Prussia", + "571099b2b654c5140001f9b6": "1806-07", + "571099b2b654c5140001f9b7": "Fredericia (Denmark), Berlin, Stockholm, Hamburg, Frankfurt, Helsinki, and Emden", + "5710e8c8a58dae1900cd6b26": "England, the Netherlands, Switzerland, Norway, Denmark, and Prussia", + "5710e8c8a58dae1900cd6b27": "C\u00e9vennes region in the south", + "5710e8c8a58dae1900cd6b28": "Camisards", + "5710e8c8a58dae1900cd6b29": "Catholic Church", + "5710e8c8a58dae1900cd6b2a": "1702 and 1709", + "5710e9f8a58dae1900cd6b30": "Jacksonville", + "5710e9f8a58dae1900cd6b31": "Jean Ribault", + "5710e9f8a58dae1900cd6b32": "Fort Caroline", + "5710e9f8a58dae1900cd6b33": "French", + "5710e9f8a58dae1900cd6b34": "September 1565", + "5710eb6fb654c5140001fa17": "Charlesfort", + "5710eb6fb654c5140001fa18": "Fort Caroline", + "5710eb6fb654c5140001fa19": "Pedro Men\u00e9ndez de Avil\u00e9s", + "5710eb6fb654c5140001fa1a": "1562", + "5710eb6fb654c5140001fa1b": "Wars of Religion", + "5710eca0a58dae1900cd6b3a": "Virginia", + "5710eca0a58dae1900cd6b3b": "Lower Norfolk County", + "5710eca0a58dae1900cd6b3c": "Manakin Town", + "5710eca0a58dae1900cd6b3d": "390", + "5710eca0a58dae1900cd6b3e": "1700", + "5710ed7bb654c5140001fa2b": "1568\u20131609", + "5710ed7bb654c5140001fa2c": "Spain", + "5710ed7bb654c5140001fa2d": "Apologie", + "5710ed7bb654c5140001fa2e": "William the Silent", + "5710ed7bb654c5140001fa2f": "Calvinist", + "5710f114a58dae1900cd6b60": "Foreign Protestants Naturalization Act", + "5710f114a58dae1900cd6b61": "1708", + "5710f114a58dae1900cd6b62": "50,000", + "5710f114a58dae1900cd6b63": "Andrew Lortie", + "5710f114a58dae1900cd6b64": "Pope", + "5710f2e2a58dae1900cd6b72": "Williamite war", + "5710f2e2a58dae1900cd6b73": "William of Orange", + "5710f2e2a58dae1900cd6b74": "Dublin, Cork, Portarlington, Lisburn, Waterford and Youghal", + "5710f2e2a58dae1900cd6b75": "flax", + "5710f2e2a58dae1900cd6b76": "linen", + "5710f4b8b654c5140001fa45": "Prince Louis de Cond\u00e9", + "5710f4b8b654c5140001fa46": "Count Ludwig von Nassau-Saarbr\u00fccken", + "5710f4b8b654c5140001fa47": "glass-making works, which provided wealth to the principality for many years. Other founding families created enterprises based on textiles", + "5710f4b8b654c5140001fa48": "1890s", + "5710f4b8b654c5140001fa49": "1604", + "5711119cb654c5140001fae3": "England, Wales, Scotland, Denmark, Sweden, Switzerland, the Dutch Republic, the Electorate of Brandenburg and Electorate of the Palatinate", + "5711119cb654c5140001fae4": "Protestant", + "5711119cb654c5140001fae6": "Quebec", + "5711119cb654c5140001fae5": "Dutch Cape Colony", + "5711119cb654c5140001fae7": "they were accepted and allowed to worship freely", + "571112ada58dae1900cd6bcc": "Hugues Capet", + "571112ada58dae1900cd6bcd": "Hugues hypothesis", + "571112ada58dae1900cd6bce": "Janet Gray", + "571112ada58dae1900cd6bcf": "little Hugos, or those who want Hugo", + "571112ada58dae1900cd6bd0": "double or triple non-French linguistic origins", + "57111380a58dae1900cd6bd6": "Jacques Lefevre", + "57111380a58dae1900cd6bd7": "University of Paris", + "57111380a58dae1900cd6bd8": "1530", + "57111380a58dae1900cd6bd9": "William Farel", + "57111380a58dae1900cd6bda": "Jean Cauvin", + "57111428b654c5140001faff": "24 August \u2013 3 October 1572", + "57111428b654c5140001fb00": "Catholics", + "57111428b654c5140001fb01": "Nearly 3,000", + "57111428b654c5140001fb02": "1573", + "57111429b654c5140001fb03": "25,000", + "571114cfb654c5140001fb09": "Louis XIV", + "571114cfb654c5140001fb0a": "increasingly aggressively to force the Huguenots to convert", + "571114cfb654c5140001fb0b": "sent missionaries", + "571114cfb654c5140001fb0c": "closed Huguenot schools and excluded them from favored professions", + "571114cfb654c5140001fb0d": "dragonnades", + "5711163bb654c5140001fb13": "Westchester", + "5711163bb654c5140001fb14": "New Rochelle", + "5711163bb654c5140001fb15": "John Pell", + "5711163bb654c5140001fb16": "La Rochelle", + "5711163bb654c5140001fb17": "Trinity-St. Paul's Episcopal Church", + "57111713a58dae1900cd6c00": "quickly and often married outside their immediate French communities", + "57111713a58dae1900cd6c01": "married outside their immediate French communities", + "57111713a58dae1900cd6c02": "E.I. du Pont", + "57111713a58dae1900cd6c03": "well into the nineteenth century", + "57111713a58dae1900cd6c04": "Eleutherian gunpowder mills", + "571117d4a58dae1900cd6c0a": "Pierre Bayle", + "571117d4a58dae1900cd6c0b": "Rotterdam", + "571117d4a58dae1900cd6c0c": "Historical and Critical Dictionary", + "571117d4a58dae1900cd6c0d": "US Library of Congress", + "571117d4a58dae1900cd6c0e": "Nicolas", + "57111992b654c5140001fb43": "The French Protestant Church of London", + "57111992b654c5140001fb44": "1550", + "57111992b654c5140001fb45": "Soho Square", + "57111992b654c5140001fb46": "Shoreditch", + "57111992b654c5140001fb47": "1724", + "57111ab8a58dae1900cd6c3c": "Lutheran and Reformed", + "57111ab8a58dae1900cd6c3d": "Brandenburg-Prussia", + "57111ab8a58dae1900cd6c3e": "Edict of Potsdam", + "57111ab8a58dae1900cd6c3f": "Elector of Brandenburg and Duke of Prussia", + "57111ab8a58dae1900cd6c40": "two new regiments", + "57111b95a58dae1900cd6c50": "Frederick William", + "57111b95a58dae1900cd6c51": "Theodor Fontane", + "57111b95a58dae1900cd6c52": "Adolf Galland", + "57111b95a58dae1900cd6c53": "Lothar de Maizi\u00e8re", + "57111b95a58dae1900cd6c54": "Federal Minister of the Interior", + "57112686b654c5140001fbd3": "solar power", + "57112686b654c5140001fbd4": "Rankine cycle", + "57112686b654c5140001fbd5": "steam", + "57112686b654c5140001fbd6": "high pressure", + "57112686b654c5140001fbd7": "external combustion engines", + "571126dfa58dae1900cd6cb2": "the atmospheric engine", + "571126dfa58dae1900cd6cb3": "Thomas Newcomen", + "571126dfa58dae1900cd6cb4": "1712", + "571126dfa58dae1900cd6cb5": "steam pump", + "571126dfa58dae1900cd6cb6": "Papin", + "571127a5a58dae1900cd6cc4": "United Kingdom", + "571127a5a58dae1900cd6cc5": "21 February 1804", + "571127a5a58dae1900cd6cc6": "Pen-y-darren ironworks, near Merthyr Tydfil to Abercynon in south Wales", + "571127a5a58dae1900cd6cc7": "south Wales", + "571127a5a58dae1900cd6cc8": "south Wales", + "571135b8a58dae1900cd6d0e": "water pump", + "571135b8a58dae1900cd6d0f": "multi-stage centrifugal pumps", + "571135b8a58dae1900cd6d10": "1850s", + "571135b8a58dae1900cd6d11": "steam locomotives", + "571135b8a58dae1900cd6d12": "lower-pressure boiler feed water", + "57113639a58dae1900cd6d18": "three or four", + "57113639a58dae1900cd6d19": "triple and quadruple expansion engines", + "57113639a58dae1900cd6d1a": "19th", + "57113639a58dae1900cd6d1b": "marine triple expansion engines", + "57113639a58dae1900cd6d1c": "Olympic class", + "571136b8a58dae1900cd6d22": "Corliss", + "571136b8a58dae1900cd6d23": "Joy", + "571136b8a58dae1900cd6d24": "lengthening rubbing surfaces of the valve", + "57113ba6b654c5140001fc1f": "Lead fusible plugs", + "57113ba6b654c5140001fc20": "the lead melts and the steam escapes", + "57113ba6b654c5140001fc21": "the steam escapes", + "57113ba6b654c5140001fc22": "manually suppress the fire", + "57113ba6b654c5140001fc23": "dampening the fire", + "57113be3a58dae1900cd6d28": "James Watt", + "57113be3a58dae1900cd6d29": "rotary motion", + "57113be3a58dae1900cd6d2a": "ten", + "57113be3a58dae1900cd6d2b": "1883", + "57113be3a58dae1900cd6d2c": "Industrial Revolution", + "57113c6da58dae1900cd6d32": "first century AD", + "57113c6da58dae1900cd6d33": "Hero of Alexandria", + "57113c6da58dae1900cd6d34": "Greek", + "57113c6da58dae1900cd6d35": "Giovanni Branca", + "57113c6da58dae1900cd6d36": "1606", + "57113f83b654c5140001fc29": "compound engines", + "57113f83b654c5140001fc2a": "expansions", + "57113f83b654c5140001fc2b": "shipping", + "57113f83b654c5140001fc2d": "internal combustion engines", + "57113f83b654c5140001fc2c": "coal", + "571142b3a58dae1900cd6d5a": "steam turbines", + "571142b3a58dae1900cd6d5b": "late", + "571142b3a58dae1900cd6d5c": "several hundred", + "571142b3a58dae1900cd6d5d": "90%", + "571142b3a58dae1900cd6d5e": "electric", + "571144d1a58dae1900cd6d6e": "burning combustible materials with an appropriate supply of air in a closed space", + "571144d1a58dae1900cd6d6f": "combustion chamber", + "571144d1a58dae1900cd6d70": "solar energy", + "571144d1a58dae1900cd6d71": "electric", + "57114667a58dae1900cd6d80": "steam engine indicator", + "57114667a58dae1900cd6d81": "1851", + "57114667a58dae1900cd6d82": "Charles Porter", + "57114667a58dae1900cd6d83": "Charles Richard", + "57114667a58dae1900cd6d84": "London Exhibition", + "5711475ca58dae1900cd6d8a": "90\u00b0", + "5711475ca58dae1900cd6d8b": "180\u00b0", + "5711475ca58dae1900cd6d8c": "90\u00b0", + "5711488ab654c5140001fc3d": "counterflow", + "5711488ab654c5140001fc3e": "two", + "5711488ab654c5140001fc3f": "one", + "5711488ab654c5140001fc40": "four", + "5711488ab654c5140001fc41": "expansion", + "57114aceb654c5140001fc47": "The Quasiturbine", + "57114aceb654c5140001fc48": "counterflow", + "57114aceb654c5140001fc49": "an additional port", + "57114b1a2419e31400955575": "oscillating cylinder steam engine", + "57114b1a2419e31400955576": "trunnion", + "57114b1a2419e31400955577": "models", + "57114b1a2419e31400955578": "ships", + "57114dfb50c2381900b54a53": "recycled continuously", + "57114dfb50c2381900b54a54": "open loop\" system", + "57114dfb50c2381900b54a55": "Mercury", + "57114dfb50c2381900b54a56": "water", + "57114e8d50c2381900b54a5b": "working fluid", + "57114e8d50c2381900b54a5c": "565 \u00b0C", + "57114e8d50c2381900b54a5d": "stainless steel", + "57114e8d50c2381900b54a5f": "63%", + "57114e8d50c2381900b54a5e": "30 \u00b0C", + "57114f0050c2381900b54a65": "Steam engines", + "57114f0050c2381900b54a66": "steamboats", + "57114f0050c2381900b54a67": "Stanley Steamer", + "57114f0050c2381900b54a68": "factories", + "57114f0050c2381900b54a69": "increase in the land available for cultivation", + "571153422419e3140095557d": "Catch Me Who Can", + "571153422419e3140095557e": "Matthew Murray", + "571153422419e3140095557f": "twin-cylinder", + "571153422419e31400955580": "rack and pinion Middleton Railway", + "571153422419e31400955581": "Stockton and Darlington Railway", + "5711541350c2381900b54a6f": "Arthur Woolf", + "5711541350c2381900b54a70": "British", + "5711541350c2381900b54a71": "torque variability", + "5711541350c2381900b54a72": "cylinder volume", + "571154c72419e31400955587": "90%", + "571154c72419e31400955588": "reciprocating Diesel engines, and gas turbines", + "571154c72419e31400955589": "gas turbines", + "571154c72419e3140095558a": "steam turbines", + "571154c72419e3140095558b": "reduction", + "571155ae2419e31400955591": "The Rankine cycle", + "571155ae2419e31400955592": "removed in a condenser", + "571155ae2419e31400955593": "1990s", + "571155ae2419e31400955594": "biomass", + "571155ae2419e31400955595": "Scottish", + "571156152419e3140095559b": "duty", + "571156152419e3140095559f": "17", + "571156152419e3140095559e": "energy efficiency", + "571156152419e3140095559d": "94", + "571156152419e3140095559c": "Watt", + "57115ac550c2381900b54a77": "steam turbines", + "57115ac550c2381900b54a78": "Reciprocating piston type", + "57115ac550c2381900b54a79": "turbine type steam engines", + "57115ac550c2381900b54a7a": "internal combustion engines", + "57115b2850c2381900b54a7f": "Thomas Savery", + "57115b2850c2381900b54a80": "water pump", + "57115b2850c2381900b54a81": "1698", + "57115b2850c2381900b54a82": "Bento de Moura Portugal", + "57115b2850c2381900b54a83": "John Smeaton", + "57115b8b50c2381900b54a89": "Richard Trevithick", + "57115b8b50c2381900b54a8a": "Richard Trevithick and, separately, Oliver Evans", + "57115b8b50c2381900b54a8b": "1802", + "57115b8b50c2381900b54a8c": "transport", + "57115b8b50c2381900b54a8d": "manufacturing techniques", + "57115bf350c2381900b54a93": "Energiprojekt AB", + "57115bf350c2381900b54a94": "Sweden", + "57115bf350c2381900b54a95": "5", + "57115bf350c2381900b54a96": "8.8", + "57115bf350c2381900b54a97": "27-30%", + "57115c7450c2381900b54a9d": "surface condensers", + "57115c7450c2381900b54a9e": "automobile radiator", + "57115c7450c2381900b54a9f": "locations where water is costly", + "57115c7450c2381900b54aa0": "wet", + "57115c7450c2381900b54aa1": "3600", + "57115dbe2419e314009555a5": "The centrifugal governor", + "57115dbe2419e314009555a6": "Boulton", + "57115dbe2419e314009555a7": "flour mill", + "57115dbe2419e314009555a8": "cotton spinning", + "57115dbe2419e314009555a9": "handle smaller variations such as those caused by fluctuating heat load to the boiler", + "57115e532419e314009555af": "1880", + "57115e532419e314009555b0": "railway locomotives", + "57115e532419e314009555b1": "complicated", + "57115e532419e314009555b2": "1930", + "57115e532419e314009555b3": "road engines", + "57115f0a50c2381900b54aa7": "shortening the cutoff", + "57115f0a50c2381900b54aa8": "kick back", + "57115f0a50c2381900b54aa9": "evacuate the cylinder", + "57115f0a50c2381900b54aaa": "fixed length", + "57115f652419e314009555b9": "Jer\u00f3nimo de Ayanz y Beaumont", + "57115f652419e314009555ba": "Spanish", + "57115f652419e314009555bb": "1606", + "57115f652419e314009555bc": "1698", + "57115f652419e314009555bd": "1712", + "57115ff82419e314009555c3": "rotating discs", + "57115ff82419e314009555c4": "a drive shaft", + "57115ff82419e314009555c5": "static discs", + "57115ff82419e314009555c6": "turbine casing", + "57115ff82419e314009555c7": "3600 revolutions per minute", + "5711607f2419e314009555cd": "lower", + "5711607f2419e314009555ce": "electric motors", + "5711607f2419e314009555cf": "steam turbine plant", + "5711607f2419e314009555d0": "Advanced Steam movement", + "5711607f2419e314009555d1": "pollution", + "571161092419e314009555d7": "Wankel engine", + "571161092419e314009555d8": "cylinders and valve gear", + "571161092419e314009555d9": "thermal expansion", + "5711619950c2381900b54aaf": "1763\u20131775", + "5711619950c2381900b54ab0": "a separate condenser", + "5711619950c2381900b54ab1": "half", + "5711619950c2381900b54ab2": "Newcomen", + "5711619950c2381900b54ab3": "a piston into the partial vacuum generated by condensing steam", + "5711623e50c2381900b54ab9": "two", + "5711623e50c2381900b54aba": "a plug valve", + "5711623e50c2381900b54abb": "adjustable spring-loaded valve", + "5711623e50c2381900b54abc": "seal", + "5711623e50c2381900b54abd": "power", + "5711628a2419e314009555dd": "Corliss steam engine", + "5711628a2419e314009555de": "1849", + "5711628a2419e314009555e1": "30%", + "5711628a2419e314009555df": "four", + "5711628a2419e314009555e0": "Rumford medal", + "571163172419e314009555e7": "thermodynamic theory", + "571163172419e314009555e8": "Watt", + "571163172419e314009555e9": "the separate condenser", + "571163172419e314009555ea": "Joseph Black", + "571163172419e314009555eb": "latent heat", + "5711648850c2381900b54ac3": "relatively little work is required to drive the pump", + "5711648850c2381900b54ac4": "liquid phase", + "5711648850c2381900b54ac5": "1% to 3%", + "5711648850c2381900b54ac6": "1500 \u00b0C", + "5711651050c2381900b54acb": "injector", + "5711651050c2381900b54acc": "recover the latent heat of vaporisation", + "5711651050c2381900b54acd": "superheaters", + "5711651050c2381900b54ace": "bunker", + "5711651050c2381900b54acf": "chain or screw stoking mechanism", + "5711658e50c2381900b54ad5": "feed water", + "5711658e50c2381900b54ad6": "British", + "5711658e50c2381900b54ad7": "dreadnought battleships", + "5711658e50c2381900b54ad8": "dreadnought battleships", + "5711658e50c2381900b54ad9": "1905", + "571166352419e314009555f1": "water", + "571166352419e314009555f2": "a turbine connected to an electrical generator", + "571166352419e314009555f3": "an electrical generator", + "571166352419e314009555f4": "turbo-electric transmission", + "571166352419e314009555f5": "Sweden", + "5711669550c2381900b54adf": "a practical Carnot cycle", + "5711669550c2381900b54ae0": "in the condenser", + "5711669550c2381900b54ae1": "constant pressure", + "5711669550c2381900b54ae2": "isothermal", + "5711669550c2381900b54ae3": "liquid", + "571a484210f8ca1400304fbd": "8", + "571a484210f8ca1400304fbe": "hydrogen and helium", + "571a484210f8ca1400304fc0": "two", + "571a484210f8ca1400304fc1": "almost half", + "571a484210f8ca1400304fbf": "Diatomic oxygen gas", + "571bb2269499d21900609ca9": "20.8%", + "571bb2269499d21900609caa": "silicon dioxide", + "571bb2269499d21900609cab": "8", + "571bb2269499d21900609cad": "global downward trend", + "571bb2269499d21900609cac": "hydrogen and helium", + "571c3a685efbb31900334db2": "8", + "571c3a685efbb31900334db3": "chalcogen group", + "571c3a685efbb31900334db4": "oxides", + "571c3a685efbb31900334db5": "third", + "571c3a685efbb31900334db6": "dioxygen", + "571a49de4faf5e1900b8a94a": "photosynthesis", + "571a49de4faf5e1900b8a94b": "sunlight", + "571a49de4faf5e1900b8a94c": "high-altitude ozone layer", + "571c3c47dd7acb1400e4c09c": "oxygen", + "571c3c47dd7acb1400e4c09d": "water", + "571c3c47dd7acb1400e4c09e": "photosynthesis", + "571c3c47dd7acb1400e4c09f": "water", + "571c3c47dd7acb1400e4c0a0": "allotrope", + "571a4b0f10f8ca1400304fd5": "Robert Boyle", + "571a4b0f10f8ca1400304fd6": "John Mayow", + "571a4b0f10f8ca1400304fd7": "nitroaereus", + "571a4b0f10f8ca1400304fd8": "1679", + "571c3e8cdd7acb1400e4c0a6": "Robert Boyle", + "571c3e8cdd7acb1400e4c0a7": "spiritus nitroaereus", + "571c3e8cdd7acb1400e4c0a8": "17th", + "571c3e8cdd7acb1400e4c0a9": "respiration", + "571c3e8cdd7acb1400e4c0aa": "John Mayow", + "571a4d1a4faf5e1900b8a958": "Priestley", + "571a4d1a4faf5e1900b8a959": "clergyman", + "571a4d1a4faf5e1900b8a95b": "HgO", + "571a4d1a4faf5e1900b8a95a": "mercuric oxide", + "571c4132dd7acb1400e4c0b0": "mercuric oxide", + "571c4132dd7acb1400e4c0b1": "dephlogisticated air", + "571c4132dd7acb1400e4c0b2": "1775", + "571c4132dd7acb1400e4c0b3": "Because he published his findings first", + "571c4132dd7acb1400e4c0b4": "more active", + "571a4ead10f8ca1400304fdd": "Leonardo da Vinci", + "571a4ead10f8ca1400304fde": "Philo of Byzantium", + "571a4ead10f8ca1400304fdf": "2nd century BCE", + "571a4ead10f8ca1400304fe0": "Philo incorrectly surmised that parts of the air in the vessel were converted into the classical element fire", + "571c7abfdd7acb1400e4c0ba": "Philo of Byzantium", + "571c7abfdd7acb1400e4c0bb": "classical element fire", + "571c7abfdd7acb1400e4c0bc": "Pneumatica", + "571c7abfdd7acb1400e4c0bd": "Leonardo da Vinci", + "571c7abfdd7acb1400e4c0be": "air", + "571a50df4faf5e1900b8a960": "an ignition event, such as heat or a spark", + "571a50df4faf5e1900b8a961": "the source of most of the chemical energy", + "571a50df4faf5e1900b8a962": "Combustion hazards", + "571a50df4faf5e1900b8a963": "Oxygen", + "571cebc05efbb31900334e49": "an ignition event", + "571cebc05efbb31900334e4a": "oxidant", + "571cebc05efbb31900334e48": "rapid combustion", + "571cebc05efbb31900334e4b": "the source of most of the chemical energy", + "571cebc05efbb31900334e4c": "peroxides, chlorates, nitrates, perchlorates, and dichromates", + "571a52cb4faf5e1900b8a968": "pure O\n2", + "571a52cb4faf5e1900b8a969": "Steel pipes and storage vessels used to store and transmit both gaseous and liquid oxygen will act as a fuel", + "571a52cb4faf5e1900b8a96a": "1\u20443", + "571a52cb4faf5e1900b8a96b": "special training", + "571ce9bddd7acb1400e4c1a0": "combustion", + "571ce9bddd7acb1400e4c1a1": "slightly more than atmospheric pressure", + "571ce9bddd7acb1400e4c1a2": "fuel", + "571ce9bddd7acb1400e4c1a4": "Apollo 1 crew", + "571a53d410f8ca1400304fe6": "silica SiO\n2", + "571a53d410f8ca1400304fe7": "carbon dioxide", + "571a53d410f8ca1400304fe5": "The Earth's mantle", + "571ce7f25efbb31900334e3e": "carbon dioxide", + "571ce7f25efbb31900334e3f": "The Earth's crustal rock", + "571ce7f25efbb31900334e40": "The Earth's mantle", + "571ce7f25efbb31900334e41": "The Earth's mantle", + "571ce7f25efbb31900334e42": "silicon", + "571c7d55dd7acb1400e4c0c4": "monatomic", + "571c7d55dd7acb1400e4c0c5": "simplest", + "571c7d55dd7acb1400e4c0c6": "HO", + "571c7d55dd7acb1400e4c0c7": "hydrogen", + "571c7d55dd7acb1400e4c0c8": "Avogadro's law", + "571c8198dd7acb1400e4c0ce": "phlogiston", + "571c8198dd7acb1400e4c0cf": "wood or coal", + "571c8198dd7acb1400e4c0d0": "Air", + "571c8198dd7acb1400e4c0d1": "metals", + "571c8198dd7acb1400e4c0d2": "lighter", + "571c83f3dd7acb1400e4c0d8": "a covalent double bond", + "571c83f3dd7acb1400e4c0d9": "two", + "571c83f3dd7acb1400e4c0da": "Aufbau", + "571c83f3dd7acb1400e4c0db": "chemically bonded to each other", + "571c83f3dd7acb1400e4c0dc": "filling of molecular orbitals formed from the atomic orbitals of the individual oxygen atoms", + "571c8539dd7acb1400e4c0e2": "1773", + "571c8539dd7acb1400e4c0e3": "1774", + "571c8539dd7acb1400e4c0e4": "his work was published first", + "571c8539dd7acb1400e4c0e5": "Antoine Lavoisier", + "571c8539dd7acb1400e4c0e6": "phlogiston theory of combustion and corrosion", + "571c879bdd7acb1400e4c0ec": "filled \u03c0* orbitals", + "571c879bdd7acb1400e4c0ed": "triplet oxygen", + "571c879bdd7acb1400e4c0ee": "unpaired electrons", + "571c879bdd7acb1400e4c0ef": "spontaneous", + "571c879bdd7acb1400e4c0f0": "antibonding", + "571c8eb9dd7acb1400e4c0f6": "tin and air were heated in a closed container. He noted that air rushed in when he opened the container, which indicated that part of the trapped air", + "571c8eb9dd7acb1400e4c0f7": "the same as the weight of the air that rushed back in", + "571c8eb9dd7acb1400e4c0f8": "increased in weight", + "571c8eb9dd7acb1400e4c0f9": "1777", + "571c8eb9dd7acb1400e4c0fa": "azote", + "571c9074dd7acb1400e4c100": "Trioxygen", + "571c9074dd7acb1400e4c101": "lung tissue", + "571c9074dd7acb1400e4c102": "lung tissue", + "571c9074dd7acb1400e4c103": "protective radiation shield", + "571c9074dd7acb1400e4c104": "ultraviolet", + "571c91c8dd7acb1400e4c10a": "dioxygen", + "571c91c8dd7acb1400e4c10b": "dioxygen", + "571c91c8dd7acb1400e4c10c": "dioxygen, O\n2", + "571c91c8dd7acb1400e4c10d": "energy content", + "571c91c8dd7acb1400e4c10e": "cellular respiration", + "571c9348dd7acb1400e4c114": "James Dewar", + "571c9348dd7acb1400e4c115": "1891", + "571c9348dd7acb1400e4c116": "1895", + "571c9348dd7acb1400e4c118": "oxyacetylene", + "571c96095efbb31900334dbc": "Oxygen", + "571c96095efbb31900334dbd": "temperature", + "571c96095efbb31900334dbe": "6.04 milliliters", + "571c96095efbb31900334dbf": "nitrogen", + "571c96095efbb31900334dc0": "twice as much", + "571c97e2dd7acb1400e4c11e": "49.2%", + "571c97e2dd7acb1400e4c11f": "third", + "571c97e2dd7acb1400e4c120": "0.9%", + "571c97e2dd7acb1400e4c121": "the world's oceans", + "571c97e2dd7acb1400e4c122": "ultraviolet radiation", + "571caac55efbb31900334dc6": "late 19th", + "571caac55efbb31900334dc7": "compressing and cooling it", + "571caac55efbb31900334dc8": "Louis Paul Cailletet", + "571caac55efbb31900334dc9": "a few drops", + "571caac55efbb31900334dca": "March 29, 1883", + "571cac5d5efbb31900334dd0": "silicon wafer exposed to the solar wind in space and returned by the crashed Genesis spacecraft", + "571cac5d5efbb31900334dd1": "oxygen-16", + "571cac5d5efbb31900334dd2": "crashed Genesis spacecraft", + "571cac5d5efbb31900334dd3": "unknown", + "571cac5d5efbb31900334dd4": "the Earth", + "571cb010dd7acb1400e4c128": "Singlet oxygen", + "571cb010dd7acb1400e4c129": "common organic molecules", + "571cb010dd7acb1400e4c12a": "photosynthesis", + "571cb010dd7acb1400e4c12b": "photolysis of ozone", + "571cb010dd7acb1400e4c12c": "Carotenoids", + "571cb27fdd7acb1400e4c132": "Paleoclimatologists", + "571cb27fdd7acb1400e4c133": "snow and rain", + "571cb27fdd7acb1400e4c134": "12%", + "571cb27fdd7acb1400e4c135": "oxygen-18", + "571cb27fdd7acb1400e4c136": "lower global temperatures", + "571cbe35dd7acb1400e4c13c": "687 and 760 nm", + "571cbe35dd7acb1400e4c13d": "carbon cycle", + "571cbe35dd7acb1400e4c13e": "vegetation canopies", + "571cbe35dd7acb1400e4c13f": "global", + "571cbe35dd7acb1400e4c140": "remote", + "571cc3dedd7acb1400e4c146": "paramagnetic", + "571cc3dedd7acb1400e4c147": "liquid oxygen", + "571cc3dedd7acb1400e4c148": "unpaired electrons", + "571cc3dedd7acb1400e4c149": "magnetic field", + "571cc3dedd7acb1400e4c14a": "a magnet", + "571cc5c45efbb31900334dda": "dangerous", + "571cc5c45efbb31900334ddb": "to destroy invading microbes", + "571cc5c45efbb31900334ddc": "pathogen attack", + "571cc5c45efbb31900334ddd": "obligately anaerobic", + "571cc5c45efbb31900334dde": "2.5 billion years ago", + "571cc6f85efbb31900334de4": "90.20 K", + "571cc6f85efbb31900334de5": "High-purity", + "571cc6f85efbb31900334de6": "liquefied air", + "571cc6f85efbb31900334de7": "liquid nitrogen", + "571cc6f85efbb31900334de8": "combustible", + "571cc8815efbb31900334dee": "water bodies", + "571cc8815efbb31900334def": "lower", + "571cc8815efbb31900334df0": "higher oxygen content", + "571cc8815efbb31900334df2": "algae", + "571cc8815efbb31900334df1": "biochemical oxygen demand", + "571cca4add7acb1400e4c150": "3.5 billion years ago", + "571cca4add7acb1400e4c151": "Paleoproterozoic", + "571cca4add7acb1400e4c152": "banded iron formations", + "571cca4add7acb1400e4c153": "1.7 billion years ago", + "571cca4add7acb1400e4c154": "3\u20132.7 billion years ago", + "571ccc00dd7acb1400e4c15a": "oxygen cycle", + "571ccc00dd7acb1400e4c15b": "biogeochemical cycle", + "571ccc00dd7acb1400e4c15c": "three", + "571ccc00dd7acb1400e4c15d": "photosynthesis", + "571ccc00dd7acb1400e4c15e": "oxygen", + "571ccd9b5efbb31900334df8": "pressure swing adsorption", + "571ccd9b5efbb31900334df9": "90% to 93%", + "571ccd9b5efbb31900334dfa": "nitrogen", + "571ccd9b5efbb31900334dfb": "cryogenic", + "571ccd9b5efbb31900334dfc": "90% to 93%", + "571ccfbadd7acb1400e4c164": "water", + "571ccfbadd7acb1400e4c165": "Oxygen gas", + "571ccfbadd7acb1400e4c166": "O\n2", + "571ccfbadd7acb1400e4c167": "water", + "571ccfbadd7acb1400e4c168": "chemical oxygen generators or oxygen candles", + "571cd11add7acb1400e4c16e": "recreational", + "571cd11add7acb1400e4c16f": "placebo effect", + "571cd11add7acb1400e4c170": "performance", + "571cd11add7acb1400e4c172": "placebo effect", + "571cd11add7acb1400e4c171": "aerobic", + "571cd3b55efbb31900334e03": "special oxygen chambers", + "571cd3b55efbb31900334e04": "carbon monoxide", + "571cd3b55efbb31900334e05": "anaerobic bacteria", + "571cd3b55efbb31900334e06": "Decompression sickness", + "571cd5b1dd7acb1400e4c17b": "oxygen supplementation", + "571cd5b1dd7acb1400e4c17a": "the heart", + "571cd5b1dd7acb1400e4c179": "oxygen supplementation", + "571cd5b1dd7acb1400e4c178": "respiration", + "571cd5b1dd7acb1400e4c17c": "gaseous oxygen", + "571cd703dd7acb1400e4c182": "electronegativity", + "571cd703dd7acb1400e4c183": "non-stoichiometric compounds", + "571cd703dd7acb1400e4c184": "FeO", + "571cd703dd7acb1400e4c185": "chemical bonds with almost all other elements to give corresponding oxides", + "571cd703dd7acb1400e4c186": "further corrosion", + "571cd88ddd7acb1400e4c18d": "cabin depressurization", + "571cd88ddd7acb1400e4c18e": "exothermic reaction", + "571cd88ddd7acb1400e4c18f": "exothermic", + "571cd88ddd7acb1400e4c190": "oxygen gas", + "571cda1bdd7acb1400e4c196": "high pressure", + "571cda1bdd7acb1400e4c198": "specially insulated tankers", + "571cda1bdd7acb1400e4c197": "liquid", + "571cda1bdd7acb1400e4c199": "compressed gas", + "571cda1bdd7acb1400e4c19a": "hospitals", + "571cdcb85efbb31900334e0c": "organic solvents", + "571cdcb85efbb31900334e0d": "Epoxides", + "571cdcb85efbb31900334e0e": "feeder materials", + "571cdcb85efbb31900334e0f": "Epoxides", + "571cdcb85efbb31900334e10": "organic solvents", + "571cde695efbb31900334e16": "phosphate", + "571cde695efbb31900334e17": "a few", + "571cde695efbb31900334e18": "carbohydrates", + "571cde695efbb31900334e19": "proteins", + "571cde695efbb31900334e1a": "bones", + "571ce3745efbb31900334e20": "pulmonary fibrosis", + "571ce3745efbb31900334e21": "permanent pulmonary fibrosis", + "571ce3745efbb31900334e22": "160 kPa", + "571ce3745efbb31900334e23": "seizures", + "571ce3745efbb31900334e24": "seizures", + "571ce5055efbb31900334e2a": "low total pressures used", + "571ce5055efbb31900334e2b": "30 kPa", + "571ce5055efbb31900334e2c": "1.4 times", + "571ce5055efbb31900334e2e": "no", + "571ce5055efbb31900334e2d": "O\n2 partial pressure", + "571ce6655efbb31900334e34": "at elevated partial pressures", + "571ce6655efbb31900334e35": "partial pressures more than 50 kilopascals", + "571ce6655efbb31900334e36": "50% oxygen composition at standard pressure", + "571ce6655efbb31900334e37": "mechanical ventilators", + "571ce6655efbb31900334e38": "30%\u201350% O\n2", + "5725b33f6a3fe71400b8952d": "October 1973", + "5725b33f6a3fe71400b8952e": "US$3 per barrel", + "5725b33f6a3fe71400b8952f": "1979", + "5725b33f6a3fe71400b89530": "shock", + "5725b33f6a3fe71400b89531": "Organization of Arab Petroleum Exporting Countries", + "5725b5a689a1e219009abd28": "to avoid being targeted by the boycott", + "5725b5a689a1e219009abd29": "multilateral negotiations", + "5725b5a689a1e219009abd2a": "January 18, 1974", + "5725b5a689a1e219009abd2b": "March 1974", + "5725b76389a1e219009abd4a": "August 15, 1971", + "5725b76389a1e219009abd4b": "rise and fall according to market demand", + "5725b76389a1e219009abd4c": "currency values would fluctuate unpredictably for a time, the industrialized nations increased their reserves", + "5725b76389a1e219009abd4d": "September 1971", + "5725b76389a1e219009abd4e": "oil producers' real income decreased", + "5725b92e38643c19005acbd3": "less than two percent per year", + "5725b92e38643c19005acbd4": "1971", + "5725b92e38643c19005acbd5": "1973\u20131974", + "5725b92e38643c19005acbd6": "the oil shock", + "5725bad5271a42140099d0bd": "October 6, 1973", + "5725bad5271a42140099d0be": "Iran", + "5725bad5271a42140099d0bf": "ten times more", + "5725bad5271a42140099d0c0": "Iran", + "5725bad5271a42140099d0c1": "\"Of course [the price of oil] is going to rise", + "5725bcb6271a42140099d0eb": "American aid to Israel", + "5725bcb6271a42140099d0ec": "October 16, 1973", + "5725bcb6271a42140099d0ed": "their economic and political objectives were met", + "5725bcb6271a42140099d0ee": "$2.2 billion", + "5725bcb6271a42140099d0ef": "principal hostile country", + "57261dab38643c19005ad037": "over 100 billion dollars", + "57261dab38643c19005ad038": "Al-Qaeda and the Taliban", + "57261dab38643c19005ad039": "Middle East", + "57261dab38643c19005ad03a": "higher oil prices and lower prices for their own export commodities, amid shrinking Western demand", + "57261dab38643c19005ad03b": "Wahhabism", + "57261f9f271a42140099d4a9": "distribution and price disruptions", + "57261f9f271a42140099d4aa": "the USSR", + "57261f9f271a42140099d4ab": "1973", + "57261f9f271a42140099d4ac": "Kissinger's dominance", + "5726241189a1e219009ac2de": "The embargo", + "5726241189a1e219009ac2df": "automobiles", + "5726241189a1e219009ac2e0": "Macroeconomic problems", + "5726241189a1e219009ac2e1": "the Arctic", + "5726241189a1e219009ac2e2": "five to ten years", + "5726487b5951b619008f6edd": "the Netherlands", + "5726487b5951b619008f6ede": "America", + "5726487b5951b619008f6edf": "The UK", + "5726487b5951b619008f6ee0": "Israelis", + "5726487b5951b619008f6ee1": "Ted Heath", + "572649d8f1498d1400e8db36": "the UK", + "572649d8f1498d1400e8db37": "a series of strikes by coal miners and railroad workers", + "572649d8f1498d1400e8db38": "1973\u201374", + "572649d8f1498d1400e8db39": "UK, Germany, Italy, Switzerland and Norway", + "572649d8f1498d1400e8db3a": "Sweden", + "57264cac708984140094c1b3": "Price controls", + "57264cac708984140094c1b4": "to encourage investment", + "57264cac708984140094c1b5": "creating greater scarcity", + "57264cac708984140094c1b7": "rationing", + "57264d9edd62a815002e80fe": "William E. Simon", + "57264d9edd62a815002e80ff": "1973", + "57264d9edd62a815002e8100": "to coordinate the response to the embargo", + "57264d9edd62a815002e8101": "20%", + "57264efddd62a815002e8134": "55 mph", + "57264efddd62a815002e8135": "Emergency Highway Energy Conservation Act", + "57264efddd62a815002e8136": "Bill Clinton", + "57264efddd62a815002e8137": "November 28, 1995", + "57264efddd62a815002e8138": "1977", + "572650325951b619008f6fa9": "The energy crisis", + "572650325951b619008f6faa": "market and technology realities", + "572650325951b619008f6fab": "congresses and presidents", + "57265200708984140094c237": "Soviet", + "57265200708984140094c238": "British", + "57265200708984140094c239": "10 years", + "57265200708984140094c23a": "the Arabs and much of the rest of the Third World", + "57265360dd62a815002e819a": "Japan", + "57265360dd62a815002e819b": "71%", + "57265360dd62a815002e819c": "declared Japan a \"nonfriendly\" country to encourage it to change its noninvolvement policy", + "57265360dd62a815002e819d": "November 22", + "57265360dd62a815002e819e": "December 25", + "57265526708984140094c2bd": "USSR", + "57265526708984140094c2be": "Saudi Arabia and Iran", + "57265526708984140094c2bf": "Saudi", + "57265526708984140094c2c0": "January 1979", + "57265526708984140094c2c1": "November 1979", + "5726581fdd62a815002e823a": "Toyota Corona, the Toyota Corolla, the Datsun B210, the Datsun 510", + "5726581fdd62a815002e823b": "Japanese", + "5726581fdd62a815002e823c": "four cylinder engines that were more fuel efficient than the typical American V8 and six cylinder", + "5726581fdd62a815002e823d": "Japanese", + "572659535951b619008f703f": "A decade after the 1973", + "572659535951b619008f7040": "Toyota Corona Mark II, the Toyota Cressida", + "572659535951b619008f7041": "passenger space and amenities such as air conditioning, power steering, AM-FM radios, and even power windows and central locking", + "572659535951b619008f7042": "Acura, Lexus and Infiniti", + "57265a58dd62a815002e8270": "Toyota Hilux and the Datsun Truck", + "57265a58dd62a815002e8271": "Dodge D-50", + "57265a58dd62a815002e8272": "Ford, Chrysler, and GM", + "57265a58dd62a815002e8273": "captive import", + "57265bdfdd62a815002e829e": "An increase in imported cars", + "57265bdfdd62a815002e829f": "at least four", + "57265bdfdd62a815002e82a0": "1985", + "57265bdfdd62a815002e82a1": "The Cadillac DeVille and Fleetwood, Buick Electra, Oldsmobile 98, Lincoln Continental, Mercury Marquis", + "57265bdfdd62a815002e82a2": "Chevrolet Bel Air, and Ford Galaxie 500", + "57265ceddd62a815002e82b8": "1979", + "57265ceddd62a815002e82b9": "1981", + "57265ceddd62a815002e82ba": "1974 Mustang I", + "57265e11708984140094c3bb": "1981", + "57265e11708984140094c3bc": "1980s", + "57265e11708984140094c3bd": "recover market share", + "57265e11708984140094c3be": "$40 per barrel", + "5725b41838643c19005acb7f": "Mercury", + "5725b41838643c19005acb80": "The Apollo program", + "5725b41838643c19005acb81": "1968", + "5725b41838643c19005acb82": "John F. Kennedy", + "5725b41838643c19005acb83": "three", + "5725b56589a1e219009abd20": "from 1961 to 1972", + "5725b56589a1e219009abd21": "Gemini missions", + "5725b56589a1e219009abd22": "Soviet Union", + "5725b56589a1e219009abd23": "Skylab", + "5725b64d89a1e219009abd40": "1967", + "5725b64d89a1e219009abd41": "oxygen tank", + "5725b64d89a1e219009abd42": "Budget cuts", + "5725b64d89a1e219009abd43": "Five", + "5725b64d89a1e219009abd44": "an oxygen tank explosion", + "5725b77889a1e219009abd54": "Apollo 8", + "5725b77889a1e219009abd55": "Apollo 17", + "5725b77889a1e219009abd56": "382", + "5725b77889a1e219009abd57": "avionics, telecommunications, and computers", + "5725b888ec44d21400f3d453": "three", + "5725b888ec44d21400f3d454": "three", + "5725b888ec44d21400f3d455": "Abe Silverstein", + "5725b888ec44d21400f3d457": "manned lunar landings", + "5725b888ec44d21400f3d456": "early 1960", + "5725ba5038643c19005acbe7": "1960", + "5725ba5038643c19005acbe8": "Maxime Faget", + "5725ba5038643c19005acbe9": "three", + "5725ba5038643c19005acbea": "Hugh L. Dryden", + "5725bb34271a42140099d0c7": "John F. Kennedy", + "5725bb34271a42140099d0c8": "Soviet Union", + "5725bb34271a42140099d0c9": "massive financial commitment required by a manned Moon landing", + "5725bb34271a42140099d0ca": "James E. Webb", + "5725bb34271a42140099d0cb": "missile gap", + "5725bc7138643c19005acc1d": "Yuri Gagarin", + "5725bc7138643c19005acc1e": "Soviet", + "5725bc7138643c19005acc1f": "one", + "5725bc7138643c19005acc20": "refusing to make a commitment", + "5725bd4b38643c19005acc31": "April 20", + "5725bd4b38643c19005acc32": "Lyndon B. Johnson", + "5725bd4b38643c19005acc33": "one week", + "5725bd4b38643c19005acc34": "we are neither making maximum effort nor achieving results necessary", + "5725be0fec44d21400f3d4a5": "Robert R. Gilruth", + "5725be0fec44d21400f3d4a6": "Langley Research Center", + "5725be0fec44d21400f3d4a7": "Houston, Texas", + "5725be0fec44d21400f3d4a8": "Rice University", + "5725be0fec44d21400f3d4a9": "Florida", + "5725bf2e89a1e219009abdce": "Merritt Island", + "5725bf2e89a1e219009abdcf": "Kurt H. Debus", + "5725bf2e89a1e219009abdd0": "the LOC's first Director", + "5725bf2e89a1e219009abdd1": "Kennedy", + "5725c01389a1e219009abdd7": "at least three", + "5725c01389a1e219009abdd8": "The Apollo spacecraft", + "5725c01389a1e219009abdd9": "250,000 feet", + "5725c01389a1e219009abdd6": "130 million cubic foot", + "5725c123271a42140099d131": "Dr. George E. Mueller", + "5725c123271a42140099d132": "July 23, 1963", + "5725c123271a42140099d133": "D. Brainerd Holmes", + "5725c123271a42140099d134": "Mueller", + "5725c2a038643c19005acc6b": "Air Force missile projects", + "5725c2a038643c19005acc6c": "United States Air Force", + "5725c2a038643c19005acc6d": "General Samuel C. Phillips", + "5725c2a038643c19005acc6e": "January 1964", + "5725c2a038643c19005acc6f": "Apollo Program Director", + "5725c4c289a1e219009abe44": "a rendezvous \u2014let alone a docking", + "5725c4c289a1e219009abe45": "1961", + "5725c4c289a1e219009abe46": "Robert Seamans", + "5725c604271a42140099d185": "Nicholas E. Golovin", + "5725c604271a42140099d186": "July 1961", + "5725c604271a42140099d187": "Manned Spacecraft Center", + "5725c604271a42140099d188": "Joseph Shea", + "5725c604271a42140099d189": "Marshall Space Flight Center", + "5725c6dcec44d21400f3d531": "Jerome Wiesner", + "5725c6dcec44d21400f3d532": "Golovin", + "5725c6dcec44d21400f3d533": "NASA", + "5725c6dcec44d21400f3d534": "July 11, 1962", + "5725c7f5271a42140099d1a1": "Wiesner", + "5725c7f5271a42140099d1a2": "No, that's no good", + "5725c7f5271a42140099d1a3": "Lunar Excursion Module", + "5725c7f5271a42140099d1a4": "Grumman", + "5725c948ec44d21400f3d577": "allowing the lander spacecraft to be used as a \"lifeboat", + "5725c948ec44d21400f3d578": "Apollo 13", + "5725c948ec44d21400f3d579": "propulsion, electrical power and life support", + "5725c948ec44d21400f3d57a": "1964", + "5725ca35271a42140099d1c1": "cone-shaped", + "5725ca35271a42140099d1c2": "Command/Service Module", + "5725ca35271a42140099d1c3": "two", + "5725cb4a89a1e219009abec8": "three", + "5725cb4a89a1e219009abec9": "lunar orbit and back to an Earth ocean landing", + "5725cb4a89a1e219009abeca": "ablative heat shield", + "5725cb4a89a1e219009abecb": "Parachutes", + "5725cb4a89a1e219009abecc": "5,560", + "5725cc2038643c19005acd1b": "A cylindrical Service Module", + "5725cc2038643c19005acd1c": "high-gain S-band", + "5725cc2038643c19005acd1d": "discarded", + "5725cc2038643c19005acd1e": "51,300", + "5725cc2038643c19005acd1f": "an orbital scientific instrument package", + "5725cda338643c19005acd3f": "North American Aviation", + "5725cda338643c19005acd40": "twice", + "5725cda338643c19005acd41": "1964", + "5725cda338643c19005acd42": "Saturn V", + "5725ceb989a1e219009abf0a": "two", + "5725ceb989a1e219009abf0b": "Not designed to fly through the Earth's atmosphere or return to Earth", + "5725ceb989a1e219009abf0d": "33,300 pounds", + "5725ceb989a1e219009abf0e": "over 3 days", + "5725d01989a1e219009abf28": "Wernher von Braun", + "5725d01989a1e219009abf29": "the Army", + "5725d01989a1e219009abf2b": "June 11, 1962", + "5725d0e3271a42140099d235": "dummy upper stages filled with water", + "5725d0e3271a42140099d236": "1964 and 1965", + "5725d0e3271a42140099d237": "Pegasus satellites", + "5725d0e3271a42140099d238": "the frequency and severity of micrometeorite impacts", + "5725d2ef271a42140099d255": "The Saturn IB", + "5725d2ef271a42140099d256": "200,000 lbf", + "5725d2ef271a42140099d257": "third", + "5725d2ef271a42140099d258": "40,000 pounds", + "5725d403ec44d21400f3d65b": "The three-stage Saturn V", + "5725d403ec44d21400f3d65c": "33", + "5725d403ec44d21400f3d65d": "three", + "5725d403ec44d21400f3d65e": "burned liquid hydrogen", + "5725d51589a1e219009abf6e": "Project Mercury and Gemini veterans", + "5725d51589a1e219009abf6f": "two", + "5725d51589a1e219009abf70": "Dr. Harrison Schmitt", + "5725d51589a1e219009abf71": "Apollo 17", + "5725d51589a1e219009abf72": "fly in space", + "5725d61038643c19005acdd3": "32", + "5725d61038643c19005acdd4": "Distinguished Service Medal", + "5725d61038643c19005acdd5": "1969", + "5725d61038643c19005acdd6": "discipline problems with the Flight Director's orders", + "5725d61038643c19005acdd7": "Apollo 8", + "5725d6cb38643c19005acde7": "1966", + "5725d6cb38643c19005acde8": "265.7 nautical miles", + "5725d6cb38643c19005acde9": "1,142.9", + "5725d6cb38643c19005acdea": "Service Module engine and the Command Module heat shield", + "5725d79e89a1e219009abf90": "a crew would fly the first Block II CSM and LM in a dual mission known as AS-207/208, or AS-278", + "5725d79e89a1e219009abf91": "Apollo spacesuit", + "5725d79e89a1e219009abf92": "visor", + "5725d79e89a1e219009abf93": "water-cooled", + "5725d79e89a1e219009abf94": "Lunar Module Pilot", + "5725d8a3271a42140099d28f": "Deke Slayton", + "5725d8a3271a42140099d290": "Gemini and Apollo", + "5725d8a3271a42140099d291": "1966", + "5725d8a3271a42140099d292": "Deke Slayton", + "5725d8a3271a42140099d293": "KC135", + "5725d94bec44d21400f3d69b": "canceled", + "5725d94bec44d21400f3d69c": "August 1967", + "5725d94bec44d21400f3d69d": "Saturn IB", + "5725d94bec44d21400f3d69e": "Apollo 1", + "5725da63ec44d21400f3d6ab": "George Mueller to appoint program director Samuel Phillips", + "5725da63ec44d21400f3d6ac": "tiger team", + "5725da63ec44d21400f3d6ad": "1967", + "5725da63ec44d21400f3d6ae": "George Mueller", + "5725db4aec44d21400f3d6bd": "altitude chamber", + "5725db4aec44d21400f3d6be": "Grissom, White, and Chaffee", + "5725db4aec44d21400f3d6bf": "a launch countdown", + "5725db4aec44d21400f3d6c0": "altitude chamber", + "5725dc1638643c19005ace01": "a strange odor", + "5725dc1638643c19005ace02": "January 27, 1967", + "5725dc1638643c19005ace03": "sealing of the hatch", + "5725dc1638643c19005ace04": "The astronauts were asphyxiated", + "5725dc1638643c19005ace05": "high pressure, 100% oxygen", + "5725dd1689a1e219009abfe2": "both houses of Congress", + "5725dd1689a1e219009abfe3": "deficiencies", + "5725dd1689a1e219009abfe4": "George Low", + "5725dd1689a1e219009abfe5": "immediately", + "5725de30ec44d21400f3d6ed": "nitrogen/oxygen mixture", + "5725de30ec44d21400f3d6ee": "flammable cabin and space suit", + "5725de30ec44d21400f3d6ef": "quick-release, outward opening door", + "5725de30ec44d21400f3d6f0": "discontinued the manned Block I program", + "5725de30ec44d21400f3d6f1": "Block II", + "5725df1838643c19005ace15": "unmanned Saturn V validation", + "5725df1838643c19005ace16": "successfully accomplished before the next ones could be performed", + "5725df1838643c19005ace17": "letters", + "5725e08389a1e219009ac010": "AS-501", + "5725e08389a1e219009ac011": "The capability of the Command Module's heat shield", + "5725e08389a1e219009ac012": "April 4, 1968", + "5725e08389a1e219009ac013": "a third unmanned test", + "5725e152271a42140099d2cd": "Apollo 5", + "5725e152271a42140099d2ce": "pad 37", + "5725e152271a42140099d2cf": "George Low", + "5725e152271a42140099d2d0": "successfully", + "5725e152271a42140099d2d1": "fire-in-the-hole\" test", + "5725e28f38643c19005ace23": "Saturn V", + "5725e28f38643c19005ace24": "Zond 5", + "5725e28f38643c19005ace25": "Christmas Eve", + "5725e28f38643c19005ace26": "deferring the D mission to the next mission", + "5725e28f38643c19005ace27": "animals", + "5725e36f89a1e219009ac038": "Gemini", + "5725e36f89a1e219009ac039": "July 1969", + "5725e36f89a1e219009ac03a": "black-and-white television", + "5725e36f89a1e219009ac03b": "Neil Armstrong, Michael Collins and Buzz Aldrin", + "5725e36f89a1e219009ac03c": "July 24", + "5725e44238643c19005ace35": "Apollo 12 within walking distance of the Surveyor 3", + "5725e44238643c19005ace36": "Surveyor 3", + "5725e44238643c19005ace37": "removed", + "5725e44238643c19005ace38": "accidentally pointed into the Sun", + "5725e547ec44d21400f3d71f": "Lunar Roving Vehicle", + "5725e547ec44d21400f3d720": "Block II spacesuit", + "5725e547ec44d21400f3d721": "eight", + "5725e547ec44d21400f3d722": "over three days", + "5725e547ec44d21400f3d723": "mass", + "5725e6f6ec44d21400f3d729": "a liquid oxygen tank exploded", + "5725e6f6ec44d21400f3d72a": "rookies", + "5725e6f6ec44d21400f3d72b": "grounded again", + "5725e6f6ec44d21400f3d72c": "oxygen tank", + "5725e6f6ec44d21400f3d72d": "April 1970", + "5725e95f89a1e219009ac086": "Apollo 20", + "5725e95f89a1e219009ac087": "shrink", + "5725e95f89a1e219009ac088": "The two unused Saturn Vs became museum exhibits", + "5725e95f89a1e219009ac089": "1971", + "5725ea6889a1e219009ac09e": "extremely old", + "5725ea6889a1e219009ac09f": "3.2 billion years", + "5725ea6889a1e219009ac0a0": "KREEP", + "5725ea6889a1e219009ac0a1": "Genesis Rock", + "5725eb8a38643c19005ace7f": "highly brecciated", + "5725eb8a38643c19005ace80": "impact process effects", + "5725eb8a38643c19005ace81": "materials melted near an impact crater", + "5725ec7538643c19005ace8f": "$170 billion", + "5725ec7538643c19005ace90": "15", + "5725ec7538643c19005ace91": "$20.4 billion", + "5725ee6438643c19005aceb3": "Apollo Extension Series", + "5725ee6438643c19005aceb4": "Apollo Applications Program", + "5725ee6438643c19005aceb5": "Venus", + "5725ef6838643c19005acece": "1973", + "5725ef6838643c19005acecf": "on the ground", + "5725ef6838643c19005aced0": "February 8, 1974", + "5725ef6838643c19005aced1": "Apollo Telescope Mount", + "5725f07f89a1e219009ac0be": "NASA's robotic Lunar Reconnaissance Orbiter", + "5725f07f89a1e219009ac0bf": "Apollo 11", + "5725f07f89a1e219009ac0c0": "unknown", + "5725f16f89a1e219009ac0cc": "Apollo 8", + "5725f16f89a1e219009ac0cd": "Book of Genesis", + "5725f16f89a1e219009ac0ce": "one-quarter", + "5725f16f89a1e219009ac0cf": "troubled", + "5725f239271a42140099d35d": "Apollo TV camera", + "5725f239271a42140099d35e": "incompatible", + "5725f239271a42140099d35f": "a magnetic tape shortage", + "5725f239271a42140099d360": "massive numbers of magnetic tapes", + "5725f239271a42140099d361": "Stan Lebar", + "5725f39638643c19005acef7": "Nafzger", + "5725f39638643c19005acef8": "without destroying historical legitimacy", + "5725f39638643c19005acef9": "kinescope", + "5725f39638643c19005acefa": "Lowry Digital", + "5725f39638643c19005acefb": "black and white", + "5725b7f389a1e219009abd5c": "primary law, secondary law and supplementary law", + "5725b7f389a1e219009abd5d": "a body of treaties and legislation", + "5725b7f389a1e219009abd5e": "Treaties establishing the European Union", + "5725b7f389a1e219009abd5f": "Treaties establishing the European Union", + "5725b7f389a1e219009abd60": "European Parliament and the Council of the European Union", + "5725c28a271a42140099d14d": "a body of treaties and legislation", + "5725c28a271a42140099d14e": "direct effect or indirect effect", + "5725c28a271a42140099d14f": "primary law, secondary law and supplementary law", + "5725c28a271a42140099d150": "European Parliament and the Council of the European Union", + "57268b43dd62a815002e88f0": "primary law, secondary law and supplementary law", + "57268b43dd62a815002e88f1": "Treaties establishing the European Union", + "57268b43dd62a815002e88f2": "European Parliament and the Council of the European Union", + "57268b43dd62a815002e88f3": "three", + "5725bbec271a42140099d0d1": "courts of member states and the Court of Justice of the European Union", + "5725bbec271a42140099d0d2": "courts of member states", + "5725bbec271a42140099d0d3": "Treaty on the Functioning of the European Union", + "5725bbec271a42140099d0d4": "The European Court of Justice", + "5725bbec271a42140099d0d5": "case law by the Court of Justice, international law and general principles of European Union law", + "5725c3a9ec44d21400f3d503": "courts of member states and the Court of Justice of the European Union", + "5725c3a9ec44d21400f3d504": "Treaty on the Functioning of the European Union", + "5725c3a9ec44d21400f3d505": "The European Court of Justice", + "5725c3a9ec44d21400f3d506": "case law by the Court of Justice", + "57268bf9dd62a815002e890a": "courts of member states and the Court of Justice of the European Union", + "57268bf9dd62a815002e890b": "courts of member states", + "57268bf9dd62a815002e890c": "The European Court of Justice", + "57268bf9dd62a815002e890d": "case law by the Court of Justice, international law and general principles of European Union law", + "5725c743ec44d21400f3d549": "the Treaty on European Union (TEU) and the Treaty on the Functioning of the European Union (TFEU)", + "5725c743ec44d21400f3d54a": "The European Commission", + "5725c743ec44d21400f3d54b": "citizens", + "5725c743ec44d21400f3d54c": "The European Court of Justice", + "5725c743ec44d21400f3d54d": "European Council", + "5725ca4389a1e219009abeb4": "The TEU", + "5725ca4389a1e219009abeb5": "Faroe Islands", + "5725ca4389a1e219009abeb6": "can interpret the Treaties, but it cannot rule on their validity", + "5725ca4389a1e219009abeb7": "if the Treaty provisions have a direct effect", + "5725ca4389a1e219009abeb8": "soon as they enter into force", + "57268d2ddd62a815002e894e": "Treaty on European Union (TEU) and the Treaty on the Functioning of the European Union (TFEU)", + "57268d2ddd62a815002e894f": "Gibraltar and the \u00c5land islands", + "57268d2ddd62a815002e8950": "as soon as they enter into force", + "57268d2ddd62a815002e8951": "Court of Justice of the European Union", + "5725cc38ec44d21400f3d5bb": "common rules for coal and steel", + "5725cc38ec44d21400f3d5bc": "Treaty of Rome 1957 and the Maastricht Treaty 1992", + "5725cc38ec44d21400f3d5bd": "1985", + "5725cc38ec44d21400f3d5be": "Norway did not end up joining", + "5725cc38ec44d21400f3d5bf": "Greenland", + "57268e2bf1498d1400e8e3b0": "common rules for coal and steel, and then atomic energy", + "57268e2bf1498d1400e8e3b1": "1992", + "57268e2bf1498d1400e8e3b2": "1986", + "57268e2bf1498d1400e8e3b3": "1972", + "57268e2bf1498d1400e8e3b4": "1985", + "57264865dd62a815002e8062": "Following the Nice Treaty", + "57264865dd62a815002e8063": "France and the referendum in the Netherlands", + "57264865dd62a815002e8064": "very similar", + "57264865dd62a815002e8065": "an amending treaty", + "57264865dd62a815002e8066": "it did not completely replace them", + "57268f2bf1498d1400e8e3c4": "constitutional law of the European Union", + "57268f2bf1498d1400e8e3c5": "make it more transparent", + "57268f2bf1498d1400e8e3c6": "the referendum in France and the referendum in the Netherlands", + "57268f2bf1498d1400e8e3c7": "Lisbon Treaty", + "57264a8cdd62a815002e808c": "The European Commission", + "57264a8cdd62a815002e808d": "The European Commission", + "57264a8cdd62a815002e808e": "The Commission's President", + "57264a8cdd62a815002e808f": "one", + "57264a8cdd62a815002e8090": "Federica Mogherini", + "572691545951b619008f76e1": "Article 17", + "572691545951b619008f76e2": "The Commission's President", + "572691545951b619008f76e3": "by a simple majority vote", + "572691545951b619008f76e4": "Ireland", + "572691545951b619008f76e5": "The Commissioners", + "57264e455951b619008f6f65": "Santer Commission", + "57264e455951b619008f6f66": "not break any law", + "57264e455951b619008f6f67": "a Committee of Independent Experts", + "57264e455951b619008f6f68": "European Council", + "57264e455951b619008f6f69": "The President of the Council and a Commissioner can sit in on ECB meetings, but do not have voting rights", + "5726926a5951b619008f7709": "1999", + "5726926a5951b619008f770a": "Commission v Edith Cresson", + "5726926a5951b619008f770b": "a Committee of Independent Experts", + "5726926a5951b619008f770c": "European Anti-fraud Office", + "5726926a5951b619008f770d": "2012", + "572651f9f1498d1400e8dbee": "European Parliament and the Council of the European Union", + "572651f9f1498d1400e8dbef": "initiate legislation against the Commission's wishes", + "572651f9f1498d1400e8dbf0": "every five years", + "572651f9f1498d1400e8dbf1": "two-thirds", + "572651f9f1498d1400e8dbf2": "Council of the European Union", + "5726938af1498d1400e8e446": "the Commission", + "5726938af1498d1400e8e447": "European Parliament and the Council of the European Union", + "5726938af1498d1400e8e448": "1979", + "5726938af1498d1400e8e449": "every five years", + "5726938af1498d1400e8e44a": "conservative European People's Party", + "5726545f708984140094c2a5": "different ministers of the member states", + "5726545f708984140094c2a6": "Donald Tusk", + "5726545f708984140094c2a7": "inversely", + "5726545f708984140094c2a8": "352", + "5726545f708984140094c2a9": "260", + "57269424dd62a815002e8a1e": "the Council", + "57269424dd62a815002e8a1f": "each six months", + "57269424dd62a815002e8a20": "352", + "57269424dd62a815002e8a21": "352 votes, but for most acts there must be a qualified majority vote, if not consensus", + "572656e4dd62a815002e81fa": "unanimity", + "572656e4dd62a815002e81fb": "qualified majority", + "572656e4dd62a815002e81fc": "harder", + "572656e4dd62a815002e81fd": "TEU articles 4 and 5", + "572656e4dd62a815002e81fe": "Court of Justice", + "572695285951b619008f774b": "294", + "572695285951b619008f774c": "a majority in Parliament", + "572695285951b619008f774d": "TEU articles 4 and 5", + "572695285951b619008f774e": "a \"Conciliation Committee", + "572658435951b619008f7025": "judicial", + "572658435951b619008f7026": "the Court of Justice of the European Union", + "572658435951b619008f7027": "28", + "572658435951b619008f7028": "member state courts", + "572658435951b619008f7029": "to \"ensure that in the interpretation and application of the Treaties the law is observed", + "5726965ef1498d1400e8e484": "by assuming the task of interpreting the treaties, and accelerating economic and political integration", + "5726965ef1498d1400e8e485": "the Court of Justice of the European Union", + "5726965ef1498d1400e8e486": "Civil Service Tribunal", + "5726965ef1498d1400e8e487": "three years", + "5726965ef1498d1400e8e488": "to \"ensure that in the interpretation and application of the Treaties the law is observed", + "57265e455951b619008f70bb": "EU law has primacy", + "57265e455951b619008f70bc": "nationalisation of the Italian energy corporations", + "57265e455951b619008f70bd": "1964 and 1968", + "5726975c708984140094cb1f": "European Court of Justice and the highest national courts", + "5726975c708984140094cb20": "1964", + "5726975c708984140094cb21": "the Court of Justice", + "572699db5951b619008f7799": "EU law takes primacy over national law where this agreed in the Treaties", + "572699db5951b619008f779a": "foundational constitutional questions affecting democracy and human rights", + "572699db5951b619008f779b": "1972", + "572699db5951b619008f779d": "the ultimate authority of member states", + "572699db5951b619008f779c": "democracy, the rule of law and the social state principles", + "57269aa65951b619008f77ab": "administrative law", + "57269aa65951b619008f77ac": "1986", + "57269aa65951b619008f77ad": "All actions", + "57269aa65951b619008f77ae": "constitutional law", + "57269bb8708984140094cb95": "Van Gend en Loos v Nederlandse Administratie der Belastingen", + "57269bb8708984140094cb96": "article 30", + "57269bb8708984140094cb97": "postal", + "57269bb8708984140094cb98": "Treaty provisions", + "57269cc3dd62a815002e8b12": "Directives", + "57269cc3dd62a815002e8b13": "4", + "57269cc3dd62a815002e8b14": "more than 28", + "57269cc3dd62a815002e8b15": "early 1990s", + "57269e3bf1498d1400e8e516": "the member state cannot enforce conflicting laws", + "57269e3bf1498d1400e8e517": "the member state cannot enforce conflicting laws", + "57269e3bf1498d1400e8e518": "10 years", + "57269e3bf1498d1400e8e519": "Swedex GmbH & Co KG", + "57269e3bf1498d1400e8e51a": "60", + "57269f3ef1498d1400e8e534": "national courts", + "57269f3ef1498d1400e8e535": "incorporations would only be nullified for a fixed list of reasons", + "57269f3ef1498d1400e8e536": "set up an insurance fund for employees to claim unpaid wages", + "57269f3ef1498d1400e8e537": "6 million Lira", + "5726a00cf1498d1400e8e550": "European Court of Justice", + "5726a00cf1498d1400e8e551": "fundamental rights (see human rights), proportionality, legal certainty, equality before the law and subsidiarity", + "5726a09f708984140094cc39": "since the 1950s", + "5726a09f708984140094cc3a": "Article 5", + "5726a09f708984140094cc3b": "the least onerous", + "5726a14c708984140094cc51": "since the 1960s", + "5726a14c708984140094cc52": "international law and public law", + "5726a14c708984140094cc53": "a proper legal basis", + "5726a14c708984140094cc54": "principles of legal certainty and good faith", + "5726a1e5dd62a815002e8b86": "constitutional traditions common to the member states", + "5726a1e5dd62a815002e8b87": "fundamental rights", + "5726a299dd62a815002e8b9e": "None", + "5726a299dd62a815002e8b9f": "member states", + "5726a299dd62a815002e8ba0": "1950", + "5726a299dd62a815002e8ba1": "European Court of Human Rights", + "5726a299dd62a815002e8ba2": "1999", + "5726a34bf1498d1400e8e59e": "2007", + "5726a34bf1498d1400e8e59f": "the Charter of Fundamental Rights of the European Union", + "5726a34bf1498d1400e8e5a0": "European Union law", + "5726a34bf1498d1400e8e5a1": "European Court of Justice", + "5726a3c6f1498d1400e8e5ae": "Treaty of Amsterdam", + "5726a3c6f1498d1400e8e5af": "1997", + "5726a3c6f1498d1400e8e5b0": "1989", + "5726a3c6f1498d1400e8e5b1": "30", + "5726a3c6f1498d1400e8e5b2": "40", + "5726a46cdd62a815002e8bd0": "11", + "5726a46cdd62a815002e8bd1": "The UK", + "5726a46cdd62a815002e8bd2": "Social Chapter", + "5726a46cdd62a815002e8bd3": "1992", + "5726a5525951b619008f78dd": "election of the UK Labour Party to government", + "5726a5525951b619008f78de": "1997", + "5726a5525951b619008f78df": "Works Council Directive", + "5726a5525951b619008f78e0": "1996", + "5726a5525951b619008f78e1": "workforce consultation in businesses", + "5726a638dd62a815002e8bf6": "France, Italy, Belgium, the Netherlands, Luxembourg and Germany", + "5726a638dd62a815002e8bf7": "1951", + "5726a638dd62a815002e8bf8": "cartels", + "5726a638dd62a815002e8bf9": "article 66", + "5726a638dd62a815002e8bfa": "1957", + "5726a7ecf1498d1400e8e654": "Article 101", + "5726a7ecf1498d1400e8e655": "abuse of dominant position", + "5726a7ecf1498d1400e8e656": "Articles 106 and 107", + "5726a7ecf1498d1400e8e657": "Article 102", + "5726b58f5951b619008f7b55": "2007", + "5726b58f5951b619008f7b56": "since the Treaty of Rome 1957", + "5726b58f5951b619008f7b57": "consumer prices", + "5726b58f5951b619008f7b58": "free trade", + "5726b58f5951b619008f7b59": "the Court of Justice", + "5726b718dd62a815002e8dbe": "a customs union", + "5726b718dd62a815002e8dbf": "parallel importers", + "5726b718dd62a815002e8dc0": "private actors", + "5726b718dd62a815002e8dc1": "Commission v France", + "5726b718dd62a815002e8dc2": "protest", + "5726b929f1498d1400e8e8e8": "25 per cent", + "5726b929f1498d1400e8e8e9": "France", + "5726b929f1498d1400e8e8ea": "2003", + "5726b929f1498d1400e8e8eb": "cocoa butter", + "5726b929f1498d1400e8e8ec": "motorcycles or mopeds pulling trailers", + "5726ba2c708984140094cf59": "Keck and Mithouard", + "5726ba2c708984140094cf5a": "prevent cut throat competition", + "5726ba2c708984140094cf5b": "Konsumentombudsmannen v De Agostini", + "5726ba2c708984140094cf5c": "Unfair Commercial Practices Directive", + "5726baf2dd62a815002e8e74": "people to pursue their life goals in any country through free movement", + "5726baf2dd62a815002e8e75": "the European Community", + "5726baf2dd62a815002e8e76": "citizenship", + "5726baf2dd62a815002e8e77": "Steymann v Staatssecretaris van Justitie", + "5726baf2dd62a815002e8e78": "stay", + "5726bc1add62a815002e8ea6": "1 to 7", + "5726bc1add62a815002e8ea7": "Jean-Marc Bosman", + "5726bc1add62a815002e8ea8": "Gaelic", + "5726bc1add62a815002e8ea9": "Hendrix v Employee Insurance Institute", + "5726bc1add62a815002e8eaa": "between 3 and 14", + "5726bcde708984140094cfbf": "Citizenship of the EU", + "5726bcde708984140094cfc0": "the number of social services that people can access wherever they move", + "5726bcde708984140094cfc1": "Commission v Austria", + "5726bcde708984140094cfc2": "higher education", + "5726c002708984140094d073": "the Treaty on the Functioning of the European Union", + "5726c002708984140094d074": "if they were non-discriminatory", + "5726c002708984140094d075": "Reyners v Belgium", + "5726c002708984140094d076": "TFEU article 49", + "5726c002708984140094d077": "Commission v Italy", + "5726c19add62a815002e8f8a": "2006", + "5726c19add62a815002e8f8b": "shipping toxic waste", + "5726c19add62a815002e8f8c": "October 2007", + "5726c19add62a815002e8f8d": "2005", + "5726c3da708984140094d0d9": "German health clinic", + "5726c3da708984140094d0da": "because Dutch law said only people established in the Netherlands could give legal advice", + "5726c3da708984140094d0db": "narcotic drugs", + "5726c3da708984140094d0dc": "treatment", + "5726c5a9f1498d1400e8eac4": "Daily Mail", + "5726c5a9f1498d1400e8eac5": "\u00a31 of capital", + "5726c5a9f1498d1400e8eac6": "\u00a31", + "5726c5a9f1498d1400e8eac7": "Denmark's minimum capital law", + "5726c5a9f1498d1400e8eac8": "\u00dcberseering BV v Nordic Construction GmbH", + "5725b81b271a42140099d097": "Amazonia or the Amazon Jungle", + "5725b81b271a42140099d098": "5,500,000", + "5725b81b271a42140099d099": "nine", + "5725b81b271a42140099d09a": "four", + "5725b81b271a42140099d09b": "over half", + "5728349dff5b5019007d9efe": "Amazoneregenwoud", + "5728349dff5b5019007d9eff": "The Amazon rainforest", + "5728349dff5b5019007d9f00": "Brazil", + "5728349dff5b5019007d9f01": "over half", + "5728349dff5b5019007d9f02": "16,000", + "5729e2316aef0514001550c4": "moist broadleaf", + "5729e2316aef0514001550c5": "7,000,000", + "5729e2316aef0514001550c6": "nine", + "5729e2316aef0514001550c7": "Brazil", + "5729e2316aef0514001550c8": "390 billion", + "5725be0f271a42140099d117": "wetter", + "5725be0f271a42140099d118": "Climate fluctuations", + "5725be0f271a42140099d119": "Oligocene", + "5725be0f271a42140099d11a": "last glacial maximum", + "5725be0f271a42140099d11b": "the rainforest still managed to thrive", + "57283adcff5b5019007d9f94": "the extinction of the dinosaurs and the wetter climate", + "57283adcff5b5019007d9f95": "45\u00b0", + "57283adcff5b5019007d9f96": "Climate fluctuations", + "57283adcff5b5019007d9f97": "Oligocene", + "57283adcff5b5019007d9f98": "expanded", + "5729e500af94a219006aa6b5": "Cretaceous\u2013Paleogene extinction event", + "5729e500af94a219006aa6b6": "66\u201334 Mya", + "5729e500af94a219006aa6b7": "Middle Miocene", + "5729e500af94a219006aa6b8": "last glacial maximum", + "5729e500af94a219006aa6b9": "34 million", + "5725c071271a42140099d127": "mid-Eocene", + "5725c071271a42140099d128": "toward the Atlantic", + "5725c071271a42140099d129": "Solim\u00f5es Basin", + "5725c071271a42140099d12a": "5\u201310 million years", + "5725c071271a42140099d12b": "the Atlantic", + "57283d173acd2414000df78f": "mid-Eocene", + "57283d173acd2414000df790": "the Pacific", + "57283d173acd2414000df791": "the Pacific", + "57283d173acd2414000df792": "Amazonas Basin", + "57283d173acd2414000df793": "Solim\u00f5es Basin", + "5729e6313f37b319004785a9": "mid-Eocene", + "5729e6313f37b319004785aa": "along the middle", + "5729e6313f37b319004785ab": "the Atlantic", + "5729e6313f37b319004785ac": "the Pacific", + "5729e6313f37b319004785ad": "Solim\u00f5es Basin", + "5725c41eec44d21400f3d50b": "Last Glacial Maximum", + "5725c41eec44d21400f3d50c": "that rainfall in the basin during the LGM was lower than for the present", + "5725c41eec44d21400f3d50d": "the rainforest was reduced to small, isolated refugia separated by open forest and grassland", + "5725c41eec44d21400f3d50e": "difficult to resolve", + "5725c41eec44d21400f3d50f": "reasonably well supported by the available data", + "572841772ca10214002da1a6": "21,000 years", + "572841772ca10214002da1a7": "Last Glacial Maximum (LGM) and subsequent deglaciation", + "572841772ca10214002da1a8": "sediment deposits", + "572841772ca10214002da1a9": "reduced moist tropical vegetation cover", + "572a0bfaaf94a219006aa779": "21,000 years", + "572a0bfaaf94a219006aa77a": "sediment", + "572a0bfaaf94a219006aa77b": "moist tropical", + "572a0bfaaf94a219006aa77c": "open forest and grassland", + "572a0bfaaf94a219006aa77d": "practical limitations of working in the rainforest mean that data sampling is biased away from the center of the Amazon basin", + "5725c63438643c19005acc9f": "CALIPSO satellite", + "5725c63438643c19005acca0": "182 million", + "5725c63438643c19005acca1": "1,600", + "5725c63438643c19005acca2": "Amazon basin", + "5725c63438643c19005acca3": "132 million", + "5728455bff5b5019007da078": "CALIPSO satellite", + "5728455bff5b5019007da079": "182 million tons", + "5728455bff5b5019007da07a": "27.7 million tons", + "5728455bff5b5019007da07b": "132 million tons", + "5728455bff5b5019007da07c": "43 million tons", + "5729ea263f37b319004785bd": "CALIPSO satellite", + "5729ea263f37b319004785be": "NASA", + "5729ea263f37b319004785bf": "182 million tons", + "5729ea263f37b319004785c0": "1,600", + "5729ea263f37b319004785c1": "27.7 million", + "5725c95f38643c19005accf3": "Amazonia: Man and Culture in a Counterfeit Paradise", + "5725c95f38643c19005accf4": "0.2 inhabitants per square kilometre", + "5725c95f38643c19005accf5": "agriculture", + "5725c95f38643c19005accf6": "recent anthropological", + "5725c95f38643c19005accf7": "5 million", + "572847dd4b864d19001648bc": "agriculture given the poor soil", + "572847dd4b864d19001648bd": "Betty Meggers", + "572847dd4b864d19001648be": "0.2", + "572847dd4b864d19001648bf": "Amazonia: Man and Culture in a Counterfeit Paradise", + "5729eb34af94a219006aa6c9": "Betty Meggers", + "5729eb34af94a219006aa6ca": "Amazonia: Man and Culture in a Counterfeit Paradise", + "5729eb34af94a219006aa6cb": "0.2", + "5729eb34af94a219006aa6cc": "5 million", + "5729eb34af94a219006aa6cd": "less than 200,000", + "5725cbb289a1e219009abed2": "Francisco de Orellana", + "5725cbb289a1e219009abed3": "1540s", + "5725cbb289a1e219009abed4": "smallpox", + "5725cbb289a1e219009abed5": "between AD 0\u20131250", + "5725cbb289a1e219009abed6": "AD 0\u20131250", + "5729edd56aef051400155112": "Francisco de Orellana", + "5729edd56aef051400155113": "1542", + "5729edd56aef051400155114": "AD 0\u20131250", + "5729edd56aef051400155115": "Ondemar Dias", + "5729edd56aef051400155116": "11,000", + "5725cf3238643c19005acd61": "black earth", + "5725cf3238643c19005acd62": "large areas", + "5725cf3238643c19005acd63": "agriculture and silviculture", + "5725cf3238643c19005acd64": "Xingu", + "5725cf3238643c19005acd65": "Michael Heckenberger", + "5729ef266aef05140015511c": "Terra preta", + "5729ef266aef05140015511d": "agriculture and silviculture", + "5729ef266aef05140015511e": "Xingu", + "5729ef266aef05140015511f": "Michael Heckenberger", + "5729ef266aef051400155120": "roads, bridges and large plazas", + "5725d16aec44d21400f3d61b": "2.5 million", + "5725d16aec44d21400f3d61c": "One in five", + "5725d16aec44d21400f3d61d": "40,000", + "5725d16aec44d21400f3d61e": "2,200", + "5725d16aec44d21400f3d61f": "128,843", + "5729f0db6aef051400155126": "2.5 million", + "5729f0db6aef051400155127": "2,000 birds and mammals. To date, at least 40,000 plant species, 2,200 fishes, 1,294 birds, 427", + "5729f0db6aef051400155128": "40,000", + "5729f0db6aef051400155129": "378", + "5729f0db6aef05140015512a": "One in five", + "5726722bdd62a815002e8528": "62", + "5726722bdd62a815002e8529": "16,000", + "5726722bdd62a815002e852a": "90,790", + "5726722bdd62a815002e852b": "356 \u00b1 47 tonnes per hectare", + "5726722bdd62a815002e852c": "438,000", + "5729f2646aef051400155130": "highest", + "5729f2646aef051400155131": "more than 1,100", + "5729f2646aef051400155132": "90,790", + "5729f2646aef051400155133": "356 \u00b1 47 tonnes", + "5729f2646aef051400155134": "438,000", + "5729f3831d0469140077967b": "electric eels", + "5729f3831d0469140077967c": "black caiman", + "5729f3831d0469140077967d": "piranha", + "5729f3831d0469140077967e": "lipophilic alkaloid toxins", + "5729f3831d0469140077967f": "Vampire bats", + "5729fd56af94a219006aa72f": "Deforestation", + "5729fd56af94a219006aa730": "early 1960s", + "5729fd56af94a219006aa731": "slash and burn", + "5729fd56af94a219006aa732": "loss of soil fertility and weed invasion", + "5729fd56af94a219006aa733": "areas cleared of forest", + "5729feaf6aef051400155188": "587,000", + "5729feaf6aef051400155189": "587,000", + "5729feaf6aef05140015518a": "pasture for cattle", + "5729feaf6aef05140015518b": "second-largest", + "5729feaf6aef05140015518c": "91%", + "572a005f1d046914007796b7": "soy", + "572a005f1d046914007796b8": "increased settlement and deforestation", + "572a005f1d046914007796b9": "8,646", + "572a005f1d046914007796bb": "declined", + "572a005f1d046914007796ba": "18%", + "572a020f6aef051400155198": "biodiversity", + "572a020f6aef051400155199": "destruction of the forest", + "572a020f6aef05140015519a": "loss of biodiversity", + "572a020f6aef05140015519b": "1.1 \u00d7 1011 metric tonnes", + "572a020f6aef05140015519c": "1.1 \u00d7 1011", + "572a03a06aef0514001551aa": "severely reduced rainfall and increased temperatures", + "572a03a06aef0514001551ab": "greenhouse gas", + "572a03a06aef0514001551ac": "2100", + "572a03a06aef0514001551ad": "though the 21st century", + "572a03a06aef0514001551ae": "deforestation", + "572a064a3f37b3190047865d": "indigenous territories", + "572a064a3f37b3190047865e": "community-based", + "572a064a3f37b3190047865f": "deforestation and ecocide", + "572a064a3f37b31900478660": "Urarina", + "572a064a3f37b31900478661": "non-human primates", + "572a07c11d046914007796d5": "remote sensing", + "572a07c11d046914007796d6": "Trio Tribe", + "572a07c11d046914007796d7": "southern Suriname", + "572a07c11d046914007796d8": "map out their ancestral lands to help strengthen their territorial claims", + "572a07c11d046914007796d9": "to protect their tribal lands from commercial interests", + "572a09abaf94a219006aa75b": "tree growth stages", + "572a09abaf94a219006aa75c": "carbon related", + "572a09abaf94a219006aa75d": "Tatiana Kuplich", + "572a09abaf94a219006aa75e": "2006", + "572a09abaf94a219006aa75f": "Synthetic aperture", + "572a0b101d046914007796e9": "2005", + "572a0b101d046914007796eb": "Brazilian National Institute of Amazonian Research", + "572a0b101d046914007796ec": "deforestation", + "572a0b101d046914007796ed": "savanna or desert", + "572a0b101d046914007796ea": "Woods Hole Research Center", + "572a0bebaf94a219006aa76f": "2010", + "572a0bebaf94a219006aa770": "1,160,000", + "572a0bebaf94a219006aa771": "three", + "572a0bebaf94a219006aa772": "2005", + "572a0bebaf94a219006aa773": "1.5 gigatons", + "5725b9db38643c19005acbe1": "comb jellies", + "5725b9db38643c19005acbe2": "marine waters worldwide", + "5725b9db38643c19005acbe3": "1.5 m (4 ft 11 in)", + "5725c0f289a1e219009abdf2": "a phylum of animals that live in marine waters worldwide", + "5725c0f289a1e219009abdf3": "combs", + "5725c0f289a1e219009abdf4": "water flow through the body cavity", + "5725c0f289a1e219009abdf5": "1.5 m (4 ft 11 in)", + "5725c0f289a1e219009abdf6": "the \u2018combs", + "57263eaa38643c19005ad371": "comb jellies", + "57263eaa38643c19005ad372": "1.5 m (4 ft 11 in)", + "57263eaa38643c19005ad373": "water flow through the body cavity", + "57263eaa38643c19005ad374": "a phylum of animals that live in marine waters worldwide", + "57263eaa38643c19005ad375": "marine waters worldwide", + "5725bae289a1e219009abd90": "ten times their own weight", + "5725bae289a1e219009abd91": "100\u2013150", + "5725bae289a1e219009abd92": "25", + "5725c337271a42140099d163": "100\u2013150", + "5725c337271a42140099d164": "tentilla", + "5725c337271a42140099d165": "ten times their own weight", + "5725c337271a42140099d166": "tentacles", + "5725c337271a42140099d167": "large, stiffened cilia", + "5726400589a1e219009ac5ee": "ten times their own weight", + "5726400589a1e219009ac5ef": "tentilla", + "5726400589a1e219009ac5f0": "large, stiffened cilia", + "5726400589a1e219009ac5f1": "egg-shaped bodies", + "5726400589a1e219009ac5f2": "100\u2013150", + "5725bc0338643c19005acc11": "hermaphrodites", + "5725bc0338643c19005acc12": "miniature cydippids", + "5725bc0338643c19005acc13": "In at least some species, juveniles are capable of reproduction before reaching the adult size and shape", + "5725c57a89a1e219009abe5e": "a single animal can produce both eggs and sperm, meaning it can fertilize its own egg, not needing a mate", + "5725c57a89a1e219009abe5f": "produce both eggs and sperm", + "5725c57a89a1e219009abe60": "sequential", + "5725c57a89a1e219009abe61": "platyctenids", + "5725c57a89a1e219009abe62": "hermaphroditism and early reproduction", + "5726415bec44d21400f3dcd1": "a single animal can produce both eggs and sperm", + "5726415bec44d21400f3dcd2": "can produce both eggs and sperm", + "5726415bec44d21400f3dcd3": "the eggs and sperm mature at different times", + "5726415bec44d21400f3dcd4": "platyctenids", + "5726415bec44d21400f3dcd5": "beroids", + "5725bdbe38643c19005acc39": "Black Sea", + "5725bdbe38643c19005acc3a": "Mnemiopsis", + "5725bdbe38643c19005acc3b": "over-fishing and long-term environmental changes", + "5725c69738643c19005accb9": "ctenophores", + "5725c69738643c19005accba": "Mnemiopsis", + "5725c69738643c19005accbb": "fish larvae", + "5725c69738643c19005accbc": "bays", + "5726431d271a42140099d7f5": "bays", + "5726431d271a42140099d7f6": "planktonic plants", + "5726431d271a42140099d7f7": "Mnemiopsis", + "5726431d271a42140099d7f8": "causing fish stocks to collapse", + "5726431d271a42140099d7f9": "over-fishing and long-term environmental changes that promoted the growth of the Mnemiopsis population. The later accidental introduction of Beroe", + "5725c91e38643c19005acceb": "66 million years ago", + "5725c91e38643c19005accec": "monophyletic", + "5725c91e38643c19005acced": "515 million years ago", + "5725c91e38643c19005accee": "no tentacles but many more comb-rows", + "5726449f1125e71900ae1928": "515 million years ago", + "5726449f1125e71900ae1929": "Cretaceous\u2013Paleogene extinction event", + "5726449f1125e71900ae192a": "monophyletic", + "5726449f1125e71900ae192b": "no tentacles but many more comb-rows", + "5725cb33271a42140099d1db": "cnidarians", + "5725cb33271a42140099d1dc": "colloblasts", + "5725cb33271a42140099d1dd": "bilaterians", + "5725cb33271a42140099d1de": "Ctenophores", + "5725cb33271a42140099d1df": "colloblasts", + "572646655951b619008f6ebf": "cnidarians", + "572646655951b619008f6ec0": "colloblasts", + "572646655951b619008f6ec1": "colloblasts", + "572646655951b619008f6ec2": "ctenophores and cnidarians", + "572646655951b619008f6ec3": "bilaterians", + "572647d0708984140094c14b": "mesoglea", + "572647d0708984140094c14c": "diploblastic", + "572647d0708984140094c14d": "ctenophores", + "572647d0708984140094c14e": "sponges", + "572648e8dd62a815002e8076": "cilia", + "572648e8dd62a815002e8077": "main method of locomotion", + "572648e8dd62a815002e8078": "ctenes", + "572648e8dd62a815002e8079": "comb-bearing", + "57264a0ef1498d1400e8db40": "Pleurobrachia", + "57264a0ef1498d1400e8db41": "oceanic species", + "57264a0ef1498d1400e8db42": "to withstand waves and swirling sediment particles", + "57264a0ef1498d1400e8db43": "Pleurobrachia, Beroe and Mnemiopsis", + "57264b1ddd62a815002e80a0": "an epithelium, the gastrodermis", + "57264b1ddd62a815002e80a1": "bioluminescence", + "57264b1ddd62a815002e80a2": "pharynx", + "57264b1ddd62a815002e80a3": "a mouth that can usually be closed by muscles", + "57264b1ddd62a815002e80a4": "the mouth and pharynx", + "57264cfa708984140094c1c3": "swimming-plates", + "57264cfa708984140094c1c4": "ctenes", + "57264cfa708984140094c1c5": "where the extra compact filament is suspected to have a supporting function", + "57264cfa708984140094c1c6": "in the direction in which the mouth is pointing", + "57264cfa708984140094c1c7": "2 millimeters", + "57264e66dd62a815002e811a": "osmotic pressure", + "57264e66dd62a815002e811b": "the mesoglea", + "57264e66dd62a815002e811c": "reduce its volume and increase its density", + "57264e66dd62a815002e811d": "pump water out of the mesoglea", + "572655e5f1498d1400e8dc5e": "aboral organ", + "572655e5f1498d1400e8dc5f": "at the opposite end from the mouth", + "572655e5f1498d1400e8dc60": "a transparent dome", + "572655e5f1498d1400e8dc61": "statocyst", + "572655e5f1498d1400e8dc62": "a balance sensor", + "57265746dd62a815002e8218": "sea gooseberry", + "57265746dd62a815002e8219": "a pair of long, slender tentacles", + "57265746dd62a815002e821a": "nearly spherical", + "57265746dd62a815002e821b": "a sheath", + "57265746dd62a815002e821c": "narrow end", + "572658daf1498d1400e8dcac": "tentilla", + "572658daf1498d1400e8dcad": "specialized mushroom-shaped cells in the outer layer of the epidermis", + "572658daf1498d1400e8dcae": "they contain striated muscle", + "572658daf1498d1400e8dcaf": "three", + "572658daf1498d1400e8dcb0": "capturing prey", + "572659ea5951b619008f7051": "eight", + "572659ea5951b619008f7052": "near the mouth to the opposite end", + "572659ea5951b619008f7053": "evenly round the body", + "572659ea5951b619008f7054": "a ciliary groove", + "57265aaf5951b619008f706b": "lobes", + "57265aaf5951b619008f706c": "gelatinous projections edged with cilia", + "57265aaf5951b619008f706d": "four", + "57265aaf5951b619008f706e": "help direct microscopic prey toward the mouth", + "57265aaf5951b619008f706f": "suspended planktonic prey", + "57265c10f1498d1400e8dd36": "clapping their lobes", + "57265c10f1498d1400e8dd37": "escape from danger", + "57265c10f1498d1400e8dd38": "nerves", + "57265c10f1498d1400e8dd39": "nerves", + "57265d86f1498d1400e8dd50": "Nuda", + "57265d86f1498d1400e8dd51": "The Beroida", + "57265d86f1498d1400e8dd52": "\"zip\" the mouth shut when the animal is not feeding", + "57265d86f1498d1400e8dd53": "tight closure", + "57265d86f1498d1400e8dd54": "their large pharynx", + "57265e97708984140094c3c3": "The Cestida", + "57265e97708984140094c3c6": "Cestum veneris", + "57265e97708984140094c3c4": "belt animals", + "57265e97708984140094c3c5": "by undulating their bodies as well as by the beating of their comb-rows", + "57265e97708984140094c3c7": "Velamen parallelum", + "572681c1dd62a815002e8796": "a pair of tentilla-bearing tentacles", + "572681c1dd62a815002e8797": "a muscular \"foot", + "572681c1dd62a815002e8798": "comb-rows", + "572681c1dd62a815002e8799": "on rocks, algae, or the body surfaces of other invertebrates", + "572683075951b619008f7513": "via pores in the epidermis", + "572683075951b619008f7514": "internal fertilization", + "572683075951b619008f7515": "Mnemiopsis", + "572683075951b619008f7516": "in the parts of the internal canal network under the comb rows", + "572683075951b619008f7517": "external", + "572684365951b619008f753f": "tentacles and tentacle sheaths", + "572684365951b619008f7540": "among the plankton", + "572684365951b619008f7541": "after dropping to the sea-floor", + "572684365951b619008f7542": "true larvae", + "572684365951b619008f7543": "Beroe", + "572686fc708984140094c8e5": "secretions", + "572686fc708984140094c8e6": "disturbed", + "572686fc708984140094c8e7": "ink", + "572686fc708984140094c8e8": "Juveniles", + "5726887e708984140094c917": "no vegetarians and only one genus that is partly parasitic", + "5726887e708984140094c918": "jellyfish", + "5726887e708984140094c919": "incorporate their prey's nematocysts (stinging cells) into their own tentacles", + "5726887e708984140094c91a": "smaller, weaker swimmers", + "5726887e708984140094c91b": "Lampea", + "57268a37f1498d1400e8e33c": "low ratio of organic matter to salt and water", + "57268a37f1498d1400e8e33d": "keta", + "57268a37f1498d1400e8e33e": "other ctenophores", + "57268a37f1498d1400e8e33f": "during blooms in the Red Sea", + "57268a37f1498d1400e8e340": "ctenophores", + "57268c01dd62a815002e8912": "the Western Atlantic ctenophore Mnemiopsis leidyi", + "57268c01dd62a815002e8913": "via the ballast tanks of ships", + "57268c01dd62a815002e8915": "by the accidental introduction of the Mnemiopsis-eating North American ctenophore Beroe ovata", + "57268c01dd62a815002e8914": "late 1980s", + "57268c01dd62a815002e8916": "slowed the animal's metabolism", + "57268da7f1498d1400e8e39c": "soft, gelatinous bodies", + "57268da7f1498d1400e8e39d": "a comb jelly", + "57268da7f1498d1400e8e39e": "mid-Cambrian period", + "57268da7f1498d1400e8e39f": "Three", + "57268da7f1498d1400e8e3a0": "tentacles", + "57268f05dd62a815002e8990": "515 million years ago", + "57268f05dd62a815002e8991": "sessile frond-like fossil Stromatoveris", + "57268f05dd62a815002e8992": "Stromatoveris", + "57268f05dd62a815002e8993": "sessile frond-like fossil Stromatoveris", + "57268f05dd62a815002e8994": "Ediacaran period", + "57269016708984140094ca41": "Bilateria", + "57269016708984140094ca42": "Porifera", + "572691bedd62a815002e89dc": "beroids", + "572691bedd62a815002e89dd": "monophyletic", + "572691bedd62a815002e89de": "65.5 million years ago", + "572691bedd62a815002e89df": "Richard Harbison", + "5725ce4d38643c19005acd4d": "Fresno", + "5725ce4d38643c19005acd4e": "220 miles", + "5725ce4d38643c19005acd4f": "ash tree", + "5725ce4d38643c19005acd50": "ash leaf", + "5725ce4d38643c19005acd51": "ash tree", + "5725cfd0271a42140099d225": "1872", + "5725cfd0271a42140099d226": "flooding", + "5725cfd0271a42140099d227": "1885", + "5725cfd0271a42140099d228": "47", + "5725cfd0271a42140099d229": "the Central Pacific Railroad", + "5725d183271a42140099d23d": "2.7%", + "5725d183271a42140099d23e": "Chinatown", + "5725d183271a42140099d23f": "Pinedale, in what is now North Fresno, was the site of the Pinedale Assembly Center", + "5725d183271a42140099d240": "an interim facility for the relocation of Fresno area Japanese Americans to internment camps", + "5725d183271a42140099d241": "assembly center", + "5725d34aec44d21400f3d639": "BankAmericard", + "5725d34aec44d21400f3d63a": "BankAmericard", + "5725d34aec44d21400f3d63b": "revolve a balance", + "5725d34aec44d21400f3d63c": "1976", + "5725d34aec44d21400f3d63d": "Visa Inc", + "5725d42a89a1e219009abf58": "Bill Aken", + "5725d42a89a1e219009abf59": "Bob Gallion", + "5725d42a89a1e219009abf5a": "Madera", + "5725d42a89a1e219009abf5b": "old country-western show at The Fresno Barn", + "5725d42a89a1e219009abf5c": "Lupe Mayorga", + "5725d662ec44d21400f3d687": "three", + "5725d662ec44d21400f3d688": "Roeding Park", + "5725d662ec44d21400f3d689": "Kearney Park", + "5725d662ec44d21400f3d68a": "Woodward Park", + "5725d662ec44d21400f3d68b": "Kearney Park", + "5725d7e438643c19005acdf9": "1880s and World War II", + "5725d7e438643c19005acdfa": "Fresno County Courthouse (demolished), the Fresno Carnegie Public Library", + "5725d7e438643c19005acdfb": "San Joaquin Light & Power Building", + "5725d7e438643c19005acdfc": "Hughes Hotel", + "5725daa8ec44d21400f3d6b3": "1964", + "5725daa8ec44d21400f3d6b4": "Fulton Mall", + "5725daa8ec44d21400f3d6b5": "Pierre-Auguste Renoir", + "5725daa8ec44d21400f3d6b6": "near their current locations", + "5725daa8ec44d21400f3d6b7": "wide sidewalks", + "5725db98ec44d21400f3d6c5": "far southeast side", + "5725db98ec44d21400f3d6c6": "Kings Canyon Avenue and Clovis Avenue", + "5725db98ec44d21400f3d6c7": "1950s", + "5725db98ec44d21400f3d6c8": "Sunnyside", + "5725db98ec44d21400f3d6c9": "William P. Bell", + "5725dd7d89a1e219009abfea": "Tower Theatre", + "5725dd7d89a1e219009abfeb": "1939", + "5725dd7d89a1e219009abfec": "water tower", + "5725dd7d89a1e219009abfed": "Fresno Normal School", + "5725dd7d89a1e219009abfee": "one-half mile south", + "5725e1c4271a42140099d2d7": "late 1970s", + "5725e1c4271a42140099d2d8": "second and third run movies", + "5725e1c4271a42140099d2d9": "1978", + "5725e1c4271a42140099d2da": "Fresno", + "5725e1c4271a42140099d2db": "Evita and The Wiz", + "5725e45689a1e219009ac048": "live", + "5725e45689a1e219009ac049": "a few hundred feet", + "5725e45689a1e219009ac04a": "the Tower District", + "5725e45689a1e219009ac04b": "the Tower District", + "5725e45689a1e219009ac04c": "Tower District", + "5725e748ec44d21400f3d733": "early twentieth century homes", + "5725e748ec44d21400f3d734": "Storybook houses", + "5725e748ec44d21400f3d735": "contrasts", + "5725e748ec44d21400f3d736": "recent decades", + "5725ec8289a1e219009ac0ae": "Huntington Boulevard", + "5725ec8289a1e219009ac0af": "William Stranahan", + "5725ec8289a1e219009ac0b0": "1914", + "5725ec8289a1e219009ac0b1": "267", + "5725ec8289a1e219009ac0b2": "Fresno Traction Company", + "5725edfe38643c19005ace9f": "Southwest Fresno", + "5725edfe38643c19005acea0": "southwest", + "5725edfe38643c19005acea1": "African-American", + "5725edfe38643c19005acea2": "Hmong or Laotian", + "5725edfe38643c19005acea3": "Fresno", + "5725f00938643c19005aced7": "M. Theo Kearney", + "5725f00938643c19005aced8": "tall palm trees", + "5725f00938643c19005aced9": "Fresno Street and Thorne Ave", + "5725f00938643c19005aceda": "Brookhaven", + "5725f00938643c19005acedb": "Dogg Pound", + "5725f190ec44d21400f3d76f": "between the 1960s and 1990s", + "5725f190ec44d21400f3d770": "Fresno and B streets", + "5725f190ec44d21400f3d771": "Cargill Meat Solutions and Foster Farms", + "5725f190ec44d21400f3d772": "Fresno Chandler Executive Airport is also on the West Side", + "5725f190ec44d21400f3d773": "very little", + "5725f2c838643c19005aceed": "Ralph Woodward", + "5725f2c838643c19005aceee": "300", + "5725f2c838643c19005aceef": "2,500", + "5725f2c838643c19005acef0": "22", + "5725f2c838643c19005acef1": "April through October, 6am to 10pm and November through March, 6am to 7pm", + "5725f46289a1e219009ac0fa": "1946", + "5725f46289a1e219009ac0fb": "William Smilie", + "5725f46289a1e219009ac0fc": "Sierra Sky Park", + "5725f46289a1e219009ac0fd": "automobiles", + "5725f46289a1e219009ac0fe": "numerous such communities across the United States and around the world", + "5725f5b1271a42140099d371": "a semidesert", + "5725f5b1271a42140099d372": "July", + "5725f5b1271a42140099d373": "11.5 inches", + "5725f5b1271a42140099d374": "northwest", + "5725f5b1271a42140099d375": "December, January and February", + "5725f6e138643c19005acf19": "115 \u00b0F", + "5725f6e138643c19005acf1a": "January 6, 1913", + "5725f6e138643c19005acf1b": "1885", + "5725f6e138643c19005acf1c": "2.2 inches", + "5725f6e138643c19005acf1d": "3.55 inches", + "5725f7cd38643c19005acf23": "494,665", + "5725f7cd38643c19005acf24": "4,404.5", + "5725f7cd38643c19005acf25": "8,525", + "5725f7cd38643c19005acf26": "30.0%", + "5725f7cd38643c19005acf27": "4,404.5", + "5725f8f5ec44d21400f3d7b1": "68,511", + "5725f8f5ec44d21400f3d7b2": "19.3%", + "5725f8f5ec44d21400f3d7b3": "1,388", + "5725f8f5ec44d21400f3d7b4": "3.62", + "5725f8f5ec44d21400f3d7b5": "3.07", + "5725fabc89a1e219009ac128": "427,652", + "5725fabc89a1e219009ac129": "149,025", + "5725fabc89a1e219009ac12a": "8.4%", + "5725fabc89a1e219009ac12b": "11.2%", + "5725fabc89a1e219009ac12c": "4,097.9 people per square mile", + "5725fb8138643c19005acf3f": "To avoid interference with existing VHF television stations in the San Francisco Bay Area", + "5725fb8138643c19005acf40": "KMJ-TV", + "5725fb8138643c19005acf41": "June 1, 1953", + "5725fb8138643c19005acf42": "NBC affiliate KSEE", + "5725fb8138643c19005acf43": "KGPE", + "5725fcbe271a42140099d3ad": "State Route 99", + "5725fcbe271a42140099d3ae": "the Sierra Freeway", + "5725fcbe271a42140099d3af": "Eisenhower Freeway", + "5725fcbe271a42140099d3b0": "west", + "5725fe63ec44d21400f3d7dd": "Fresno", + "5725fe63ec44d21400f3d7de": "1950s", + "5725fe63ec44d21400f3d7df": "SR 99", + "5725fe63ec44d21400f3d7e0": "rapidly raising population and traffic in cities along SR 99, as well as the desirability of Federal funding", + "5725ff8238643c19005acf49": "Amtrak San Joaquins", + "5725ff8238643c19005acf4a": "Downtown Fresno", + "5725ff8238643c19005acf4b": "Burlington Northern Santa Fe Railway and Union Pacific Railroad railroads", + "5725ff8238643c19005acf4c": "San Joaquin Valley Railroad", + "5725ff8238643c19005acf4d": "Fresno", + "5725d34089a1e219009abf50": "Distributed Adaptive Message Block Switching", + "5725d34089a1e219009abf51": "to provide a fault-tolerant, efficient routing method for telecommunication messages", + "5725d34089a1e219009abf52": "theretofore established principles of pre-allocation of network bandwidth", + "5725d34089a1e219009abf53": "coining the modern name packet switching", + "572632ceec44d21400f3dc2f": "Distributed Adaptive Message Block Switching", + "572632ceec44d21400f3dc30": "to provide a fault-tolerant, efficient routing method for telecommunication messages", + "572632ceec44d21400f3dc31": "Donald Davies", + "5725d52f89a1e219009abf78": "circuit switching", + "5725d52f89a1e219009abf79": "a fee per unit of connection time", + "5725d52f89a1e219009abf7a": "a fee per unit of information transmitted", + "572634a789a1e219009ac56c": "circuit switching, a method which pre-allocates dedicated network bandwidth specifically for each communication session", + "572634a789a1e219009ac56d": "pre-allocates dedicated network bandwidth specifically for each communication session, each having a constant bit rate and latency between nodes", + "572634a789a1e219009ac56e": "pre-allocates dedicated network bandwidth specifically for each communication session, each having a constant bit rate and latency between nodes", + "572634a789a1e219009ac56f": "a fee per unit of information transmitted", + "5726219489a1e219009ac2ce": "with or without intermediate forwarding nodes", + "5726219489a1e219009ac2cf": "by intermediate network nodes", + "5726219489a1e219009ac2d0": "according to a multiple access scheme", + "5726356938643c19005ad2ff": "with or without intermediate forwarding nodes", + "5726356938643c19005ad300": "by intermediate network nodes", + "5726356938643c19005ad301": "according to a multiple access scheme", + "5726249538643c19005ad07f": "distributed adaptive message block switching", + "5726249538643c19005ad080": "distributed adaptive message block switching", + "5726249538643c19005ad081": "use of a decentralized network with multiple paths between any two points", + "5726249538643c19005ad082": "by store and forward switching", + "57263677ec44d21400f3dc4a": "a general architecture for a large-scale, distributed, survivable communications network", + "57263677ec44d21400f3dc4c": "store and forward switching", + "57263677ec44d21400f3dc49": "distributed adaptive message block switching", + "57263677ec44d21400f3dc4b": "use of a decentralized network with multiple paths between any two points", + "572629c6271a42140099d6a3": "message routing methodology", + "572629c6271a42140099d6a4": "packet switching", + "572629c6271a42140099d6a5": "a nationwide network in the UK", + "572629c6271a42140099d6a6": "ARPANET", + "5726378238643c19005ad313": "Donald Davies", + "5726378238643c19005ad314": "packet switching", + "5726378238643c19005ad315": "suggested it for use in the ARPANET", + "5726385e271a42140099d797": "complete addressing information", + "5726385e271a42140099d798": "individually", + "5726385e271a42140099d799": "a destination address, source address, and port numbers", + "5726385e271a42140099d79a": "the original message/data is reassembled in the correct order", + "5726398589a1e219009ac58b": "small", + "5726398589a1e219009ac58a": "The packet header can be small", + "5726398589a1e219009ac589": "address information", + "5726398589a1e219009ac588": "a setup phase in each involved node before any packet is transferred to establish the parameters of communication", + "57263b1638643c19005ad333": "connection-oriented operations", + "57263b1638643c19005ad335": "Internet Protocol (IP) at the network layer", + "57263b1638643c19005ad334": "interconnect LANs across wide area networks", + "57263b1638643c19005ad336": "to run IP over ATM or a version of MPLS", + "57263c78ec44d21400f3dc7b": "1969", + "57263c78ec44d21400f3dc7c": "division of functions and tasks between the hosts at the edge of the network and the network core", + "57263c78ec44d21400f3dc7d": "The User Datagram Protocol (UDP) is an example of a datagram protocol", + "57263c78ec44d21400f3dc7e": "this network type", + "57263cfcec44d21400f3dc8d": "AppleTalk was a proprietary suite of networking protocols", + "57263cfcec44d21400f3dc8e": "allowed local area networks to be established ad hoc without the requirement for a centralized router or server", + "57263cfcec44d21400f3dc8f": "addresses", + "57263cfcec44d21400f3dc90": "plug-n-play system", + "57263dcd89a1e219009ac5a2": "The CYCLADES packet switching network", + "57263dcd89a1e219009ac5a3": "It was the first network to make the hosts responsible for reliable delivery of data", + "57263dcd89a1e219009ac5a4": "using unreliable datagrams and associated end-to-end protocol mechanisms", + "57263dcd89a1e219009ac5a5": "ARPANET architecture", + "57263ea0271a42140099d7c3": "a suite of network protocols created by Digital Equipment Corporation, originally released in 1975 in order to connect two PDP-11 minicomputers", + "57263ea0271a42140099d7c4": "to connect two PDP-11 minicomputers", + "57263ea0271a42140099d7c5": "seven", + "57263ea0271a42140099d7c6": "open standards with published specifications", + "57263fd138643c19005ad37b": "a data network based on this voice-phone network", + "57263fd138643c19005ad37c": "Schenectady, Phoenix, Chicago, and Phoenix", + "57263fd138643c19005ad37d": "They lost money from the beginning", + "57263fd138643c19005ad37e": "He decided that a time-sharing system", + "5726414e271a42140099d7e5": "to explore computer networking between three of Michigan's public universities as a means to help the state's educational and economic development", + "5726414e271a42140099d7e6": "connections to the CDC mainframe at Michigan State University in East Lansing", + "5726414e271a42140099d7e7": "All of this set the stage for Merit's role in the NSFNET project starting in the mid-1980s", + "57264228ec44d21400f3dcf5": "the first FCC-licensed public data network in the United States", + "57264228ec44d21400f3dcf6": "Larry Roberts", + "57264228ec44d21400f3dcf7": "making ARPANET technology public", + "57264228ec44d21400f3dcf8": "ARPANET", + "57264228ec44d21400f3dcf9": "GTE", + "5726431aec44d21400f3dd13": "an international data communications network headquartered in San Jose, CA", + "5726431aec44d21400f3dd14": "Users typically connected via dial-up connections or dedicated async connections", + "5726431aec44d21400f3dd15": "via dial-up connections or dedicated async connections", + "5726431aec44d21400f3dd16": "build their own dedicated networks", + "5726431aec44d21400f3dd17": "build their own dedicated networks", + "572643de5951261400b5195a": "two", + "572643de5951261400b5195b": "Bell Northern Research", + "572643de5951261400b5195c": "the interconnection of national X.25 networks", + "5726446a89cfff1900a8404d": "an Australian public X.25 network operated by Telstra", + "5726446a89cfff1900a8404e": "supporting applications such as on-line betting, financial applications", + "5726446a89cfff1900a8404f": "linking a permanent X.25 node to the network", + "57264586f1498d1400e8dac6": "the public switched data network operated by the Dutch PTT Telecom", + "57264586f1498d1400e8dac7": "the network and the connected users via leased lines", + "57264586f1498d1400e8dac8": "the network and the connected users via leased lines", + "57264586f1498d1400e8dac9": "incorrect", + "5726462b708984140094c117": "The Computer Science Network", + "5726462b708984140094c118": "to extend networking benefits", + "5726462b708984140094c119": "extend networking benefits", + "5726472bdd62a815002e8042": "a not-for-profit United States computer networking consortium", + "5726472bdd62a815002e8043": "Qwest", + "5726472bdd62a815002e8044": "Abilene", + "5726472bdd62a815002e8045": "Qwest", + "5726472bdd62a815002e8046": "Internet2 Network", + "572647e2dd62a815002e805c": "The National Science Foundation Network", + "572647e2dd62a815002e805d": "advanced research and education networking in the United States", + "572647e2dd62a815002e805e": "to link researchers to the nation's NSF-funded supercomputing centers", + "572648d1708984140094c15d": "Very high-speed Backbone Network Service", + "572648d1708984140094c15e": "Very high-speed Backbone Network Service", + "572648d1708984140094c15f": "MCI Telecommunications", + "572648d1708984140094c160": "more than 100", + "572648d1708984140094c161": "The vBNS installed one of the first ever production OC-48c (2.5 Gbit/s) IP links", + "57264684708984140094c123": "Central Asia", + "57264684708984140094c124": "Spreading throughout the Mediterranean and Europe, the Black Death is estimated to have killed 30\u201360%", + "57264684708984140094c125": "30\u201360%", + "57264684708984140094c126": "17th century", + "57264684708984140094c127": "until the 19th century", + "572647935951b619008f6ec9": "The plague disease", + "572647935951b619008f6eca": "1338\u201339", + "572647935951b619008f6ecb": "China", + "572647935951b619008f6ecc": "1331", + "572647935951b619008f6ecd": "25 million", + "57264845f1498d1400e8db0a": "Genoese traders", + "57264845f1498d1400e8db0b": "Mongol army under Jani Beg", + "57264845f1498d1400e8db0c": "infected corpses", + "57264845f1498d1400e8db0d": "Sicily and the south of Europe", + "57264845f1498d1400e8db0e": "war, famine, and weather", + "572648ed5951b619008f6f03": "northwest", + "572648ed5951b619008f6f04": "Russia", + "572648ed5951b619008f6f05": "France, Spain, Portugal and England", + "572648ed5951b619008f6f06": "Germany and Scandinavia", + "572648ed5951b619008f6f07": "1349", + "57264991f1498d1400e8db2e": "serious depopulation and permanent change in both economic and social structures", + "57264991f1498d1400e8db2f": "autumn 1347", + "57264991f1498d1400e8db30": "through the port's trade with Constantinople, and ports on the Black Sea", + "57264991f1498d1400e8db31": "the north", + "57264a74708984140094c18b": "Gasquet", + "57264a74708984140094c18c": "atra mors", + "57264a74708984140094c18d": "Gasquet", + "57264a74708984140094c18e": "1823", + "57264a74708984140094c18f": "Germany", + "57264b3edd62a815002e80aa": "the heavens", + "57264b3edd62a815002e80ab": "the king of France", + "57264b3edd62a815002e80ac": "Miasma theory", + "57264b3edd62a815002e80ad": "Miasma theory", + "57264c42dd62a815002e80c6": "Yersinia pestis", + "57264c42dd62a815002e80c7": "1894", + "57264c42dd62a815002e80c8": "Alexandre Yersin", + "57264c42dd62a815002e80c9": "The mechanism", + "57264c42dd62a815002e80ca": "two populations of rodents", + "57264cc6dd62a815002e80e4": "Francis Aidan Gasquet", + "57264cc6dd62a815002e80e5": "some form of the ordinary Eastern or bubonic plague", + "57264cc6dd62a815002e80e6": "1908", + "57264cc6dd62a815002e80e7": "Great Pestilence", + "57264cc6dd62a815002e80e8": "Justinian plague", + "57264d58f1498d1400e8db7a": "30\u201375%", + "57264d58f1498d1400e8db7b": "38\u201341 \u00b0C", + "57264d58f1498d1400e8db7c": "80", + "57264d58f1498d1400e8db7d": "90 to 95 percent", + "57264d58f1498d1400e8db7e": "high fevers and purple skin patches", + "57264e2f708984140094c1e1": "October 2010", + "57264e2f708984140094c1e2": "Yersinia pestis in the Black Death", + "57264e2f708984140094c1e3": "Polymerase Chain Reaction (PCR) techniques", + "57264e2f708984140094c1e4": "tooth sockets in human skeletons from mass graves in northern, central and southern Europe", + "57264e2f708984140094c1e5": "Yersinia pestis in the Black Death", + "57264f18f1498d1400e8dbae": "genetic branches", + "57264f18f1498d1400e8dbaf": "Y. p. orientalis and Y. p. medievalis", + "57264f18f1498d1400e8dbb0": "may have entered Europe", + "57264f18f1498d1400e8dbb1": "November 1347", + "57264f18f1498d1400e8dbb2": "spring of 1349", + "57264fe65951b619008f6fa1": "The results of the Haensch study have since been confirmed and amended", + "57264fe65951b619008f6fa2": "East Smithfield burial site in England", + "57264fe65951b619008f6fa3": "may no longer exist", + "57264fe65951b619008f6fa4": "October 2011", + "5726509bdd62a815002e815a": "J. F. D. Shrewsbury", + "5726509bdd62a815002e815b": "the reported rates of mortality in rural areas during the 14th-century pandemic were inconsistent with the modern bubonic plague", + "5726509bdd62a815002e815c": "that contemporary accounts were exaggerations", + "5726509bdd62a815002e815d": "the first major work to challenge the bubonic plague theory", + "5726509bdd62a815002e815e": "Samuel K. Cohn, Jr.", + "5726516a708984140094c223": "an epidemiological account", + "5726516a708984140094c224": "lack of reliable statistics", + "5726516a708984140094c225": "over 100%", + "5726516a708984140094c226": "the clergy", + "5726516a708984140094c227": "1377", + "57265285708984140094c25b": "the DNA results may be flawed and might not have been repeated elsewhere, despite extensive samples from other mass graves", + "57265285708984140094c25c": "marginal significance", + "57265285708984140094c25d": "too cold", + "57265285708984140094c25e": "faster", + "57265285708984140094c25f": "5 to 15 years", + "5726534d708984140094c26d": "a form of anthrax", + "5726534d708984140094c26e": "it may have been a combination of anthrax and other pandemics", + "5726534d708984140094c26f": "typhus, smallpox and respiratory infections", + "5726534d708984140094c270": "a type of \"blood poisoning", + "5726534d708984140094c271": "25", + "5726542ff1498d1400e8dc28": "about a third", + "5726542ff1498d1400e8dc29": "Half", + "5726542ff1498d1400e8dc2a": "pre-planning and Christian burials", + "5726542ff1498d1400e8dc2b": "50%", + "5726542ff1498d1400e8dc2c": "isolated", + "572654e2708984140094c2b7": "14th to 17th centuries", + "572654e2708984140094c2b8": "the plague was present somewhere in Europe in every year between 1346 and 1671", + "572654e2708984140094c2b9": "almost a million", + "5726559edd62a815002e81c8": "propose", + "5726559edd62a815002e81c9": "1350", + "5726559edd62a815002e81ca": "10\u201315%", + "5726559edd62a815002e81cb": "1665", + "57265642f1498d1400e8dc68": "40,000", + "57265642f1498d1400e8dc69": "Russia", + "57265642f1498d1400e8dc6b": "Italian Plague", + "57265642f1498d1400e8dc6c": "1654", + "57265642f1498d1400e8dc6a": "22", + "57265700dd62a815002e820e": "1.7 million", + "57265700dd62a815002e820f": "300,000", + "57265700dd62a815002e8210": "half", + "57265700dd62a815002e8211": "Sweden v. Russia and allies", + "57265700dd62a815002e8212": "1720", + "5726577f708984140094c301": "1500 and 1850", + "5726577f708984140094c302": "30 to 50 thousand", + "5726577f708984140094c303": "second quarter of the 19th century", + "5726577f708984140094c304": "two-thirds", + "572657d9dd62a815002e8230": "melt", + "572657d9dd62a815002e8231": "metamorphic rock", + "572657d9dd62a815002e8232": "a new magma", + "572657d9dd62a815002e8233": "igneous, sedimentary, and metamorphic", + "572657d9dd62a815002e8234": "heat and pressure", + "57265d08708984140094c397": "seafloor spreading", + "57265d08708984140094c398": "crust and rigid uppermost portion of the upper mantle", + "57265d08708984140094c399": "asthenosphere", + "57265d08708984140094c39a": "the convection of the mantle", + "57265d08708984140094c39b": "1960s", + "57265f605951b619008f70db": "divergent boundaries", + "57265f605951b619008f70dc": "convergent boundaries", + "57265f605951b619008f70dd": "Transform boundaries", + "57265f605951b619008f70de": "Alfred Wegener", + "57265f605951b619008f70df": "convecting", + "57266193dd62a815002e832a": "seismic waves", + "57266193dd62a815002e832b": "a crust and lithosphere on top, the mantle below", + "57266193dd62a815002e832d": "mantle below", + "57266193dd62a815002e832e": "wave speeds", + "57266193dd62a815002e832c": "a crust and lithosphere on top", + "572663a9f1498d1400e8ddf2": "compresses the most recent era", + "572663a9f1498d1400e8ddf4": "Quaternary", + "572663a9f1498d1400e8ddf5": "Holocene", + "572663a9f1498d1400e8ddf6": "Quaternary", + "572665ff708984140094c4c3": "The principle of cross-cutting relationships", + "572665ff708984140094c4c4": "older", + "572665ff708984140094c4c5": "the key bed", + "572665ff708984140094c4c6": "younger", + "572667e2f1498d1400e8de90": "xenoliths", + "572667e2f1498d1400e8de91": "magma or lava flows", + "572667e2f1498d1400e8de92": "clasts", + "572667e2f1498d1400e8de93": "The principle of inclusions and components", + "572667e2f1498d1400e8de94": "gravel", + "572669a9dd62a815002e8416": "The principle of faunal succession", + "572669a9dd62a815002e8417": "William Smith", + "572669a9dd62a815002e8418": "complex", + "572669a9dd62a815002e8419": "organisms", + "572669a9dd62a815002e841a": "Charles Darwin", + "57266c015951b619008f7237": "beginning of the 20th century", + "57266c015951b619008f7238": "stratigraphic", + "57266c015951b619008f7239": "new absolute ages", + "57266c015951b619008f723a": "one another", + "57266c015951b619008f723b": "fossil sequences", + "57266e72f1498d1400e8df8c": "Thermochemical techniques", + "57266e72f1498d1400e8df8d": "closure temperature", + "57266e72f1498d1400e8df8e": "isotope ratios", + "57266e72f1498d1400e8df8f": "Dating of lava and volcanic ash layers", + "5726701add62a815002e84c8": "horizontal", + "5726701add62a815002e84c9": "shallow crust", + "5726701add62a815002e84ca": "antiforms", + "5726701add62a815002e84cb": "synforms", + "5726701add62a815002e84cc": "anticlines and synclines", + "572671a5f1498d1400e8dfe4": "Extension", + "572671a5f1498d1400e8dfe5": "boudins", + "572671a5f1498d1400e8dfe6": "Maria Fold and Thrust Belt", + "572671a5f1498d1400e8dfe7": "metamorphosed", + "572671a5f1498d1400e8dfe8": "Extension causes the rock units as a whole to become longer and thinner", + "572673f5708984140094c69b": "Dikes", + "572673f5708984140094c69c": "around the lava tube of a volcano", + "572673f5708984140094c69d": "topographic gradients", + "572673f5708984140094c69e": "Continual motion along the fault", + "572673f5708984140094c69f": "Deformational events", + "57267640f1498d1400e8e074": "layered basaltic lava flows", + "57267640f1498d1400e8e075": "the Acasta gneiss of the Slave craton", + "57267640f1498d1400e8e076": "sedimentary rocks", + "57267640f1498d1400e8e077": "Cambrian time", + "57267640f1498d1400e8e078": "northwestern Canada", + "572677e7708984140094c723": "the study of rocks", + "572677e7708984140094c724": "the study of sedimentary layers", + "572677e7708984140094c725": "the study of positions of rock units and their deformation", + "572677e7708984140094c726": "soils, rivers, landscapes, and glaciers", + "57267947f1498d1400e8e0ec": "identifying rocks", + "57267947f1498d1400e8e0ed": "interference properties", + "57267947f1498d1400e8e0ee": "geochemical evolution of rock units", + "57267947f1498d1400e8e0ef": "the laboratory", + "57267947f1498d1400e8e0f0": "electron microprobe", + "57267b3c5951b619008f7423": "fluid inclusion data and perform high temperature and pressure physical experiments", + "57267b3c5951b619008f7424": "fluid inclusion data and perform high temperature and pressure physical experiments", + "57267b3c5951b619008f7425": "metamorphic processes", + "57267d52708984140094c7d9": "Structural", + "57267d52708984140094c7da": "microscopic analysis of oriented thin sections of geologic samples", + "57267d52708984140094c7db": "plot and combine", + "57267d52708984140094c7dc": "analog and numerical", + "57267ebfdd62a815002e872c": "orogenic wedges", + "57267ebfdd62a815002e872d": "orogenic wedges", + "57267ebfdd62a815002e872e": "sand", + "57267ebfdd62a815002e872f": "orogenic wedge", + "57267ebfdd62a815002e8730": "Numerical models", + "57268066708984140094c821": "stratigraphers", + "57268066708984140094c822": "geophysical surveys", + "57268066708984140094c823": "well logs", + "57268066708984140094c824": "computer programs", + "57268066708984140094c825": "water, coal, and hydrocarbon", + "57268220f1498d1400e8e218": "to provide better absolute bounds on the timing and rates of deposition", + "57268220f1498d1400e8e216": "biostratigraphers", + "57268220f1498d1400e8e219": "Magnetic stratigraphers", + "57268220f1498d1400e8e217": "Geochronologists", + "572683f95951b619008f7525": "Persia", + "572683f95951b619008f7526": "Abu al-Rayhan al-Biruni", + "572683f95951b619008f7527": "Shen Kuo", + "572683f95951b619008f7528": "Ibn Sina", + "572683f95951b619008f7529": "deposition of silt", + "57268527708984140094c8bf": "James Hutton", + "57268527708984140094c8c0": "Theory of the Earth", + "57268527708984140094c8c1": "1795", + "57268527708984140094c8c2": "explained his theory that the Earth must be much older", + "572686ac5951b619008f75a9": "William Maclure", + "572686ac5951b619008f75aa": "1809", + "572686ac5951b619008f75ab": "1807", + "572686ac5951b619008f75ad": "Observations on the Geology of the United States explanatory of a Geological Map", + "572686ac5951b619008f75ac": "American Philosophical Society", + "57268882f1498d1400e8e306": "Principles of Geology", + "57268882f1498d1400e8e307": "uniformitarianism", + "57268882f1498d1400e8e308": "uniformitarianism", + "57268882f1498d1400e8e309": "catastrophism", + "57268882f1498d1400e8e30a": "Charles Darwin", + "5726642f5951b619008f7157": "103", + "5726642f5951b619008f7158": "8.5", + "5726642f5951b619008f7159": "Eurocities network of European cities", + "5726642f5951b619008f715a": "Northumberland", + "5726642f5951b619008f715b": "Geordie", + "5726651ff1498d1400e8de30": "Robert Curthose", + "5726651ff1498d1400e8de31": "wool trade", + "5726651ff1498d1400e8de32": "coal", + "5726651ff1498d1400e8de33": "16th", + "5726651ff1498d1400e8de34": "the Great North Run", + "5726660d5951b619008f71b1": "Pons Aelius", + "5726660d5951b619008f71b2": "River Tyne", + "5726660d5951b619008f71b3": "2,000", + "5726660d5951b619008f71b4": "Hadrian's Wall", + "5726660d5951b619008f71b5": "Pictish", + "572666d9dd62a815002e83b4": "England", + "572666d9dd62a815002e83b5": "Elizabeth", + "572666d9dd62a815002e83b6": "25-foot", + "572666d9dd62a815002e83b7": "William the Lion", + "572666d9dd62a815002e83b8": "three", + "57266783f1498d1400e8de86": "coal", + "57266783f1498d1400e8de87": "the Hostmen", + "57266783f1498d1400e8de88": "a pointless pursuit", + "57266783f1498d1400e8de89": "eccentric", + "57266783f1498d1400e8de8a": "ruin him", + "57266a15f1498d1400e8def6": "their families", + "57266a15f1498d1400e8def7": "boats", + "57266a15f1498d1400e8def8": "7,000 out of 20,000", + "57266a15f1498d1400e8def9": "one-third", + "57266a15f1498d1400e8defa": "devastating loss", + "57266ab3dd62a815002e8434": "the King", + "57266ab3dd62a815002e8435": "the Scots", + "57266ab3dd62a815002e8436": "drummes", + "57266ab3dd62a815002e8437": "Triumphing by a brave defence", + "57266ab3dd62a815002e8438": "Charles I", + "57266cc9f1498d1400e8df53": "urbanization of the city", + "57266cc9f1498d1400e8df54": "Maling company", + "57266cc9f1498d1400e8df55": "electric lighting", + "57266cc9f1498d1400e8df52": "prosperity", + "57266cc9f1498d1400e8df56": "steam turbine", + "57266dd4f1498d1400e8df78": "medieval", + "57266dd4f1498d1400e8df79": "Narrow alleys", + "57266dd4f1498d1400e8df7a": "Stairs", + "57266dd4f1498d1400e8df7b": "modern buildings", + "57266dd4f1498d1400e8df7c": "a restaurant situated at a Grade I-listed 16th century merchant's house", + "57266ec2dd62a815002e84a0": "Tyneside Classical", + "57266ec2dd62a815002e84a1": "England's best-looking city", + "57266ec2dd62a815002e84a2": "Grey Street", + "57266ec2dd62a815002e84a3": "1960s", + "57266ec2dd62a815002e84a4": "Shopping Centre", + "57266fa1f1498d1400e8dfa4": "the Town Moor", + "57266fa1f1498d1400e8dfa5": "graze", + "57266fa1f1498d1400e8dfa7": "The Hoppings funfair", + "57266fa1f1498d1400e8dfa8": "June", + "57266fa1f1498d1400e8dfa6": "Honorary freemen", + "57267076708984140094c601": "Large-scale regeneration", + "57267076708984140094c602": "Gateshead Council", + "57267076708984140094c603": "Norman Foster", + "57267076708984140094c604": "As a tourist promotion", + "57267076708984140094c605": "ten", + "572671165951b619008f72b7": "Grainger Town area", + "572671165951b619008f72b8": "1835 and 1842", + "572671165951b619008f72b9": "four stories high", + "572671165951b619008f72ba": "244", + "572671e55951b619008f72d7": "the Butcher Market", + "572671e55951b619008f72d8": "1835", + "572671e55951b619008f72d9": "2000", + "572671e55951b619008f72da": "a painting", + "572671e55951b619008f72db": "English Heritage", + "57267383dd62a815002e8552": "oceanic", + "57267383dd62a815002e8553": "warming", + "57267383dd62a815002e8554": "rain shadow", + "57267383dd62a815002e8555": "January 1982", + "57267383dd62a815002e8556": "British Isles", + "572674f6f1498d1400e8e03a": "2010", + "572674f6f1498d1400e8e03b": "Eldon Square Shopping Centre", + "572674f6f1498d1400e8e03c": "Bainbridge's", + "572674f6f1498d1400e8e03d": "by department", + "572674f6f1498d1400e8e03e": "2007", + "5726769c708984140094c711": "shopping", + "5726769c708984140094c712": "suburban", + "5726769c708984140094c713": "Tesco", + "5726769c708984140094c714": "the MetroCentre", + "5726769c708984140094c715": "Gateshead", + "5726778df1498d1400e8e0ac": "The Tyneside flat", + "5726778df1498d1400e8e0ad": "terraces", + "5726778df1498d1400e8e0ae": "Ouseburn valley", + "5726778df1498d1400e8e0af": "Architects", + "5726778df1498d1400e8e0b0": "high density", + "572678c0dd62a815002e863e": "7.8%", + "572678c0dd62a815002e863f": "5.9%", + "572678c0dd62a815002e8640": "overinflated", + "572678c0dd62a815002e8641": "overinflated markets in the local authorities: Harrogate, Cheltenham, Bath, inner London, Hastings, Brighton and Tunbridge Wells", + "572678c0dd62a815002e8642": "Tunbridge Wells", + "572679c35951b619008f73db": "2001", + "572679c35951b619008f73dc": "the metropolitan borough of Newcastle", + "572679c35951b619008f73dd": "student", + "572679c35951b619008f73de": "Newcastle and Northumbria Universities", + "572679c35951b619008f73df": "student populations", + "57267a94f1498d1400e8e122": "37.8", + "57267a94f1498d1400e8e123": "Many people in the city have Scottish or Irish ancestors", + "57267a94f1498d1400e8e124": "Border Reiver", + "57267a94f1498d1400e8e125": "between 500 and 2,000", + "57267a94f1498d1400e8e126": "1%", + "57267b65dd62a815002e86a6": "Geordie", + "57267b65dd62a815002e86a7": "Anglo-Saxon populations", + "57267b65dd62a815002e86a8": "many elements", + "57267b65dd62a815002e86a9": "how they were pronounced", + "57267b65dd62a815002e86aa": "stream", + "57267c63dd62a815002e86d6": "Scandinavia", + "57267c63dd62a815002e86d7": "Northern United Kingdom", + "57267c63dd62a815002e86d8": "Scots", + "57267c63dd62a815002e86d9": "Many words", + "57267c63dd62a815002e86da": "Dutch gooien", + "57267ce7708984140094c7c9": "a report", + "57267ce7708984140094c7ca": "noisiest", + "57267ce7708984140094c7cb": "80.4", + "57267ce7708984140094c7cc": "negative", + "57267ce7708984140094c7cd": "arbitrarily selected locations", + "57267de1f1498d1400e8e194": "Collingwood Street", + "57267de1f1498d1400e8e195": "a new indoor complex", + "57267de1f1498d1400e8e196": "12", + "57267de1f1498d1400e8e197": "The Pink Triangle", + "57267de1f1498d1400e8e198": "bars, caf\u00e9s and clubs", + "57267f695951b619008f74bd": "theatre", + "57267f695951b619008f74be": "Stephen Kemble", + "57267f695951b619008f74bf": "many celebrated seasons", + "57267f695951b619008f74c0": "21 January 1788", + "57267f695951b619008f74c1": "Grey Street", + "5726800add62a815002e8750": "theatres", + "5726800add62a815002e8751": "Theatre Royal", + "5726800add62a815002e8752": "Royal Shakespeare Company", + "5726800add62a815002e8753": "local talent", + "5726800add62a815002e8754": "the arts capital of the UK", + "572680865951b619008f74e7": "The Literary and Philosophical Society of Newcastle upon Tyne", + "572680865951b619008f74e8": "8000", + "572680865951b619008f74e9": "John and Benjamin Green", + "572680865951b619008f74ea": "lecture theatre", + "572680865951b619008f74eb": "Joseph Swan", + "57268109f1498d1400e8e1fa": "The Newcastle Beer Festival", + "57268109f1498d1400e8e1fb": "May", + "57268109f1498d1400e8e1fc": "March", + "57268109f1498d1400e8e1fd": "EAT! NewcastleGateshead", + "57268109f1498d1400e8e1fe": "2", + "57268341f1498d1400e8e23c": "The Hoppings", + "57268341f1498d1400e8e23d": "every June", + "57268341f1498d1400e8e23e": "Temperance Movement", + "57268341f1498d1400e8e23f": "cycling", + "57268341f1498d1400e8e240": "Northern Pride Festival", + "572683e6f1498d1400e8e24c": "Newcastle Mela", + "572683e6f1498d1400e8e24e": "Sage Gateshead Music and Arts Centre", + "572683e6f1498d1400e8e24f": "Design Event festival", + "572683e6f1498d1400e8e250": "East Asian", + "572683e6f1498d1400e8e24d": "NewcastleGateshead", + "5726847f708984140094c8ab": "folk-rock", + "5726847f708984140094c8ac": "1971", + "5726847f708984140094c8ad": "Venom", + "5726847f708984140094c8ae": "Skyclad", + "5726847f708984140094c8af": "Duran Duran", + "57268525dd62a815002e8806": "November 2006 and May 2008", + "57268525dd62a815002e8807": "Old Town Hall, Gateshead", + "57268525dd62a815002e8808": "three", + "57268525dd62a815002e8809": "the restored Classic", + "57268525dd62a815002e880a": "roof extension", + "57268692dd62a815002e8826": "Newcastle", + "57268692dd62a815002e8827": "life on Tyneside", + "57268692dd62a815002e8828": "shipbuilding", + "57268692dd62a815002e8829": "2009", + "57268692dd62a815002e882a": "Seven Stories", + "57268731f1498d1400e8e2e2": "On the Night of the Fire", + "57268731f1498d1400e8e2e3": "Get Carter", + "57268731f1498d1400e8e2e4": "noir thriller", + "57268731f1498d1400e8e2e5": "Mike Figgis", + "57268731f1498d1400e8e2e6": "Mike Figgis", + "572687e1dd62a815002e8852": "Gosforth Park", + "572687e1dd62a815002e8853": "Newcastle Eagles", + "572687e1dd62a815002e8854": "Newcastle Diamonds", + "572687e1dd62a815002e8855": "Byker", + "572687e1dd62a815002e8856": "Blaydon Race", + "57268885dd62a815002e886a": "6 miles", + "57268885dd62a815002e886b": "via the Metro Light Rail system", + "57268885dd62a815002e886c": "20 minutes", + "57268885dd62a815002e886d": "over five million", + "57268885dd62a815002e886e": "over 90", + "572689385951b619008f761b": "Victorian architecture", + "572689385951b619008f761c": "six", + "572689385951b619008f761d": "Queen Victoria", + "572689385951b619008f761e": "Robert Stephenson", + "572689385951b619008f761f": "Manors", + "572689b6dd62a815002e8890": "about three hours", + "572689b6dd62a815002e8891": "three", + "572689b6dd62a815002e8892": "Edinburgh", + "572689b6dd62a815002e8893": "CrossCountry", + "572689b6dd62a815002e8894": "Northern Rail", + "57268a8fdd62a815002e88ce": "Tyne and Wear Metro", + "57268a8fdd62a815002e88cf": "five", + "57268a8fdd62a815002e88d0": "deep-level tunnels", + "57268a8fdd62a815002e88d1": "A bridge", + "57268a8fdd62a815002e88d2": "over 37 million", + "57268bb25951b619008f7645": "Metro: All Change", + "57268bb25951b619008f7646": "smart ticketing", + "57268bb25951b619008f7647": "tracks, signalling and overhead wires", + "57268bb25951b619008f7648": "procurement of an entirely new fleet of trains", + "57268bb25951b619008f7649": "trams", + "57268d1b708984140094c9cd": "A1", + "57268d1b708984140094c9ce": "A69", + "57268d1b708984140094c9cf": "Great North Road", + "57268d1b708984140094c9d0": "the roads between this and the A1's former alignment through the Tyne Tunnel", + "57268d1b708984140094c9d1": "the capacity of the Tyne Tunnel", + "57268ff9f1498d1400e8e3e6": "3", + "57268ff9f1498d1400e8e3e7": "two", + "57268ff9f1498d1400e8e3e8": "Stagecoach", + "57268ff9f1498d1400e8e3e9": "the Tyne and Wear Passenger Transport Executive", + "57268ff9f1498d1400e8e3ea": "Go-Ahead", + "57269120708984140094ca59": "1998", + "57269120708984140094ca5a": "usage of cycling", + "57269120708984140094ca5b": "healthy", + "57269120708984140094ca5c": "one way streets", + "57269120708984140094ca5d": "national networks", + "5726934f5951b619008f771d": "Danish DFDS Seaways", + "5726934f5951b619008f771e": "October 2006", + "5726934f5951b619008f771f": "high fuel prices and new competition from low-cost air services", + "5726934f5951b619008f7720": "late 2008", + "5726934f5951b619008f7721": "Thomson cruise lines", + "57269526dd62a815002e8a4e": "eleven", + "57269526dd62a815002e8a4f": "seven", + "57269526dd62a815002e8a50": "Royal Grammar School", + "57269526dd62a815002e8a51": "Newcastle College", + "57269526dd62a815002e8a52": "Catholic", + "57269698dd62a815002e8a6c": "two", + "57269698dd62a815002e8a6d": "Newcastle University", + "57269698dd62a815002e8a6e": "Sunday Times University of the Year award", + "57269698dd62a815002e8a6f": "polytechnics became new universities", + "57269698dd62a815002e8a70": "Northumbria University", + "572699b55951b619008f778f": "three", + "572699b55951b619008f7790": "1474", + "572699b55951b619008f7791": "Coptic Cathedral", + "572699b55951b619008f7792": "Church of St Thomas the Martyr", + "572699b55951b619008f7793": "parish churches", + "57269b165951b619008f77b3": "The Parish Church of St Andrew", + "57269b165951b619008f77b4": "1726", + "57269b165951b619008f77b5": "the main porch", + "57269b165951b619008f77b6": "the last of the ancient churchyards", + "57269b165951b619008f77b7": "The church tower", + "57269c26f1498d1400e8e4ca": "City Road", + "57269c26f1498d1400e8e4cb": "Watermark business park", + "57269c26f1498d1400e8e4cc": "studio 5", + "57269c26f1498d1400e8e4cd": "colouring", + "57269c26f1498d1400e8e4ce": "BBC Radio Newcastle", + "57269d745951b619008f77d7": "NE1fm", + "57269d745951b619008f77d8": "Newcastle Student Radio", + "57269d745951b619008f77d9": "1951", + "57269d745951b619008f77da": "Radio Lollipop", + "57269d745951b619008f77db": "Newcastle University's student's union building", + "57269e80f1498d1400e8e520": "1770", + "57269e80f1498d1400e8e521": "Archbishop of Westminster", + "57269e80f1498d1400e8e522": "George Stephenson", + "57269e80f1498d1400e8e523": "steam turbine", + "57269e80f1498d1400e8e524": "Thailand", + "57269fab5951b619008f7807": "Rutherford Grammar School", + "57269fab5951b619008f7808": "international footballers", + "57269fab5951b619008f7809": "Nobel Prize", + "57269fab5951b619008f780a": "keyed Northumbrian smallpipes", + "57269fab5951b619008f780b": "Newcastle", + "5726710b708984140094c61d": "London", + "5726710b708984140094c61e": "over 4.5 million", + "5726710b708984140094c61f": "1852", + "5726710b708984140094c620": "Queen Victoria and Prince Albert", + "572680ac708984140094c83d": "Kensington and Chelsea", + "572680ac708984140094c83e": "1852", + "572680ac708984140094c83f": "Queen Victoria and Prince Albert", + "572680ac708984140094c840": "Department for Culture, Media and Sport", + "572680ac708984140094c841": "2001", + "57268294708984140094c877": "12.5", + "57268294708984140094c878": "145", + "57268294708984140094c879": "5,000", + "57268294708984140094c87a": "Europe, North America, Asia and North Africa", + "57268294708984140094c87b": "post-classical sculpture", + "572685cd5951b619008f7573": "the Great Exhibition of 1851", + "572685cd5951b619008f7574": "Henry Cole", + "572685cd5951b619008f7575": "Museum of Manufactures", + "572685cd5951b619008f7576": "Somerset House", + "572685cd5951b619008f7577": "Gottfried Semper", + "57268d02f1498d1400e8e378": "Queen Victoria", + "57268d02f1498d1400e8e379": "22 June 1857", + "57268d02f1498d1400e8e37a": "George Wallis", + "57268d02f1498d1400e8e37b": "late night openings", + "57268d02f1498d1400e8e37c": "1949", + "57268f2c708984140094ca25": "September and November 1946", + "57268f2c708984140094ca26": "nearly a million and a half", + "57268f2c708984140094ca27": "Council of Industrial Design", + "57268f2c708984140094ca28": "Festival of Britain", + "57268f2c708984140094ca29": "1948", + "572691d7708984140094ca6d": "a rock concert", + "572691d7708984140094ca6e": "Gryphon", + "572691d7708984140094ca6f": "Roy Strong", + "572691d7708984140094ca70": "mediaeval", + "57269656708984140094cafd": "Dundee", + "57269656708984140094cafe": "\u00a376 million", + "57269656708984140094caff": "on the city's waterfront", + "57269656708984140094cb00": "fashion, architecture, product design, graphic arts and photography", + "57269656708984140094cb01": "within five years", + "572698d7dd62a815002e8a98": "Museum of Childhood. The first building to be erected that still forms part of the museum was the Sheepshanks Gallery", + "572698d7dd62a815002e8a99": "Sheepshanks Gallery", + "572698d7dd62a815002e8a9a": "Captain Francis Fowke", + "572698d7dd62a815002e8a9b": "1862", + "572698d7dd62a815002e8a9c": "the offices and board room", + "57269c06708984140094cba1": "Owen Jones", + "57269c06708984140094cba2": "Italian Renaissance", + "57269c06708984140094cba3": "James Gamble & Reuben Townroe", + "57269c06708984140094cba4": "Isaac Newton", + "57269c06708984140094cba5": "Titian", + "57269d68708984140094cbd7": "Philip Webb and William Morris", + "57269d68708984140094cbd8": "Edward Burne-Jones", + "57269d68708984140094cbd9": "James Gamble", + "57269d68708984140094cbda": "Alfred Stevens", + "57269d68708984140094cbdb": "Sir Edward Poynter", + "5726a0205951b619008f781b": "Colonel (later Major General) Henry Young Darracott Scott", + "5726a0205951b619008f781c": "School for Naval Architects", + "5726a0205951b619008f781d": "Cadeby stone", + "5726a0205951b619008f781e": "prints, drawings, paintings and photographs", + "5726a0205951b619008f781f": "2008", + "5726a2445951b619008f7861": "sgraffito", + "5726a2445951b619008f7862": "F. W. Moody", + "5726a2445951b619008f7863": "southeast of the garden", + "5726a2445951b619008f7864": "south side of the garden", + "5726a2445951b619008f7865": "Reuben Townroe", + "5726a5b5f1498d1400e8e5fe": "Aston Webb", + "5726a5b5f1498d1400e8e5ff": "red brick and Portland stone", + "5726a5b5f1498d1400e8e600": "720 feet", + "5726a5b5f1498d1400e8e601": "statue of fame", + "5726a5b5f1498d1400e8e602": "top row of windows", + "5726a9ff708984140094cd4b": "Alfred Drury", + "5726a9ff708984140094cd4c": "four", + "5726a9ff708984140094cd4d": "Webb", + "5726a9ff708984140094cd4e": "marble", + "5726a9ff708984140094cd4f": "Queen Victoria", + "5726ace8dd62a815002e8c9e": "Art Library", + "5726ace8dd62a815002e8c9f": "Henry Cole wing", + "5726ace8dd62a815002e8ca0": "a new entrance building", + "5726ace8dd62a815002e8ca1": "Christopher Hay and Douglas Coyne", + "5726ace8dd62a815002e8ca2": "the Spiral", + "5726afeb708984140094cdd7": "main silverware gallery", + "5726afeb708984140094cdd8": "mosaic floors", + "5726afeb708984140094cdd9": "FuturePlan", + "5726afeb708984140094cdda": "South Kensington tube station", + "5726afeb708984140094cddb": "McInnes Usher McKnight Architects", + "5726b12f5951b619008f7aaf": "Kim Wilkie", + "5726b12f5951b619008f7ab0": "John Madejski Garden", + "5726b12f5951b619008f7ab1": "elliptical", + "5726b12f5951b619008f7ab2": "receptions, gatherings or exhibition purposes", + "5726b12f5951b619008f7ab3": "American Sweetgum", + "5726b2fcf1498d1400e8e7e4": "2004", + "5726b2fcf1498d1400e8e7e5": "Royal Institute of British Architects", + "5726b2fcf1498d1400e8e7e7": "600,000", + "5726b2fcf1498d1400e8e7e6": "RIBA Drawings and Archives Collection", + "5726b2fcf1498d1400e8e7e8": "700,000", + "5726b6e05951b619008f7b99": "Andrea Palladio", + "5726b6e05951b619008f7b9a": "Andrea Palladio", + "5726b6e05951b619008f7b9b": "over 330", + "5726b6e05951b619008f7b9c": "Andrea Palladio", + "5726b6e05951b619008f7b9d": "Andrea Palladio", + "5726ba83dd62a815002e8e6a": "Bishopsgate", + "5726ba83dd62a815002e8e6b": "Great Fire of London", + "5726ba83dd62a815002e8e6c": "c1600", + "5726ba83dd62a815002e8e6d": "chateau of Montal", + "5726ba83dd62a815002e8e6e": "Alhambra", + "5726bc505951b619008f7c79": "19,000", + "5726bc505951b619008f7c7a": "2006", + "5726bc505951b619008f7c7b": "Ardabil Carpet", + "5726bc505951b619008f7c7c": "Spain", + "5726bc505951b619008f7c7d": "1909", + "5726bdc6f1498d1400e8e9c0": "60,000", + "5726bdc6f1498d1400e8e9c1": "10,000", + "5726bdc6f1498d1400e8e9c2": "6000", + "5726bdc6f1498d1400e8e9c4": "1991", + "5726bdc6f1498d1400e8e9c3": "Jawaharlal Nehru", + "5726bf325951b619008f7cfd": "70,000", + "5726bf325951b619008f7cfe": "China, Japan and Korea", + "5726bf325951b619008f7cff": "T. T. Tsui Gallery", + "5726bf325951b619008f7d00": "1991", + "5726bf325951b619008f7d01": "Ming and Qing", + "5726c4b5dd62a815002e8fd8": "Ando Cloisonn\u00e9", + "5726c4b5dd62a815002e8fd9": "1986", + "5726c4b5dd62a815002e8fda": "13th-century", + "5726c4b5dd62a815002e8fdb": "1550 to 1900", + "5726c4b5dd62a815002e8fdc": "bronze", + "5726c80c5951b619008f7de7": "14th to the 19th century", + "5726c80c5951b619008f7de8": "South East Asia", + "5726c80c5951b619008f7de9": "Refined Hindu and Buddhist sculptures", + "5726c80c5951b619008f7dea": "mother-of-pearl", + "5726c80c5951b619008f7deb": "ivory", + "5726c9a4708984140094d16f": "Leonardo da Vinci", + "5726c9a4708984140094d170": "Forster I, Forster II, and Forster III", + "5726c9a4708984140094d171": "14,000", + "5726c9a4708984140094d172": "1869", + "5726c9a4708984140094d173": "1876", + "5726cc11dd62a815002e9086": "Charles Dickens", + "5726cc11dd62a815002e9087": "Charles Dickens", + "5726cc11dd62a815002e9088": "12th to 16th", + "5726cc11dd62a815002e9089": "the trial and rehabilitation of Joan of Arc", + "5726cc11dd62a815002e908a": "Lucas Horenbout", + "5726ce11f1498d1400e8ebc4": "Word and Image Department", + "5726ce11f1498d1400e8ebc5": "MODES cataloging system", + "5726ce11f1498d1400e8ebc6": "Encoded Archival Description", + "5726ce11f1498d1400e8ebc8": "those were newly accessioned into the collection", + "5726ce11f1498d1400e8ebc7": "Search the Collections", + "5726cfa3708984140094d209": "2007", + "5726cfa3708984140094d20a": "the Factory Project", + "5726cfa3708984140094d20b": "Andy Warhol", + "5726cfa3708984140094d20c": "15,000", + "5726cfa3708984140094d20d": "to catalog everything", + "5726d4a45951b619008f7f69": "British patrons", + "5726d4a45951b619008f7f6a": "Asia", + "5726d4a45951b619008f7f6b": "Gian Lorenzo Bernini", + "5726d4a45951b619008f7f6c": "Horace Walpole", + "5726d4a45951b619008f7f6d": "porcelain, cloth and wallpaper", + "5726d7faf1498d1400e8ecdb": "increase in tea drinking", + "5726d7faf1498d1400e8ecda": "wider trends in British culture", + "5726d7faf1498d1400e8ecde": "John Ruskin", + "5726d7faf1498d1400e8ecdc": "mass production", + "5726d7faf1498d1400e8ecdd": "Arts and Crafts movement", + "5726d993f1498d1400e8ed16": "Trajan's Column", + "5726d993f1498d1400e8ed17": "cut in half", + "5726d993f1498d1400e8ed18": "David", + "5726d993f1498d1400e8ed19": "sculptures, friezes and tombs", + "5726d993f1498d1400e8ed1a": "in a glass case", + "5726dba1dd62a815002e92e4": "1731", + "5726dba1dd62a815002e92e5": "Frederick II the Great", + "5726dba1dd62a815002e92e6": "1762", + "5726dba1dd62a815002e92e7": "1909", + "5726dba1dd62a815002e92e8": "the museum's stock of Chinese and Japanese ceramics", + "5726dd71f1498d1400e8edd8": "Josiah Wedgwood, William De Morgan and Bernard Leach", + "5726dd71f1498d1400e8edd9": "Britain and Holland", + "5726dd71f1498d1400e8edda": "a series of elaborately ornamented ceramic stoves", + "5726dd71f1498d1400e8eddb": "16th and 17th centuries", + "5726dd71f1498d1400e8eddc": "Germany and Switzerland", + "5726de7a5951b619008f80ab": "4000", + "5726de7a5951b619008f80ac": "over 6000", + "5726de7a5951b619008f80ad": "Ancient Egypt", + "5726de7a5951b619008f80af": "Ren\u00e9 Lalique", + "5726de7a5951b619008f80ae": "Ren\u00e9 Lalique", + "5726e06df1498d1400e8ee52": "1994", + "5726e06df1498d1400e8ee53": "Danny Lane", + "5726e06df1498d1400e8ee54": "2004", + "5726e06df1498d1400e8ee55": "Dale Chihuly", + "5726e06df1498d1400e8ee56": "13th", + "5726e1fcdd62a815002e93c4": "10,000", + "5726e1fcdd62a815002e93c5": "2,000", + "5726e1fcdd62a815002e93c6": "Paul Nash, Percy Wyndham Lewis, Eric Gill, Stanley Spencer, John Piper, Graham Sutherland, Lucian Freud and David Hockney", + "5726e1fcdd62a815002e93c7": "Paul Nash, Percy Wyndham Lewis, Eric Gill, Stanley Spencer, John Piper, Graham Sutherland, Lucian Freud and David Hockney", + "5726e1fcdd62a815002e93c8": "Paul Nash, Percy Wyndham Lewis, Eric Gill, Stanley Spencer, John Piper, Graham Sutherland, Lucian Freud and David Hockney", + "5726e37ef1498d1400e8eed8": "14,000", + "5726e37ef1498d1400e8eed9": "Word and Image department", + "5726e37ef1498d1400e8eeda": "everyday clothing from previous eras has not generally survived", + "5726e37ef1498d1400e8eedb": "1913", + "5726e37ef1498d1400e8eedc": "Harrods", + "5726e4eedd62a815002e9438": "2002", + "5726e4eedd62a815002e9439": "Vivienne Westwood", + "5726e4eedd62a815002e943a": "178", + "5726e4eedd62a815002e943b": "Costiff collection of 178 Vivienne Westwood", + "5726e4eedd62a815002e943c": "modern fashion", + "5726e680dd62a815002e946e": "Italian and French Renaissance", + "5726e680dd62a815002e946f": "between 1859 and 1865", + "5726e680dd62a815002e9470": "French 18th-century art and furnishings", + "5726e680dd62a815002e9471": "1882", + "5726e680dd62a815002e9472": "\u00a3250,000", + "5726e834dd62a815002e94a4": "1580", + "5726e834dd62a815002e94a5": "Hans Vredeman de Vries", + "5726e834dd62a815002e94a6": "c1750", + "5726e834dd62a815002e94a7": "Germany", + "5726e834dd62a815002e94a8": "Ernest Gimson, Edward William Godwin, Charles Voysey, Adolf Loos and Otto Wagner", + "5726e9c65951b619008f8247": "over 6000", + "5726e9c65951b619008f8248": "Egypt", + "5726e9c65951b619008f8249": "1869", + "5726e9c65951b619008f824a": "154", + "5726e9c65951b619008f824b": "William and Judith Bollinger", + "5726ee28708984140094d656": "secular and sacred", + "5726ee28708984140094d657": "1496\u201397", + "5726ee28708984140094d658": "nearly 8", + "5726ee28708984140094d659": "Sir George Gilbert Scott", + "5726ee28708984140094d655": "over 10,000", + "5726ef12dd62a815002e959e": "c1110", + "5726ef12dd62a815002e959f": "gilt bronze", + "5726ef12dd62a815002e95a0": "St Thomas Becket", + "5726ef12dd62a815002e95a1": "c1180", + "5726ef12dd62a815002e95a2": "gilt copper", + "5726f1ec708984140094d6aa": "5,100", + "5726f1ec708984140094d6ad": "Bryan Davies", + "5726f1ec708984140094d6ab": "Horniman Museum", + "5726f1ec708984140094d6ac": "35", + "5726f1ec708984140094d6a9": "2010", + "5726f2bcf1498d1400e8f0bc": "650", + "5726f2bcf1498d1400e8f0bd": "650", + "5726f2bcf1498d1400e8f0be": "6800", + "5726f2bcf1498d1400e8f0bf": "Her Majesty the Queen Elizabeth II", + "5726f2bcf1498d1400e8f0c0": "Andr\u00e9s Marzal De Sax", + "5726f4a0708984140094d6e9": "1857", + "5726f4a0708984140094d6ea": "233", + "5726f4a0708984140094d6eb": "forming a 'A National Gallery of British Art", + "5726f4a0708984140094d6ec": "Hay Wain", + "5726f4a0708984140094d6ed": "British", + "5726f755708984140094d737": "galleries of continental art", + "5726f755708984140094d738": "Madame de Pompadour", + "5726f755708984140094d739": "Carlo Crivelli's Virgin and Child", + "5726f755708984140094d73a": "Fran\u00e7ois, Duc d'Alen\u00e7on by Fran\u00e7ois Clouet, Gaspard Dughet", + "5726f90b708984140094d75d": "Eadweard Muybridge", + "5726f90b708984140094d75e": "1887", + "5726f90b708984140094d75f": "781", + "5726f90b708984140094d760": "images of different animals and humans performimg various actions", + "5726f90b708984140094d761": "James Lafayette", + "5726fb18dd62a815002e96ce": "400 AD to 1914", + "5726fb18dd62a815002e96cf": "22,000", + "5726fb18dd62a815002e96d0": "400 AD to 1914", + "5726fb18dd62a815002e96d1": "portrait, allegorical, religious, mythical, statues for gardens including fountains, as well as architectural decorations", + "5726fc63dd62a815002e9706": "National Galleries of Scotland", + "5726fc63dd62a815002e9707": "Neptune and Triton", + "5726fc63dd62a815002e9708": "Chancel Chapel", + "5726fc63dd62a815002e9709": "Giuliano da Sangallo", + "5726fc63dd62a815002e970a": "1493\u20131500", + "5726fe95dd62a815002e9732": "more than 20", + "5726fe95dd62a815002e9733": "the sculptor", + "5726fe95dd62a815002e9734": "1914", + "5726fe95dd62a815002e9735": "World War I", + "5726fe95dd62a815002e9736": "St John the Baptist", + "572700c8dd62a815002e976a": "Nicholas Stone", + "572700c8dd62a815002e976b": "Nicholas Stone", + "572700c8dd62a815002e976c": "Nicholas Stone", + "572700c8dd62a815002e976d": "both British and Europeans", + "572702a3dd62a815002e9790": "Dorothy and Michael Hintze", + "572702a3dd62a815002e9791": "1950", + "572702a3dd62a815002e9792": "by theme, tomb sculpture, portraiture, garden sculpture and mythology", + "572702a3dd62a815002e9793": "Dorothy and Michael Hintze", + "572702a3dd62a815002e9794": "Tate Britain", + "572703fdf1498d1400e8f23c": "53,000", + "572703fdf1498d1400e8f23d": "western European", + "572703fdf1498d1400e8f23e": "1st century AD", + "572703fdf1498d1400e8f23f": "western European though all populated continents", + "572703fdf1498d1400e8f240": "technique", + "57270541dd62a815002e97c8": "Cloth of St Gereon", + "57270541dd62a815002e97c9": "15th-century", + "57270541dd62a815002e97ca": "the Netherlands", + "57270541dd62a815002e97cb": "the hunting of various animals", + "57270541dd62a815002e97cc": "John Vanderbank's workshop", + "57270676dd62a815002e97f0": "late 14th-century", + "57270676dd62a815002e97f1": "William Morris", + "57270676dd62a815002e97f2": "1887", + "57270676dd62a815002e97f3": "Marion Dorn", + "57270676dd62a815002e97f4": "Serge Chermayeff", + "57270817708984140094d8c7": "Theatre Museum", + "57270817708984140094d8c8": "2009", + "57270817708984140094d8c9": "the UK's biggest national collection of material about live performance in the UK since Shakespeare's day", + "57270817708984140094d8ca": "Shakespeare's day", + "57270817708984140094d8cb": "research, exhibitions and other shows", + "57270ab9708984140094d8f7": "Conservation", + "57270ab9708984140094d8f8": "temperature and light", + "57270ab9708984140094d8f9": "interventive", + "57270ab9708984140094d8fa": "Museum of Childhood", + "57270ab9708984140094d8fb": "preventive", + "57267b755951b619008f7433": "Disney\u2013ABC Television Group", + "57267b755951b619008f7434": "1957", + "57267b755951b619008f7435": "Manhattan", + "57267b755951b619008f7436": "Columbus Avenue and West 66th Street", + "57267b755951b619008f7437": "Disney Media Networks", + "57267ca75951b619008f7469": "October 12, 1943", + "57267ca75951b619008f746a": "radio", + "57267ca75951b619008f746b": "1948", + "57267ca75951b619008f746c": "ESPN", + "57267ca75951b619008f746d": "Capital Cities Communications", + "57267f1cdd62a815002e8740": "over 232", + "57267f1cdd62a815002e8741": "Citadel Broadcasting", + "57267f1cdd62a815002e8742": "eight", + "57267f1cdd62a815002e8743": "Canadian Radio-television and Telecommunications Commission", + "57267f1cdd62a815002e8744": "Citadel Broadcasting", + "5726808bdd62a815002e8776": "National Broadcasting Company", + "5726808bdd62a815002e8777": "NBC Blue and NBC Red", + "5726808bdd62a815002e8778": "the major cities", + "5726808bdd62a815002e8779": "drama series", + "5726808bdd62a815002e877a": "NBC Blue Network", + "572681ab708984140094c85d": "Mutual", + "572681ab708984140094c85e": "1938", + "572681ab708984140094c85f": "1940", + "572681ab708984140094c860": "NBC Red", + "572681ab708984140094c861": "NBC Blue", + "572684f5dd62a815002e87fc": "Mark Woods", + "572684f5dd62a815002e87fd": "NBC Blue Network", + "572684f5dd62a815002e87fe": "Dillon, Read & Co.", + "572684f5dd62a815002e87ff": "David Sarnoff", + "572684f5dd62a815002e8800": "$7.5 million", + "572685d1f1498d1400e8e29e": "Life Savers candy", + "572685d1f1498d1400e8e29f": "October 12, 1943", + "572685d1f1498d1400e8e2a0": "George B. Storer", + "572685d1f1498d1400e8e2a1": "president and CEO", + "572685d1f1498d1400e8e2a2": "June 30, 1951", + "57268739708984140094c8ed": "Magnetophon tape recorder", + "57268739708984140094c8ee": "Paul Whiteman", + "57268739708984140094c8ef": "ABC", + "57268739708984140094c8f0": "Bing Crosby", + "57268739708984140094c8f1": "public service", + "57269260dd62a815002e89ea": "$155 million", + "57269260dd62a815002e89eb": "ABC1", + "57269260dd62a815002e89ec": "September 8, 2007", + "57269260dd62a815002e89ed": "ABC International", + "57269260dd62a815002e89ee": "United States", + "57269344f1498d1400e8e43e": "1959", + "57269344f1498d1400e8e43f": "satellite television", + "57269344f1498d1400e8e440": "Japan and Latin America", + "57269344f1498d1400e8e441": "many governments also wanted to increase their independence and strengthen legislation to limit foreign ownership of broadcasting properties", + "5726caaaf1498d1400e8eb5c": "coronation of Queen Elizabeth II", + "5726caaaf1498d1400e8eb5d": "Beirut", + "5726caaaf1498d1400e8eb5e": "Mainichi Broadcasting System", + "5726caaaf1498d1400e8eb5f": "respective issues with technical problems and flight delays", + "5726caaaf1498d1400e8eb60": "respective issues with technical problems and flight delays", + "5726e5ac708984140094d51b": "Peanuts television specials", + "5726e5ac708984140094d51c": "Emmy Awards", + "5726e5ac708984140094d51d": "1965", + "5726e5ac708984140094d51e": "Academy Awards", + "5726e5ac708984140094d51f": "A Charlie Brown Christmas", + "5726e5b1f1498d1400e8ef30": "1974", + "5726e5b1f1498d1400e8ef31": "Ryan Seacrest", + "5726e5b1f1498d1400e8ef32": "1954 to 1956", + "5726e5b1f1498d1400e8ef33": "ABC", + "5726e5b1f1498d1400e8ef34": "TLC", + "5726e671dd62a815002e9464": "General Hospital", + "5726e671dd62a815002e9465": "1975", + "5726e671dd62a815002e9466": "General Hospital", + "5726e671dd62a815002e9467": "The View and The Chew", + "5726e671dd62a815002e9468": "1963", + "5726e773f1498d1400e8ef6e": "X Games", + "5726e773f1498d1400e8ef6c": "2006", + "5726e773f1498d1400e8ef6b": "12:00 to 6:00 p.m. Eastern Time", + "5726e773f1498d1400e8ef6a": "NBA", + "5726e773f1498d1400e8ef6d": "Open Championship golf and The Wimbledon tennis tournaments", + "5726e860708984140094d579": "Frank Marx", + "5726e860708984140094d57a": "2 through 6", + "5726e860708984140094d57b": "1947", + "5726e860708984140094d57c": "VHF channel 7", + "5726e942f1498d1400e8efa0": "108", + "5726e942f1498d1400e8efa1": "two", + "5726e942f1498d1400e8efa2": "DuMont Television Network", + "5726e942f1498d1400e8efa3": "CBS and NBC", + "5726ea06dd62a815002e950a": "U.S. Supreme Court", + "5726ea06dd62a815002e950b": "Paramount Pictures", + "5726ea06dd62a815002e950c": "nine", + "5726ea06dd62a815002e950d": "CBS", + "5726ea06dd62a815002e950e": "Prudential Insurance Company of America", + "5726ec6ff1498d1400e8eff2": "Leonard Goldenson", + "5726ec6ff1498d1400e8eff3": "William S. Paley", + "5726ec6ff1498d1400e8eff4": "June 6, 1951", + "5726ed12708984140094d645": "1952", + "5726ed12708984140094d646": "February 9, 1953", + "5726ed12708984140094d647": "American Broadcasting-Paramount Theatres, Inc.", + "5726ed12708984140094d648": "1501 Broadway in Manhattan", + "5726edeff1498d1400e8f024": "August 10, 1948", + "5726edeff1498d1400e8f025": "October 1948", + "5726edeff1498d1400e8f026": "Mount Wilson", + "5726edeff1498d1400e8f027": "Prospect Studios", + "5726efdbdd62a815002e95c6": "September 30, 1960", + "5726efdbdd62a815002e95c7": "1960s", + "5726efdbdd62a815002e95c8": "William Hanna and Joseph Barbera", + "5726efdbdd62a815002e95c9": "1960s", + "5726f0865951b619008f82e5": "1959", + "5726f0865951b619008f82e6": "NBC", + "5726f0865951b619008f82e7": "1961", + "5726f0865951b619008f82e8": "1985", + "572734af708984140094dae3": "its circle logo", + "572734af708984140094dae4": "Troika Design Group", + "572734af708984140094dae5": "black-and-yellow", + "572734af708984140094dae6": "the dot", + "572735a15951b619008f86bf": "Pittard Sullivan", + "572735a15951b619008f86c0": "2015", + "572735a15951b619008f86c1": "We Love TV", + "572735a15951b619008f86c2": "production company vanity cards", + "572736625951b619008f86d1": "1993\u201394", + "572736625951b619008f86d2": "1995\u201396 season", + "572736625951b619008f86d3": "1983", + "572736625951b619008f86d4": "That Special Feeling", + "572736fc5951b619008f86d9": "1977", + "572736fc5951b619008f86da": "black", + "572736fc5951b619008f86db": "black", + "57273799f1498d1400e8f4be": "Paul Rand", + "57273799f1498d1400e8f4bf": "Bauhaus", + "57273799f1498d1400e8f4c0": "Herbert Bayer", + "57273799f1498d1400e8f4c1": "1963\u201364 season", + "5727387b5951b619008f86e9": "ABC Radio", + "5727387b5951b619008f86ea": "October 19, 2005", + "5727387b5951b619008f86eb": "six", + "57273954708984140094db05": "2004", + "57273954708984140094db06": "Dancing with the Stars", + "57273954708984140094db07": "Anne Sweeney", + "57273954708984140094db08": "NASCAR", + "57273a0d708984140094db0d": "2002", + "57273a0d708984140094db0e": "Michael Eisner", + "57273a0d708984140094db0f": "The Bachelor", + "57273a0d708984140094db10": "The Bachelorette", + "57273abef1498d1400e8f4da": "Time Warner Cable", + "57273abef1498d1400e8f4db": "ABC", + "57273abef1498d1400e8f4dc": "NBC", + "57273abef1498d1400e8f4dd": "May 2", + "57273b69dd62a815002e99d6": "2000", + "57273b69dd62a815002e99d7": "WB", + "57273b69dd62a815002e99d8": "CBS", + "57273c195951b619008f8721": "August 1999", + "57273c195951b619008f8722": "Regis Philbin", + "57273c195951b619008f8723": "Buena Vista Television", + "57273c195951b619008f8724": "Meredith Vieira", + "57273d19708984140094db3d": "July 31, 1995", + "57273d19708984140094db3e": "ABC Inc", + "57273d19708984140094db3f": "Knight Ridder", + "57273d19708984140094db40": "Robert Iger", + "57273d19708984140094db41": "Sports Night", + "57273dbbf1498d1400e8f508": "1965\u201366", + "57273dbbf1498d1400e8f509": "third place", + "57273dbbf1498d1400e8f50a": "Beating the Odds: The Untold Story Behind the Rise of ABC", + "57273ef15951b619008f8751": "May 1, 1953", + "57273ef15951b619008f8752": "7 West 66th Street", + "57273ef15951b619008f8753": "Baltimore", + "57273f9d708984140094db51": "Robert Kintner", + "57273f9d708984140094db52": "DuMont Television Network", + "57273f9d708984140094db53": "ABC-DuMont", + "57273f9d708984140094db54": "$5 million", + "5727403af1498d1400e8f526": "Paramount Pictures", + "5727403af1498d1400e8f527": "The Lone Ranger", + "5727403af1498d1400e8f528": "The Adventures of Ozzie and Harriet", + "57274118dd62a815002e9a1c": "Cheyenne", + "57274118dd62a815002e9a1d": "Sugarfoot", + "57274118dd62a815002e9a1e": "Walt Disney", + "57274118dd62a815002e9a1f": "Warner Bros. Presents", + "572741aaf1498d1400e8f53e": "Roy", + "572741aaf1498d1400e8f53f": "$500,000", + "572741aaf1498d1400e8f540": "1954", + "572741aaf1498d1400e8f541": "Disneyland", + "572742daf1498d1400e8f550": "Allen Shaw", + "572742daf1498d1400e8f551": "Harold L. Neal", + "572742daf1498d1400e8f552": "LOVE Radio", + "572742daf1498d1400e8f553": "seven", + "5727436af1498d1400e8f558": "1969", + "5727436af1498d1400e8f559": "Duel", + "5727436af1498d1400e8f55a": "1971", + "5727436af1498d1400e8f55b": "$400,000\u2013$450,000", + "572743fb708984140094db93": "1970s", + "572743fb708984140094db94": "CBS and NBC", + "572743fb708984140094db95": "behavioral and demographic", + "5727448b5951b619008f87a1": "Monday Night Football", + "5727448b5951b619008f87a2": "2006", + "5727448b5951b619008f87a3": "NBC", + "5727448b5951b619008f87a4": "15%\u201316%", + "57274633dd62a815002e9a4e": "1970", + "57274633dd62a815002e9a4f": "1972", + "57274633dd62a815002e9a50": "Worldvision Enterprises", + "572746d3dd62a815002e9a66": "cigarette advertising from all television and radio networks", + "572746d3dd62a815002e9a67": "January 2, 1971", + "572746d3dd62a815002e9a68": "Henry Plitt", + "572746d3dd62a815002e9a69": "Elton Rule", + "572747dd5951b619008f87a9": "1966", + "572747dd5951b619008f87aa": "Happy Days", + "572747dd5951b619008f87ab": "developing youth-oriented programming", + "572747dd5951b619008f87ac": "Paramount Pictures", + "572748745951b619008f87b1": "Fred Pierce", + "572748745951b619008f87b2": "Fred Silverman", + "572748745951b619008f87b3": "S.W.A.T.", + "572748745951b619008f87b4": "November 3, 1975", + "5727492f708984140094dbb5": "president of NBC's entertainment division", + "5727492f708984140094dbb6": "Laverne & Shirley", + "5727492f708984140094dbb7": "jiggle TV", + "572749d7dd62a815002e9a90": "Alex Haley", + "572749d7dd62a815002e9a91": "Aaron Spelling", + "572749d7dd62a815002e9a92": "nine", + "572749d7dd62a815002e9a93": "1976\u201377", + "572749d7dd62a815002e9a94": "Soap", + "57274a8cf1498d1400e8f5b4": "Roone Arledge", + "57274a8cf1498d1400e8f5b5": "ABC Sports", + "57274a8cf1498d1400e8f5b6": "7 Lincoln Square", + "57274a8cf1498d1400e8f5b7": "June 1979", + "57274baff1498d1400e8f5dc": "June 1978", + "57274baff1498d1400e8f5dd": "Hugh Downs", + "57274baff1498d1400e8f5de": "Barbara Walters", + "57274baff1498d1400e8f5df": "MCA Inc.", + "57274cac708984140094dbdd": "ABC Cable News", + "57274cac708984140094dbde": "ABC News Now", + "57274cac708984140094dbdf": "WJRT-TV", + "57274cac708984140094dbe0": "WJRT-TV and WTVG", + "57274d905951b619008f87e1": "Writers Guild of America", + "57274d905951b619008f87e2": "Duel", + "57274d905951b619008f87e3": "Caris & Co", + "57274e6a5951b619008f87f1": "ABC Entertainment", + "57274e6a5951b619008f87f2": "ABC Entertainment Group", + "57274e6a5951b619008f87f3": "Citadel Media", + "57274e6a5951b619008f87f4": "iTunes", + "57274f07708984140094dbed": "2004", + "57274f07708984140094dbee": "2004", + "57274f07708984140094dbef": "Fridays", + "57274f07708984140094dbf0": "Wednesdays", + "5727504b5951b619008f881d": "1970", + "5727504b5951b619008f881e": "Worldvision Enterprises", + "5727504b5951b619008f881f": "ABC Circle Films", + "5727504b5951b619008f8820": "Turner Broadcasting System", + "57275273dd62a815002e9b16": "Disney", + "57275273dd62a815002e9b17": "Buena Vista Television", + "57275273dd62a815002e9b18": "Buena Vista International Television", + "57275273dd62a815002e9b19": "Selznick library", + "57275339dd62a815002e9b28": "WABC-TV and WPVI-TV", + "57275339dd62a815002e9b29": "eight", + "57275339dd62a815002e9b2a": "235", + "57275339dd62a815002e9b2b": "96.26%", + "572754b5dd62a815002e9b44": "1946", + "572754b5dd62a815002e9b45": "the seal of the Federal Communications Commission", + "572754b5dd62a815002e9b46": "1946", + "57275573708984140094dc45": "2011", + "57275573708984140094dc46": "Extreme Makeover: Home Edition", + "57275573708984140094dc47": "HD", + "57275573708984140094dc48": "Litton's Weekend Aventure", + "57275650708984140094dc5f": "720p high definition", + "57275650708984140094dc60": "1080i HD", + "57275650708984140094dc61": "11", + "57275650708984140094dc62": "720p high definition", + "57275743f1498d1400e8f680": "Body of Proof", + "57275743f1498d1400e8f681": "Happy Endings", + "57275743f1498d1400e8f682": "NBC", + "57275743f1498d1400e8f683": "Body of Proof", + "5727590df1498d1400e8f6b6": "All My Children and One Life to Live", + "5727590df1498d1400e8f6b7": "Prospect Park", + "5727590df1498d1400e8f6b8": "Hulu", + "5727590df1498d1400e8f6b9": "The Revolution", + "5727590df1498d1400e8f6ba": "18\u201349", + "572759c1f1498d1400e8f6ca": "2004", + "572759c1f1498d1400e8f6cb": "CBS", + "572759c1f1498d1400e8f6cc": "The Goldbergs", + "572759c1f1498d1400e8f6cd": "The Neighbors", + "57275a505951b619008f889f": "The Middle and Modern Family", + "57275a505951b619008f88a0": "Dragon's Den", + "57275a505951b619008f88a1": "Sundays", + "57275a505951b619008f88a2": "Tim Allen", + "57275bfb708984140094dc97": "Daniel Burke", + "57275bfb708984140094dc98": "Thomas Murphy", + "57275bfb708984140094dc99": "NYPD Blue", + "57275bfb708984140094dc9a": "Steven Bochco", + "57275bfb708984140094dc9b": "ten", + "57275cb3f1498d1400e8f6da": "1993", + "57275cb3f1498d1400e8f6db": "DIC Entertainment", + "57275cb3f1498d1400e8f6dc": "Time Warner Cable", + "57275cb3f1498d1400e8f6dd": "23.63%", + "57275e125951b619008f88d7": "WLS", + "57275e125951b619008f88d8": "May 9, 1960", + "57275e125951b619008f88d9": "John Bassett", + "57275e125951b619008f88da": "CFTO-TV", + "57275e95f1498d1400e8f6f4": "Wide World of Sports", + "57275e95f1498d1400e8f6f5": "Edgar Scherick", + "57275e95f1498d1400e8f6f6": "Edgar Scherick through his company Sports Programs, Inc. and produced by a young Roone Arledge", + "57275e95f1498d1400e8f6f7": "Sports Programs, Inc.", + "57275f6ef1498d1400e8f706": "American Broadcasting Companies", + "57275f6ef1498d1400e8f707": "The Newlywed Game", + "57275f6ef1498d1400e8f708": "Dating Game", + "57275f6ef1498d1400e8f709": "1330 Avenue of the Americas", + "57276166dd62a815002e9bd8": "90%", + "57276166dd62a815002e9bd9": "Dynasty", + "57276166dd62a815002e9bda": "Mork & Mindy", + "57276166dd62a815002e9bdb": "Alpha Repertory Television Service", + "5727623a5951b619008f8921": "Infinity Broadcasting Corporation", + "5727623a5951b619008f8922": "Getty Oil", + "5727623a5951b619008f8923": "The Entertainment Channel", + "5727623a5951b619008f8924": "Arts & Entertainment Television", + "572763a8708984140094dcd9": "Daniel B. Burke", + "572763a8708984140094dcda": "chairman and CEO", + "572763a8708984140094dcdb": "$465 million", + "572763a8708984140094dcdc": "America's Funniest Home Videos", + "572763a8708984140094dcdd": "Home Improvement", + "572764855951b619008f8951": "General Hospital", + "572764855951b619008f8952": "The View and The Chew and the soap opera General Hospital", + "572764855951b619008f8953": "7:00 to 9:00 a.m", + "572764855951b619008f8954": "Jimmy Kimmel Live!", + "57276576dd62a815002e9c18": "New Jersey, Rhode Island and Delaware", + "57276576dd62a815002e9c19": "WBMA-LD", + "57276576dd62a815002e9c1a": "WBND-LD", + "57276576dd62a815002e9c1b": "WLQP-LP", + "57276690708984140094dd01": "ABC Circle Films", + "57276690708984140094dd02": "ABC Studios", + "57276690708984140094dd03": "ABC Television Center", + "57276690708984140094dd04": "ABC Television Center", + "5727678e5951b619008f8973": "Times Square Studios", + "5727678e5951b619008f8974": "Good Morning America and Nightline", + "5727678e5951b619008f8975": "Peter Jennings Way", + "5727678e5951b619008f8976": "World News Tonight", + "572768d9708984140094dd13": "ABC on Demand", + "572768d9708984140094dd14": "Hulu", + "572768d9708984140094dd15": "July 6, 2009", + "572768d9708984140094dd16": "27%", + "572769e85951b619008f8985": "the day after their original broadcast", + "572769e85951b619008f8986": "eight", + "572769e85951b619008f8987": "fast forwarding of accessed content", + "572769e85951b619008f8988": "January 7, 2014", + "57276a8f5951b619008f8995": "LoyalKaspar", + "57276a8f5951b619008f8996": "four", + "57276a8f5951b619008f8997": "ABC Modern", + "57276a8f5951b619008f8998": "ESPN", + "57276c64f1498d1400e8f7b2": "14", + "57276c64f1498d1400e8f7b3": "14", + "57276c64f1498d1400e8f7b4": "All-Channel Receiver Act", + "57276c64f1498d1400e8f7b5": "UHF", + "57276d7f708984140094dd3f": "Youngstown", + "57276d7f708984140094dd40": "five times", + "57276d7f708984140094dd41": "WTRF-TV", + "57276d7f708984140094dd42": "1980s", + "57276f82dd62a815002e9cd0": "Walt Disney Presents", + "57276f82dd62a815002e9cd1": "Desilu Productions", + "57276f82dd62a815002e9cd2": "its use of violence", + "57276f82dd62a815002e9cd3": "April 1959", + "5727705f5951b619008f89f3": "ABC Sunday Night Movie", + "5727705f5951b619008f89f4": "$15.5 million", + "5727705f5951b619008f89f5": "Hanna-Barbera", + "5727705f5951b619008f89f6": "The Jetsons", + "5727705f5951b619008f89f7": "April 1, 1963", + "572771a5f1498d1400e8f840": "ITT", + "572771a5f1498d1400e8f841": "Donald F. Turner", + "572771a5f1498d1400e8f842": "Department of Justice", + "572771a5f1498d1400e8f843": "January 1, 1968", + "57277373dd62a815002e9d24": "Capital Cities Communications", + "57277373dd62a815002e9d25": "$3.5 billion", + "57277373dd62a815002e9d26": "Warren Buffett", + "57277373dd62a815002e9d27": "E. W. Scripps Company", + "57277373dd62a815002e9d28": "12", + "572774cf5951b619008f8a51": "September 5, 1985", + "572774cf5951b619008f8a52": "Capital Cities/ABC, Inc.", + "572774cf5951b619008f8a53": "president of ABC's broadcasting division", + "572774cf5951b619008f8a54": "Michael P. Millardi", + "572774cf5951b619008f8a55": "Roone Arledge", + "57277585708984140094de2b": "Laverne & Shirley", + "57277585708984140094de2c": "Happy Days and Three's Company", + "57277585708984140094de2d": "NBC", + "57277585708984140094de2e": "The Love Boat", + "57277585708984140094de2f": "comedies and family-oriented", + "57277632f1498d1400e8f8c4": "TGIF", + "57277632f1498d1400e8f8c5": "Thank Goodness It's Funny", + "57277632f1498d1400e8f8c6": "Miller-Boyett Productions", + "57277632f1498d1400e8f8c7": "Warner Bros.", + "572776e85951b619008f8a7f": "seven", + "572776e85951b619008f8a80": "Charly", + "572776e85951b619008f8a81": "Ralph Nelson", + "572776e85951b619008f8a82": "1985", + "572776e85951b619008f8a83": "Redwood City, California", + "5727780a5951b619008f8a9d": "westerns and detective series", + "5727780a5951b619008f8a9e": "500%", + "5727780a5951b619008f8a9f": "between 10% and 18%", + "5727780a5951b619008f8aa0": "Ollie Treiz", + "5727780a5951b619008f8aa1": "Dick Clark", + "57277944f1498d1400e8f90a": "counterprogramming against its competitors", + "57277944f1498d1400e8f90b": "Zorro", + "57277944f1498d1400e8f90c": "Life", + "57277944f1498d1400e8f90d": "detective shows", + "57277af2708984140094dec3": "WATCH ABC", + "57277af2708984140094dec4": "New York City O&O WABC-TV and Philadelphia O&O WPVI-TV", + "57277af2708984140094dec5": "Hearst Television", + "57277af2708984140094dec6": "WatchESPN", + "57277bfc708984140094ded9": "The Sinclair Broadcast Group", + "57277bfc708984140094deda": "WABM-DT2/WDBB-DT2", + "57277bfc708984140094dedb": "E. W. Scripps Company", + "57277bfc708984140094dedc": "28", + "57277bfc708984140094dedd": "28", + "57277cf6dd62a815002e9e76": "Start Here", + "57277cf6dd62a815002e9e77": "Troika", + "57277cf6dd62a815002e9e78": "entertainment", + "57277cf6dd62a815002e9e79": "entertainment", + "57277de9dd62a815002e9ea4": "WFTS-TV and WWSB", + "57277de9dd62a815002e9ea5": "KMBC-TV and KQTV", + "57277de9dd62a815002e9ea6": "WZZM and WOTV", + "57277de9dd62a815002e9ea7": "WTSP", + "57269e8a5951b619008f77f5": "Mongol Empire", + "57269e8a5951b619008f77f6": "many of the nomadic tribes of Northeast Asia", + "57269e8a5951b619008f77f7": "Khwarezmian and Xia controlled lands", + "57269e8a5951b619008f77f8": "Central Asia and China", + "57269e8a5951b619008f77f9": "Western Xia and Jin dynasties", + "5726a00d708984140094cc25": "\u00d6gedei Khan", + "5726a00d708984140094cc26": "1227", + "5726a00d708984140094cc27": "Western Xia", + "5726a00d708984140094cc28": "his sons and grandsons", + "5726a00d708984140094cc29": "Mongolia", + "5726a21bf1498d1400e8e578": "Del\u00fc\u00fcn Boldog", + "5726a21bf1498d1400e8e579": "Yes\u00fcgei", + "5726a21bf1498d1400e8e57a": "1162", + "5726a21bf1498d1400e8e57b": "Tem\u00fcjin-\u00fcge", + "5726a340dd62a815002e8bbc": "Tem\u00fclen", + "5726a340dd62a815002e8bbd": "Hasar, Hachiun, and Tem\u00fcge", + "5726a340dd62a815002e8bbe": "a marriage", + "5726a340dd62a815002e8bbf": "Khongirad", + "5726a340dd62a815002e8bc0": "Dai Setsen", + "5726a4a9708984140094ccb7": "Begter", + "5726a4a9708984140094ccb8": "Temujin's mother Hoelun", + "5726a4a9708984140094ccb9": "Khasar", + "5726a4a9708984140094ccba": "one hunting excursion", + "5726a5f65951b619008f7903": "Tayichi'ud", + "5726a5f65951b619008f7904": "a cangue", + "5726a5f65951b619008f7905": "Jelme and Bo'orchu", + "5726a5f65951b619008f7906": "Jelme and Bo'orchu", + "5726a5f65951b619008f7907": "a river crevice", + "5726a784708984140094ccff": "arranged marriages", + "5726a784708984140094cd00": "Hoelun", + "5726a784708984140094cd01": "Chinese dynasties", + "5726a784708984140094cd02": "the need for alliances", + "5726a8d4dd62a815002e8c34": "Onggirat", + "5726a8d4dd62a815002e8c35": "Merkits", + "5726a8d4dd62a815002e8c36": "Jamukha", + "5726a8d4dd62a815002e8c37": "Jochi", + "5726a8d4dd62a815002e8c38": "1185\u20131226", + "5726a9ed5951b619008f7969": "three", + "5726a9ed5951b619008f796a": "Chagatai", + "5726a9ed5951b619008f796b": "1241", + "5726a9ed5951b619008f796c": "Chagatai", + "5726a9ed5951b619008f796d": "at least six", + "5726ab47f1498d1400e8e6a2": "sworn brother or blood brother", + "5726ab47f1498d1400e8e6a3": "Toghrul", + "5726ab47f1498d1400e8e6a4": "Jadaran", + "5726ab47f1498d1400e8e6a5": "20,000", + "5726ab47f1498d1400e8e6a6": "Jamukha", + "5726acc1f1498d1400e8e6ca": "traditional Mongolian aristocracy", + "5726acc1f1498d1400e8e6cb": "Kokochu", + "5726acc1f1498d1400e8e6cc": "1186", + "5726acc1f1498d1400e8e6cd": "Battle of Dalan Balzhut", + "5726acc1f1498d1400e8e6ce": "Qara Khitai", + "5726ae32708984140094cdab": "Yassa code", + "5726ae32708984140094cdac": "wealth", + "5726ae32708984140094cdad": "orphans", + "5726ae32708984140094cdae": "wealth", + "5726af765951b619008f7a51": "Jochi", + "5726af765951b619008f7a52": "Jamukha", + "5726af765951b619008f7a53": "Jamukha", + "5726af765951b619008f7a54": "Keraite", + "5726b0985951b619008f7a91": "Naimans", + "5726b0985951b619008f7a92": "1201", + "5726b0985951b619008f7a93": "universal ruler", + "5726b0985951b619008f7a94": "Subutai", + "5726b0985951b619008f7a95": "1206", + "5726b1d95951b619008f7acd": "friendship", + "5726b1d95951b619008f7ace": "he did not want disloyal men in his army", + "5726b1d95951b619008f7acf": "reunion", + "5726b1d95951b619008f7ad0": "noble", + "5726b879708984140094cf01": "the Chinese", + "5726b879708984140094cf02": "Jamukha", + "5726b879708984140094cf03": "Khasar", + "5726b879708984140094cf04": "military strategies showed a deep interest in gathering good intelligence and understanding the motivations of his rivals, exemplified by his extensive spy network and Yam route systems", + "5726b879708984140094cf05": "Wang Khan", + "5726b9e15951b619008f7bf1": "1206", + "5726b9e15951b619008f7bf2": "Khuruldai", + "5726b9e15951b619008f7bf3": "Khagan", + "5726b9e15951b619008f7bf4": "\u00d6gedei", + "5726b9e15951b619008f7bf5": "Khuruldai, a council of Mongol chiefs", + "5726bb645951b619008f7c3b": "Jin dynasty", + "5726bb645951b619008f7c3c": "Ming-Tan", + "5726bb645951b619008f7c3d": "1215", + "5726bb645951b619008f7c3e": "Kaifeng", + "5726bb645951b619008f7c3f": "\u00d6gedei Khan", + "5726bd655951b619008f7c9f": "Genghis Khan", + "5726bd655951b619008f7ca0": "Liao dynasty", + "5726bd655951b619008f7ca1": "20,000", + "5726bd655951b619008f7ca2": "Jebe", + "5726bd655951b619008f7ca3": "The Arrow", + "5726bf135951b619008f7ce9": "internal revolt", + "5726bf135951b619008f7cea": "west of Kashgar", + "5726bf135951b619008f7ceb": "as far west as Lake Balkhash", + "5726bf135951b619008f7cec": "Khwarezmia", + "5726bf135951b619008f7ced": "Muslim", + "5726c0c5dd62a815002e8f76": "Shah Ala ad-Din Muhammad", + "5726c0c5dd62a815002e8f77": "Inalchuq", + "5726c0c5dd62a815002e8f78": "two Mongols and a Muslim) to meet the Shah himself instead of the governor Inalchuq", + "5726c0c5dd62a815002e8f79": "100,000", + "5726c0c5dd62a815002e8f7a": "Silk Road", + "5726c20fdd62a815002e8fa6": "Tien Shan mountains", + "5726c20fdd62a815002e8fa7": "three", + "5726c20fdd62a815002e8fa8": "southeast part of Khwarzemia", + "5726c20fdd62a815002e8fa9": "Jochi", + "5726c20fdd62a815002e8faa": "Samarkand", + "5726c3b3708984140094d0cf": "fragmentation", + "5726c3b3708984140094d0d0": "Otrar", + "5726c3b3708984140094d0d1": "silver", + "5726c3b3708984140094d0d2": "fled", + "5726c3b3708984140094d0d3": "Subutai and Jebe", + "5726c4c8708984140094d0f5": "Samarkand", + "5726c4c8708984140094d0f6": "Bukhara", + "5726c4c8708984140094d0f7": "a river through the Khwarezmid emperor's birthplace", + "5726c61ff1498d1400e8eae2": "captured enemies", + "5726c61ff1498d1400e8eae3": "reneged", + "5726c61ff1498d1400e8eae4": "pyramids of severed heads", + "5726c7a85951b619008f7ddd": "opened the gates", + "5726c7a85951b619008f7dde": "Turkish defenders", + "5726c7a85951b619008f7ddf": "artisans and craftsmen", + "5726c7a85951b619008f7de0": "the flail of God", + "5726c7a85951b619008f7de1": "young men", + "5726c9b0dd62a815002e9046": "1220", + "5726c9b0dd62a815002e9047": "Subutai", + "5726c9b0dd62a815002e9048": "Russia", + "5726c9b0dd62a815002e9049": "Battle of Kalka River", + "5726c9b0dd62a815002e904a": "Mstislav the Bold of Halych and Mstislav III", + "57272bcb5951b619008f8683": "Batu", + "57272bcb5951b619008f8684": "cavalry", + "57272bcb5951b619008f8685": "Transoxiana", + "57272bcb5951b619008f8686": "1225", + "57272bcb5951b619008f8687": "Samarkand", + "57272ce1f1498d1400e8f43a": "1226", + "57272ce1f1498d1400e8f43b": "autumn", + "57272ce1f1498d1400e8f43c": "Mongols", + "57272ce1f1498d1400e8f43d": "Yellow River", + "57272ce1f1498d1400e8f43e": "a line of five stars", + "57272dd55951b619008f8697": "Ning Hia", + "57272dd55951b619008f8698": "Ma Jianlong", + "57272dd55951b619008f8699": "arrows", + "57272dd55951b619008f869a": "Liupanshan", + "57272dd55951b619008f869b": "ordered the entire imperial family to be executed", + "57272ec7f1498d1400e8f44e": "Jochi", + "57272ec7f1498d1400e8f44f": "\u00d6gedei", + "57272ec7f1498d1400e8f450": "Secret History of the Mongols", + "57272ec7f1498d1400e8f451": "\u00d6gedei", + "57272ff2708984140094dabd": "Chagatai and Jochi", + "57272ff2708984140094dabe": "Tolui", + "57272ff2708984140094dabf": "Tolui", + "57272ff2708984140094dac0": "\u00d6gedei", + "5727311d5951b619008f86ab": "1226", + "5727311d5951b619008f86ac": "Khorasan", + "5727311d5951b619008f86ad": "Urgench", + "5727311d5951b619008f86ae": "Sultan Muhammad, brought this land to life and gave assistance and support to the Muslims", + "5727311d5951b619008f86af": "the accuracy of this story is questionable", + "57273249f1498d1400e8f46a": "Yinchuan", + "57273249f1498d1400e8f46b": "fell from his horse while hunting", + "57273249f1498d1400e8f46c": "arrow", + "57273249f1498d1400e8f46d": "Western Xia", + "57273249f1498d1400e8f46e": "Oirads", + "572732f8f1498d1400e8f474": "without markings", + "572732f8f1498d1400e8f475": "Khentii Aimag", + "572732f8f1498d1400e8f476": "Onon River", + "572732f8f1498d1400e8f477": "The Genghis Khan Mausoleum", + "57273455f1498d1400e8f48c": "Edsen Khoroo", + "57273455f1498d1400e8f48d": "Dongshan Dafo Dian", + "57273455f1498d1400e8f48e": "Tibetan monastery of Kumbum Monastery or Ta'er Shi near Xining", + "57273455f1498d1400e8f48f": "early 1954", + "57273455f1498d1400e8f490": "Red Guards", + "57273581708984140094daeb": "October 6, 2004", + "57273581708984140094daec": "river", + "57273581708984140094daed": "Gilgamesh of Uruk and Atilla the Hun", + "57273581708984140094daee": "horses", + "572736bff1498d1400e8f4b5": "Genghis Khan", + "572736bff1498d1400e8f4b4": "the Yassa", + "572736bff1498d1400e8f4b6": "meritocracy", + "572736bff1498d1400e8f4b7": "Genghis Khan and his family", + "572736bff1498d1400e8f4b8": "Muhammad Khan", + "57273887dd62a815002e99a2": "tax exemptions", + "57273887dd62a815002e99a3": "Ong Khan", + "57273887dd62a815002e99a4": "practiced religious tolerance because Mongol tradition had long held that religion was a personal concept, and not subject to law or interference", + "57273887dd62a815002e99a5": "Shamanist, Buddhist or Christian", + "572739a75951b619008f86f7": "T\u00f6regene Khatun", + "572739a75951b619008f86f8": "Pax Mongolica", + "572739a75951b619008f86f9": "the Chinese", + "572739a75951b619008f86fa": "a civil state", + "57273b1a5951b619008f8709": "Chu'Tsai", + "57273b1a5951b619008f870a": "they were nomads", + "57273b1a5951b619008f870b": "Jin", + "57273b1a5951b619008f870c": "Khitan rulers", + "57273c01f1498d1400e8f4e2": "Muqali, Jebe and Subutai", + "57273c01f1498d1400e8f4e3": "Karakorum", + "57273c01f1498d1400e8f4e4": "Muqali", + "57273c01f1498d1400e8f4e5": "Subutai and Jebe", + "57273c01f1498d1400e8f4e6": "unwavering loyalty", + "57273d06f1498d1400e8f4f6": "certain rivers", + "57273d06f1498d1400e8f4f7": "Muslim and Chinese", + "57273d06f1498d1400e8f4f8": "ambush and counterattack", + "57273d06f1498d1400e8f4f9": "driving them in front of the army", + "57273dccdd62a815002e99fa": "Sea of Japan", + "57273dccdd62a815002e99fb": "Caspian Sea", + "57273dccdd62a815002e99fc": "\u00d6gedei Khan", + "57273dccdd62a815002e99fd": "1279", + "57273eecf1498d1400e8f51e": "Silk Road", + "57273eecf1498d1400e8f51f": "Turkey", + "57273eecf1498d1400e8f520": "tolerant", + "57273eecf1498d1400e8f521": "increased", + "5727404b708984140094db59": "1990s", + "5727404b708984140094db5a": "uniting warring tribes", + "5727404b708984140094db5b": "\"Genghis Khan's children", + "5727404b708984140094db5c": "his butchery is exaggerated", + "5727404b708984140094db5d": "Genghis Khan's children\"", + "57274126dd62a815002e9a24": "t\u00f6gr\u00f6g", + "57274126dd62a815002e9a25": "Genghis Khan", + "57274126dd62a815002e9a26": "Chinggis Khaan International Airport", + "57274126dd62a815002e9a27": "to avoid trivialization", + "57274126dd62a815002e9a28": "Ulaanbaatar", + "5727515af1498d1400e8f63a": "Ikh Zasag", + "5727515af1498d1400e8f63b": "illegal matters related to corruption and bribery", + "5727515af1498d1400e8f63c": "Elbegdorj", + "5727515af1498d1400e8f63d": "traditional Mongolian script", + "57275250708984140094dc25": "Inner Mongolia region", + "57275250708984140094dc26": "around 5 million", + "57275250708984140094dc27": "Kublai Khan", + "57275250708984140094dc28": "Yuan dynasty", + "57275250708984140094dc29": "his grandson", + "572753af708984140094dc2f": "Iran", + "572753af708984140094dc30": "three-fourths", + "572753af708984140094dc31": "10 to 15 million", + "572754cd5951b619008f8863": "Hulagu Khan", + "572754cd5951b619008f8864": "Mamluks of Egypt", + "572754cd5951b619008f8865": "Ghazan Khan", + "572754cd5951b619008f8866": "1237", + "572754cd5951b619008f8867": "Novgorod and Pskov", + "572756715951b619008f8877": "Mughal emperors", + "572756715951b619008f8878": "Timur", + "572756715951b619008f8879": "Nishapur", + "5727580bf1498d1400e8f69a": "tenggis", + "5727580bf1498d1400e8f69b": "Lake Baikal", + "5727580bf1498d1400e8f69c": "right", + "5727580bf1498d1400e8f69d": "Genghis", + "5727580bf1498d1400e8f69e": "Chinggis", + "572758c3dd62a815002e9b78": "Chinggis Khaan", + "572758c3dd62a815002e9b79": "in variety of ways", + "572758c3dd62a815002e9b7a": "simplified Chinese: \u94c1\u6728\u771f", + "572758c3dd62a815002e9b7b": "Chinghiz, Chinghis, and Chingiz", + "572758c3dd62a815002e9b7c": "Ch\u00e9ngj\u00eds\u012b H\u00e1n", + "5726d8bd708984140094d35b": "pharma", + "5726d8bd708984140094d35c": "tobacco and patent medicines", + "5726d8bd708984140094d35d": "sorcery or even poison", + "5726d8bd708984140094d35e": "outdated or only approproriate", + "5726d8bd708984140094d35f": "many other herbs not listed", + "5726d9935951b619008f7fed": "healthcare", + "5726d9935951b619008f7fee": "optimal", + "5726d9935951b619008f7fef": "optimisation of a drug", + "5726d9935951b619008f7ff0": "optimisation of a drug treatment for an individual", + "5726d9935951b619008f7ff1": "specialised education and training who perform various roles to ensure optimal health outcomes for their patients through the quality use of medicines", + "5726da89dd62a815002e92b2": "The GPhC", + "5726da89dd62a815002e92b3": "General Pharmaceutical Council", + "5726da89dd62a815002e92b4": "manage the pharmacy department and specialised areas in pharmacy practice", + "5726da89dd62a815002e92b5": "health care", + "5726da89dd62a815002e92b6": "to manage the pharmacy department and specialised areas in pharmacy practice", + "5726db5add62a815002e92d5": "writing a five volume book", + "5726db5add62a815002e92d6": "De Materia Medica", + "5726db5add62a815002e92d7": "materia medica", + "5726db5add62a815002e92d4": "Diocles of Carystus", + "5726db5add62a815002e92d8": "middle eastern scientists", + "5726dcbddd62a815002e9320": "highly respected", + "5726dcbddd62a815002e9321": "Taih\u014d Code", + "5726dcbddd62a815002e9322": "Meiji Restoration", + "5726dcbddd62a815002e9323": "Ranked positions", + "5726dcbddd62a815002e9324": "above", + "5726ddf6f1498d1400e8ee04": "botany and chemistry", + "5726ddf6f1498d1400e8ee05": "Muhammad ibn Zakar\u012bya R\u0101zi", + "5726ddf6f1498d1400e8ee06": "Abu al-Qasim al-Zahrawi", + "5726ddf6f1498d1400e8ee08": "Abu al-Qasim al-Zahrawi", + "5726ddf6f1498d1400e8ee07": "sodium carbonate and potassium carbonate", + "5726deed5951b619008f80c5": "15th century", + "5726deed5951b619008f80c6": "Church of Santa Maria Novella in Florence, Italy", + "5726deed5951b619008f80c7": "keeping albarellos from the 16th and 17th centuries, old prescription books and antique drugs", + "5726deed5951b619008f80c8": "old prescription books and antique drugs", + "5726deed5951b619008f80c9": "1221", + "5726e08e5951b619008f810f": "pharmacy legislation", + "5726e08e5951b619008f8110": "dealing with patients' prescriptions and patient safety issues", + "5726e08e5951b619008f8111": "automation", + "5726e08e5951b619008f8112": "patients' prescriptions and patient safety issues", + "5726e08e5951b619008f8113": "the dispensary", + "5726e179dd62a815002e93ae": "pharmacy practice residency", + "5726e179dd62a815002e93af": "various disciplines of pharmacy", + "5726e179dd62a815002e93b0": "patient compliance issues", + "5726e179dd62a815002e93b1": "clinical pharmacists", + "5726e313f1498d1400e8eeb2": "within the premises of the hospital", + "5726e313f1498d1400e8eeb3": "unit-dose, or a single dose of medicine", + "5726e313f1498d1400e8eeb4": "high risk preparations", + "5726e313f1498d1400e8eeb5": "high cost of medications and drug-related technology", + "5726e313f1498d1400e8eeb6": "more specialized medications", + "5726e3c4dd62a815002e9404": "direct patient care services that optimizes the use of medication and promotes health, wellness, and disease prevention", + "5726e3c4dd62a815002e9405": "inside hospitals and clinics", + "5726e3c4dd62a815002e9406": "physicians and other healthcare professionals", + "5726e3c4dd62a815002e9407": "patient care rounds drug product selection", + "5726e3c4dd62a815002e9408": "all health care settings", + "5726e5c95951b619008f81cb": "creating a comprehensive drug therapy plan for patient-specific problems", + "5726e5c95951b619008f81cc": "an evaluation of the appropriateness of the drug therapy", + "5726e5c95951b619008f81cd": "drug choice, dose, route, frequency, and duration of therapy", + "5726e5c95951b619008f81ce": "potential drug interactions, adverse drug reactions, and assess patient drug allergies", + "5726e985dd62a815002e94da": "full independent prescribing authority", + "5726e985dd62a815002e94db": "North Carolina and New Mexico", + "5726e985dd62a815002e94dc": "2011", + "5726e985dd62a815002e94dd": "Board Certified Ambulatory Care Pharmacist", + "5726e985dd62a815002e94de": "VA, the Indian Health Service, and NIH", + "5726ea985951b619008f8261": "medication regimen review", + "5726ea985951b619008f8262": "nursing homes", + "5726ea985951b619008f8263": "Omnicare, Kindred Healthcare and PharMerica", + "5726ea985951b619008f8264": "many elderly people are now taking numerous medications but continue to live outside of institutional settings", + "5726ea985951b619008f8265": "employ consultant pharmacists and/or provide consulting services", + "5726eb4b5951b619008f826b": "about the year 2000", + "5726eb4b5951b619008f826c": "brick-and-mortar community pharmacies", + "5726eb4b5951b619008f826d": "online pharmacies", + "5726eb4b5951b619008f826e": "overhear about the drugs that they take", + "5726eb4b5951b619008f826f": "the method by which the medications are requested and received", + "5726ed6cf1498d1400e8f00c": "to avoid the \"inconvenience\" of visiting a doctor or to obtain medications which their doctors were unwilling to prescribe", + "5726ed6cf1498d1400e8f00d": "Many customers", + "5726ed6cf1498d1400e8f00e": "potentially dangerous", + "5726ed6cf1498d1400e8f00f": "sell prescription drugs", + "5726ed6cf1498d1400e8f010": "sell prescription drugs and require a valid prescription", + "5726edecdd62a815002e957e": "ease with which people, youth in particular, can obtain controlled substances", + "5726edecdd62a815002e957f": "it must be issued for a legitimate medical purpose by a licensed practitioner acting in the course of legitimate doctor-patient relationship", + "5726ef73f1498d1400e8f05e": "ease with which people, youth in particular, can obtain controlled substances", + "5726ef73f1498d1400e8f05f": "legitimate doctor-patient relationship", + "5726ef73f1498d1400e8f060": "ensure that the prescription is valid", + "5726ef73f1498d1400e8f061": "individual state laws", + "5726ef73f1498d1400e8f062": "Vicodin", + "5726f0e35951b619008f82f7": "to reduce consumer costs", + "5726f0e35951b619008f82f8": "Canada", + "5726f0e35951b619008f82f9": "international drug suppliers", + "5726f0e35951b619008f82fa": "There is no known case of any U.S. citizens buying Canadian drugs for personal use with a prescription, who has ever been charged by authorities", + "5726f0e35951b619008f82fb": "legalize importation of medications from Canada and other countries", + "5726f2375951b619008f830f": "pharmacy practice science and applied information science", + "5726f2375951b619008f8310": "information technology departments or for healthcare information technology vendor companies", + "5726f2375951b619008f8311": "major national and international patient information projects and health system interoperability goals", + "5726f2375951b619008f8312": "practice areas", + "5726f2375951b619008f8313": "quickly", + "5726f36cdd62a815002e95fe": "specialty drugs", + "5726f36cdd62a815002e95ff": "19 of 28", + "5726f36cdd62a815002e9600": "cancer, hepatitis, and rheumatoid arthritis", + "5726f36cdd62a815002e9601": "high cost injectable, oral, infused, or inhaled", + "5726f36cdd62a815002e9602": "lab monitoring, adherence counseling", + "5726f48df1498d1400e8f0da": "separately from physicians", + "5726f48df1498d1400e8f0db": "pharmacists", + "5726f48df1498d1400e8f0dc": "American Medical Association (AMA) Code of Ethics", + "5726f48df1498d1400e8f0dd": "7 to 10 percent", + "5726f48df1498d1400e8f0de": "supply scheduled pharmaceuticals to the public", + "5726f635dd62a815002e9657": "United Kingdom", + "5726f635dd62a815002e9656": "rural areas in the United Kingdom", + "5726f635dd62a815002e9658": "1.6 kilometres", + "5726f635dd62a815002e9659": "1.6 kilometres", + "5726f7715951b619008f838d": "high risk of a conflict of interest and/or the avoidance of absolute powers", + "5726f7715951b619008f838e": "financial self-interest", + "5726f7715951b619008f838f": "checks and balances system of the U.S. and many other governments", + "5726f7715951b619008f8391": "sell more medications to the patient", + "5726f7715951b619008f8390": "conflicts with the patient's interest in obtaining cost-effective medication", + "5726f868dd62a815002e9684": "more integral within the health care system", + "5726f868dd62a815002e9685": "dispensing medication, pharmacists are increasingly expected to be compensated for their patient care skills", + "5726f868dd62a815002e9686": "clinical services that pharmacists can provide for their patients", + "5726f868dd62a815002e9687": "Medication Therapy Management", + "5726f868dd62a815002e9688": "increased patient health outcomes and decreased costs to the health care system", + "5726f96ddd62a815002e9698": "Alberta and British Columbia", + "5726f96ddd62a815002e9699": "the Australian Government", + "5726f96ddd62a815002e969a": "medicine use reviews", + "5726f96ddd62a815002e969b": "pharmaceutical care or clinical pharmacy", + "5726f96ddd62a815002e969c": "Doctor of Pharmacy", + "5726fa525951b619008f83f7": "mortar and pestle and the \u211e (recipere) character", + "5726fa525951b619008f83f8": "The show globe", + "5726fa525951b619008f83f9": "Netherlands", + "5726fa525951b619008f83fa": "Germany and Austria", + "5726fa525951b619008f83fb": "France, Argentina, the United Kingdom, Belgium, Ireland, Italy, Spain, and India", + "5726e65e708984140094d53d": "a system of many biological structures and processes within an organism that protects against disease", + "5726e65e708984140094d53e": "disease", + "5726e65e708984140094d53f": "innate immune system versus the adaptive immune system, or humoral immunity versus cell-mediated immunity", + "5726e65e708984140094d540": "neuroimmune system", + "5726eb76f1498d1400e8efda": "a system of many biological structures and processes within an organism that protects against disease", + "5726eb76f1498d1400e8efdb": "disease", + "5726eb76f1498d1400e8efdc": "innate immune system versus the adaptive immune system, or humoral immunity versus cell-mediated immunity", + "5728eff82ca10214002daadc": "disease", + "5728eff82ca10214002daadd": "pathogens", + "5728eff82ca10214002daade": "neuroimmune system", + "5728eff82ca10214002daadf": "the blood\u2013brain barrier, blood\u2013cerebrospinal fluid barrier, and similar fluid\u2013brain barriers", + "572a14af3f37b319004786c1": "pathogens", + "572a14af3f37b319004786c3": "innate immune system versus the adaptive immune system, or humoral immunity versus cell-mediated immunity", + "572a14af3f37b319004786c2": "humoral immunity versus cell-mediated immunity", + "572a14af3f37b319004786c4": "neuroimmune system", + "5726eb785951b619008f8275": "neutralization by the immune system", + "5726eb785951b619008f8276": "rudimentary", + "5726eb785951b619008f8277": "eukaryotes", + "5726eb785951b619008f8278": "vaccination", + "572a135daf94a219006aa79f": "rudimentary", + "572a135daf94a219006aa7a0": "defensins", + "572a135daf94a219006aa7a1": "vaccination", + "572a135daf94a219006aa7a2": "Adaptive (or acquired) immunity", + "5726eb8bf1498d1400e8efe2": "autoimmune diseases, inflammatory diseases and cancer", + "5726eb8bf1498d1400e8efe3": "when the immune system is less active than normal", + "5726eb8bf1498d1400e8efe4": "recurring and life-threatening infections", + "5726eb8bf1498d1400e8efe5": "recurring and life-threatening infections", + "5726eb8bf1498d1400e8efe6": "Hashimoto's thyroiditis", + "5728f2e26aef051400154896": "Immunodeficiency", + "5728f2e26aef051400154897": "autoimmunity", + "5728f2e26aef051400154898": "Immunology", + "5728f2e26aef051400154899": "HIV/AIDS", + "5726f8abf1498d1400e8f166": "the plague of Athens", + "5726f8abf1498d1400e8f167": "scorpion", + "5726f8abf1498d1400e8f168": "Louis Pasteur", + "5726f8abf1498d1400e8f169": "Walter Reed", + "5728f3724b864d1900165116": "Robert Koch", + "5728f3724b864d1900165117": "microorganisms", + "5728f3724b864d1900165118": "yellow fever virus", + "5728f3724b864d1900165119": "430 BC", + "5726f8aef1498d1400e8f16e": "immunological memory", + "5726f8aef1498d1400e8f16f": "innate immune system", + "5726f8aef1498d1400e8f170": "adaptive immune system", + "5728f6446aef0514001548e4": "Innate immune systems", + "5728f6446aef0514001548e5": "adaptive immune system", + "5728f6446aef0514001548e6": "immunological memory", + "5728f6446aef0514001548e7": "physical barriers", + "5728f7774b864d190016512e": "self and non-self molecules", + "5728f7774b864d190016512f": "self molecules", + "5728f7774b864d1900165130": "non-self molecules", + "5728f7774b864d1900165131": "antigens", + "5728f7774b864d1900165132": "specific immune receptors", + "5728f9882ca10214002dab5a": "pattern recognition receptors", + "5728f9882ca10214002dab5b": "innate immune system", + "5728f9882ca10214002dab5c": "microorganisms", + "5728f9882ca10214002dab5d": "non-specific", + "5728fb002ca10214002dab6a": "exoskeleton", + "5728fb002ca10214002dab6b": "waxy cuticle", + "5728fb002ca10214002dab6c": "coughing and sneezing", + "5728fb002ca10214002dab6d": "mucus", + "5728fb002ca10214002dab6e": "tears and urine", + "5728fc2eaf94a219006a9ec7": "\u03b2-defensins", + "5728fc2eaf94a219006a9ec8": "lysozyme and phospholipase A2", + "5728fc2eaf94a219006a9ec9": "defensins and zinc", + "5728fc2eaf94a219006a9eca": "gastric acid and proteases", + "5728fc2eaf94a219006a9ecb": "menarche", + "5728fd206aef05140015494c": "commensal flora", + "5728fd206aef05140015494d": "fungi", + "5728fd206aef05140015494e": "pure cultures of the lactobacilli", + "5728fd206aef05140015494f": "pH or available iron", + "572900f73f37b31900477f69": "Inflammation", + "572900f73f37b31900477f6a": "increased blood flow into tissue", + "572900f73f37b31900477f6b": "eicosanoids and cytokines", + "572900f73f37b31900477f6c": "prostaglandins", + "572900f73f37b31900477f6d": "interleukins", + "572905ce1d04691400778f83": "phagocytes", + "572905ce1d04691400778f84": "cytokines", + "572905ce1d04691400778f85": "phagosome", + "572905ce1d04691400778f86": "phagolysosome", + "572905ce1d04691400778f87": "acquiring nutrients", + "5729081d3f37b31900477fab": "Neutrophils and macrophages", + "5729081d3f37b31900477fac": "Neutrophils", + "5729081d3f37b31900477fad": "50% to 60%", + "5729081d3f37b31900477fae": "chemotaxis", + "5729081d3f37b31900477faf": "interleukin 1", + "572908c13f37b31900477fbd": "Leukocytes", + "572908c13f37b31900477fbe": "Leukocytes", + "572908c13f37b31900477fbf": "adaptive", + "572908c13f37b31900477fc0": "macrophages, neutrophils, and dendritic cells", + "5729efab3f37b319004785cf": "Dendritic cells", + "5729efab3f37b319004785d0": "neuronal dendrites", + "5729efab3f37b319004785d1": "T cells", + "5729efab3f37b319004785d2": "T cells", + "5729f06f1d04691400779674": "missing self", + "5729f06f1d04691400779673": "Natural killer cells", + "5729f06f1d04691400779675": "MHC I", + "5729f06f1d04691400779676": "killer cell immunoglobulin receptors", + "5729f12e3f37b319004785e1": "early vertebrates", + "5729f12e3f37b319004785e2": "antigen presentation", + "5729f12e3f37b319004785e3": "specific pathogens or pathogen-infected cells", + "5729f1fcaf94a219006aa6d3": "killer T cell and the helper T cell", + "5729f1fcaf94a219006aa6d4": "regulatory T cells", + "5729f1fcaf94a219006aa6d5": "Class I MHC", + "5729f1fcaf94a219006aa6d6": "Class II MHC molecules", + "5729f1fcaf94a219006aa6d7": "\u03b3\u03b4 T cells", + "5729f39a6aef05140015514c": "Killer T cells", + "5729f39a6aef05140015514e": "CD8", + "5729f39a6aef05140015514d": "TCR", + "5729f39a6aef051400155150": "granulysin", + "5729f39a6aef05140015514f": "perforin", + "5729f4b41d0469140077968b": "CD4", + "5729f4b41d0469140077968c": "200\u2013300", + "5729f4b41d0469140077968d": "200\u2013300", + "5729f4b41d0469140077968e": "cytokines", + "5729f4b41d0469140077968f": "CD40 ligand", + "5729f5a03f37b31900478605": "helper T cells, cytotoxic T cells and NK cells", + "5729f5a03f37b31900478606": "TCR", + "5729f5a03f37b31900478607": "\u03b3\u03b4 T cells", + "5729f5a03f37b31900478608": "receptor diversity", + "5729f5a03f37b31900478609": "V\u03b39/V\u03b42 T cells", + "5729f69caf94a219006aa6f9": "A B cell", + "5729f69caf94a219006aa6fa": "proteolysis", + "5729f69caf94a219006aa6fb": "lymphokines", + "5729f799af94a219006aa707": "long-lived memory cells", + "5729f799af94a219006aa708": "adaptive", + "5729f799af94a219006aa709": "passive short-term memory or active long-term memory", + "5729f799af94a219006aa70a": "each specific pathogen", + "5729f8516aef05140015516c": "microbes", + "5729f8516aef05140015516d": "IgG", + "5729f8516aef05140015516e": "Breast milk or colostrum", + "5729f8516aef05140015516f": "passive immunity", + "5729f9953f37b3190047861f": "immunomodulators", + "5729f9953f37b31900478620": "adaptive and innate", + "5729f9953f37b31900478621": "lupus erythematosus", + "5729f9953f37b31900478622": "immunosuppressive", + "5729fa40af94a219006aa70f": "NFIL3", + "5729fa40af94a219006aa710": "heart disease, chronic pain, and asthma", + "5729fa40af94a219006aa711": "sleep deprivation, active immunizations", + "5729fb003f37b31900478627": "progressive decline in hormone levels with age", + "5729fb003f37b31900478628": "vitamin D", + "5729fb003f37b31900478629": "thyroid hormone activity", + "5729fb003f37b3190047862a": "cholecalciferol", + "5729fc3d1d0469140077969d": "killer T cells", + "5729fc3d1d0469140077969e": "MHC class I", + "5729fc3d1d0469140077969f": "viral antigens", + "5729fc3d1d046914007796a0": "antibodies", + "5729fd111d046914007796a5": "phagocytic cells", + "5729fd111d046914007796a6": "Pathogen-associated molecular patterns or PAMPs", + "5729fd111d046914007796a7": "rapid apoptosis", + "5729fd111d046914007796a8": "Systemic acquired resistance", + "5729fd111d046914007796a9": "RNA silencing mechanisms", + "5729fe5c3f37b3190047862f": "autoimmune disorders", + "5729fe5c3f37b31900478630": "self and non-self", + "5729fe5c3f37b31900478631": "thymus and bone marrow", + "5729fe5c3f37b31900478632": "self\" peptides", + "5729fefbaf94a219006aa739": "Immunodeficiencies", + "5729fefbaf94a219006aa73a": "young and the elderly", + "5729fefbaf94a219006aa73b": "50 years of age", + "5729fefbaf94a219006aa73c": "obesity, alcoholism, and drug use", + "5729fefbaf94a219006aa73d": "malnutrition", + "5729ffda1d046914007796af": "vaccination", + "5729ffda1d046914007796b0": "immunization", + "5729ffda1d046914007796b1": "an antigen", + "5729ffda1d046914007796b2": "natural specificity", + "572a019f3f37b31900478643": "enzymes", + "572a019f3f37b31900478644": "type III secretion system", + "572a019f3f37b31900478645": "shut down host defenses", + "572a019f3f37b31900478646": "elude host immune responses", + "572a02483f37b3190047864b": "Frank Burnet", + "572a02483f37b3190047864c": "pathogens, an allograft", + "572a02483f37b3190047864d": "histocompatibility", + "572a02483f37b3190047864e": "Niels Jerne", + "572a03086aef0514001551a2": "Glucocorticoids", + "572a03086aef0514001551a3": "cytotoxic or immunosuppressive", + "572a03086aef0514001551a4": "methotrexate or azathioprine", + "572a03086aef0514001551a5": "cyclosporin", + "572a04d51d046914007796cd": "cytotoxic natural killer cells and CTLs", + "572a04d51d046914007796ce": "cortisol and catecholamines", + "572a04d51d046914007796cf": "melatonin", + "572a04d51d046914007796d0": "free radical production", + "572a058aaf94a219006aa751": "vitamin D receptor", + "572a058aaf94a219006aa752": "calcitriol", + "572a058aaf94a219006aa753": "symbiotic", + "572a058aaf94a219006aa754": "CYP27B1", + "572a058aaf94a219006aa755": "dendritic cells, keratinocytes and macrophages", + "572a06af3f37b31900478667": "Pattern recognition receptors", + "572a06af3f37b31900478668": "defensins", + "572a06af3f37b31900478669": "phagocytic cells", + "572a06af3f37b3190047866a": "RNA interference pathway", + "572a07fc6aef0514001551dc": "immunoglobulins and T cell receptors", + "572a07fc6aef0514001551dd": "lamprey and hagfish", + "572a07fc6aef0514001551de": "Variable lymphocyte receptors", + "572a07fc6aef0514001551df": "adaptive immune system", + "572a096e6aef0514001551e4": "lymphocytes", + "572a096e6aef0514001551e5": "restriction modification system to protect themselves from viral pathogens, called bacteriophages", + "572a096e6aef0514001551e6": "viral", + "572a096e6aef0514001551e7": "CRISPR sequences", + "572a0a686aef0514001551ec": "\"cellular\" and \"humoral\"", + "572a0a686aef0514001551ed": "Elie Metchnikoff", + "572a0a686aef0514001551ee": "phagocytes", + "572a0a686aef0514001551ef": "Robert Koch and Emil von Behring", + "572a0a686aef0514001551f0": "soluble components", + "572a0b0b6aef0514001551f6": "cancers", + "572a0b0b6aef0514001551f7": "MHC class I molecules", + "572a0b0b6aef0514001551f8": "cytokine TGF-\u03b2", + "572a0b0b6aef0514001551f9": "macrophages and lymphocytes", + "572a0bf96aef051400155204": "Hypersensitivity", + "572a0bf96aef051400155205": "four", + "572a0bf96aef051400155206": "Type I", + "572a0bf96aef051400155207": "IgE", + "572a0bf96aef051400155208": "cytotoxic", + "572a0ce11d046914007796fd": "intracellular pathogenesis", + "572a0ce11d046914007796fe": "Salmonella", + "572a0ce11d046914007796ff": "Plasmodium falciparum", + "572a0ce11d04691400779700": "Mycobacterium tuberculosis", + "572a0ce11d04691400779701": "protein A", + "572a0e4b6aef051400155214": "antigenic variation", + "572a0e4b6aef051400155215": "HIV", + "572a0e4b6aef051400155216": "Trypanosoma brucei", + "572a0e4b6aef051400155217": "antigens", + "572a0f073f37b3190047867f": "immune surveillance", + "572a0f073f37b31900478680": "papillomavirus", + "572a0f073f37b31900478681": "tyrosinase", + "572a0f073f37b31900478682": "melanomas", + "572a0f073f37b31900478683": "melanomas", + "572a10cd6aef051400155222": ">500 Da", + "572a10cd6aef051400155223": "hydrophilic", + "572a10cd6aef051400155224": "Immunoproteomics", + "572a10cd6aef051400155225": "B cells", + "572a10cd6aef051400155226": "immunoinformatics", + "572a12386aef051400155234": "leptin, pituitary growth hormone, and prolactin", + "572a12386aef051400155235": "APCs", + "572a12386aef051400155236": "Th1/Th2", + "572a12386aef051400155237": "Th1", + "572a142e3f37b319004786b9": "carbohydrates", + "572a142e3f37b319004786bc": "disrupting their plasma membrane", + "572a142e3f37b319004786ba": "signal amplification", + "572a142e3f37b319004786bb": "catalytic", + "57271c235951b619008f860b": "Civil disobedience", + "57271c235951b619008f860c": "fight against apartheid", + "57271c235951b619008f860d": "Singing Revolution", + "57271c235951b619008f860e": "Ukraine", + "57271c235951b619008f860f": "Georgia", + "5728d4c03acd2414000dff9f": "Egyptians", + "5728d4c03acd2414000dffa0": "British occupation", + "5728d4c03acd2414000dffa1": "unfair laws", + "5728d4c03acd2414000dffa2": "unfair laws", + "5728d4c03acd2414000dffa3": "Singing Revolution", + "57271f125951b619008f8635": "Antigone", + "57271f125951b619008f8636": "Oedipus", + "57271f125951b619008f8637": "Oedipus, defies Creon", + "57271f125951b619008f8638": "Sophocles", + "57271f125951b619008f8639": "giving her brother Polynices a proper burial", + "5728d5793acd2414000dffb3": "Antigone", + "5728d5793acd2414000dffb4": "Sophocles", + "5728d5793acd2414000dffb5": "Creon", + "5728d5793acd2414000dffb6": "defies Creon, the current King of Thebes, who is trying to stop her from giving her brother Polynices a proper burial", + "5728d5793acd2414000dffb7": "defies Creon", + "5727213c708984140094da35": "Percy Shelley", + "5727213c708984140094da36": "nonviolent", + "5727213c708984140094da38": "Satyagraha", + "5727213c708984140094da39": "campaign for a free India", + "5727213c708984140094da37": "Henry David Thoreau", + "5728d63c4b864d1900164f18": "Percy Shelley", + "5728d63c4b864d1900164f19": "nonviolence", + "5728d63c4b864d1900164f1a": "nonviolent protest", + "5728d63c4b864d1900164f1c": "The Mask of Anarchy", + "5728d63c4b864d1900164f1b": "Henry David Thoreau", + "572726c9708984140094da7b": "muggers, arsonists, draft evaders, campaign hecklers, campus militants, anti-war demonstrators, juvenile delinquents and political assassins", + "572726c9708984140094da7e": "Marshall Cohen", + "572726c9708984140094da7c": "ambiguity", + "572726c9708984140094da7d": "debased", + "5728d6f02ca10214002da90e": "utterly debased", + "5728d6f02ca10214002da90f": "Marshall Cohen", + "5728d6f02ca10214002da910": "utterly debased", + "5728d6f02ca10214002da911": "Marshall Cohen", + "5728d6f02ca10214002da912": "ambiguity", + "572807802ca10214002d9bf8": "LeGrande", + "572807802ca10214002d9bf9": "the formulation of a single all-encompassing definition of the term is extremely difficult, if not impossible", + "572807802ca10214002d9bfa": "lawful protest demonstration, nonviolent civil disobedience, and violent civil disobedience", + "572807802ca10214002d9bfb": "semantical", + "572807802ca10214002d9bfc": "no more (or no less) meaning", + "5728d7c54b864d1900164f4c": "LeGrande", + "5728d7c54b864d1900164f4d": "voluminous", + "5728d7c54b864d1900164f4e": "semantical problems and grammatical niceties", + "5728d7c54b864d1900164f4f": "lawful", + "5728d7c54b864d1900164f50": "nonviolent", + "57280f974b864d1900164370": "civil disobedience", + "57280f974b864d1900164371": "public agencies", + "57280f974b864d1900164372": "pertaining to a citizen's relation to the state and its laws", + "57280f974b864d1900164373": "if the head of government of a country were to refuse to enforce a decision of that country's highest court", + "57280f974b864d1900164374": "Civil disobedience", + "5728d9403acd2414000e001b": "a citizen's relation to the state and its laws", + "5728d9403acd2414000e001c": "if the head of government of a country were to refuse to enforce a decision of that country's highest court", + "5728d9403acd2414000e001d": "private citizen", + "5728d9403acd2414000e001e": "citizen's relation to the state", + "5728d9403acd2414000e001f": "citizen's relation to the state", + "572812e74b864d19001643ce": "Thoreau", + "572812e74b864d19001643cf": "Resign", + "572812e74b864d19001643d0": "The majority may be powerful but it is not necessarily right", + "572812e74b864d19001643d1": "Resign", + "572812e74b864d19001643d2": "a postman or tax collector", + "5728dafe3acd2414000e005d": "The individual", + "5728dafe3acd2414000e005e": "only individuals", + "5728dafe3acd2414000e005f": "postman or tax collector whose hand hits the wood. Before Thoreau\u2019s imprisonment, when a confused taxman", + "5728dafe3acd2414000e0060": "Resign", + "5728dafe3acd2414000e0061": "The majority may be powerful", + "5728151b4b864d1900164428": "against governmental entities", + "5728151b4b864d1900164429": "trade unions, banks, and private universities", + "5728151b4b864d190016442a": "governmental entities", + "5728151b4b864d190016442b": "only justified against governmental entities", + "5728dc2d3acd2414000e0080": "Brownlee", + "5728dc2d3acd2414000e0081": "a larger challenge to the legal system", + "5728dc2d3acd2414000e007f": "civil disobedience is only justified against governmental entities", + "5728dc2d3acd2414000e0083": "governmental entities", + "572818f54b864d190016446c": "civil disobedience", + "572818f54b864d190016446d": "covert lawbreaking", + "572818f54b864d190016446e": "hiding a Jew in their house", + "572818f54b864d190016446f": "Book of Exodus", + "572818f54b864d1900164470": "Shiphrah and Puah", + "5728dddc2ca10214002da9d2": "publicly announced", + "5728dddc2ca10214002da9d3": "rules that conflict with morality", + "5728dddc2ca10214002da9d4": "assisting in fabricating evidence or committing perjury", + "5728dddc2ca10214002da9d5": "lawbreaking", + "5728dddc2ca10214002da9d6": "Book of Exodus", + "57281c594b864d19001644a2": "non-violent", + "57281c594b864d19001644a3": "Black's Law Dictionary", + "57281c594b864d19001644a4": "rebellion", + "57281c594b864d19001644a5": "rebellion is much more destructive", + "57281c594b864d19001644a6": "non-violent", + "5728df634b864d1900164fe2": "non-violent", + "5728df634b864d1900164fe3": "non-violent", + "5728df634b864d1900164fe4": "one cannot justify a civil disobedients' use of force and violence and refusal to submit to arrest", + "5728df634b864d1900164fe6": "constitutional defects", + "5728202c4b864d19001644ec": "Revolutionary civil disobedience", + "5728202c4b864d19001644ed": "the Hungarians", + "5728202c4b864d19001644ee": "Ferenc De\u00e1k", + "5728202c4b864d19001644ef": "the Hungarians under Ferenc De\u00e1k directed revolutionary civil disobedience against the Austrian government", + "5728202c4b864d19001644f0": "cultural traditions, social customs, religious beliefs", + "5728e07e3acd2414000e00e9": "Non-revolutionary", + "5728e07e3acd2414000e00ea": "they are judged \"wrong\" by an individual conscience", + "5728e07e3acd2414000e00eb": "to overthrow a government", + "5728e07e3acd2414000e00ec": "Non-revolutionary", + "5728e07e3acd2414000e00ed": "Gandhi", + "572822233acd2414000df555": "during the Roman Empire", + "572822233acd2414000df556": "Unarmed Jews gathered in the streets", + "572822233acd2414000df557": "his arrest was not covered in any newspapers in the days, weeks and months after it happened. The tax collector who arrested him rose to higher political office", + "572822233acd2414000df558": "higher political office", + "572822233acd2414000df559": "after the end of the Mexican War", + "5728e3c33acd2414000e0131": "during the Roman Empire", + "5728e3c33acd2414000e0132": "prevent the installation of pagan images in the Temple in Jerusalem", + "5728e3c33acd2414000e0133": "jail solidarity", + "5728e3c33acd2414000e0134": "jail solidarity", + "5728e3c33acd2414000e0135": "weeks and months", + "572825a92ca10214002d9efe": "illegal acts", + "572825a92ca10214002d9eff": "propaganda purpose", + "572825a92ca10214002d9f00": "the proprietors of illegal medical cannabis dispensaries and Voice in the Wilderness", + "572825a92ca10214002d9f01": "738 days", + "572825a92ca10214002d9f02": "successfully preventing it from being cut down", + "5728e5224b864d1900165032": "harassment", + "5728e5224b864d1900165033": "trespassing at a nuclear-missile installation", + "5728e5224b864d1900165034": "harassment", + "5728e5224b864d1900165035": "harassment", + "5728e5224b864d1900165036": "Julia Butterfly Hill", + "5728284e3acd2414000df5cd": "allegedly sending an email to the Lebanon, New Hampshire city councilors", + "5728284e3acd2414000df5ce": "\"Wise up or die.\"", + "5728284e3acd2414000df5cf": "forbidden speech", + "5728284e3acd2414000df5d0": "1978 Supreme Court case of FCC v. Pacifica Foundation", + "5728284e3acd2414000df5d1": "1978", + "5728e5f43acd2414000e0171": "pure speech", + "5728e5f43acd2414000e0172": "Threatening government officials", + "5728e5f43acd2414000e0173": "Threatening government officials", + "5728e5f43acd2414000e0174": "engaging in the forbidden speech", + "57282dfb4b864d1900164668": "more difficult for a system to function", + "57282dfb4b864d1900164669": "padlocking the gates", + "57282dfb4b864d190016466a": "GCSB Waihopai", + "57282dfb4b864d190016466b": "coercive", + "57282dfb4b864d190016466c": "coercive", + "5728e715ff5b5019007da914": "civil", + "5728e715ff5b5019007da916": "limited coercion", + "5728e715ff5b5019007da917": "moral dialogue", + "5728e715ff5b5019007da918": "limited coercion", + "5728e8212ca10214002daa6c": "criminal", + "5728e8212ca10214002daa6d": "the arrest", + "5728e8212ca10214002daa6e": "can serve no useful purpose", + "5728e8212ca10214002daa6f": "lack of understanding of the legal ramifications, or due to a fear of seeming rude", + "5728e8212ca10214002daa70": "lack of understanding of the legal ramifications, or due to a fear of seeming rude", + "5728eb1a3acd2414000e01c5": "it is incumbent upon them to accept punishment", + "5728eb1a3acd2414000e01c6": "their belief in the validity of the social contract", + "5728eb1a3acd2414000e01c7": "their belief in the validity of the social contract", + "5728eb1a3acd2414000e01c8": "anarchists", + "5728eb1a3acd2414000e01c9": "a violation of criminal law", + "5728ebcb3acd2414000e01d9": "whether or not to plead guilty", + "5728ebcb3acd2414000e01da": "to submit to the punishment prescribed by law", + "5728ebcb3acd2414000e01db": "illegally protesting nuclear power", + "5728ebcb3acd2414000e01dc": "Guilt implies wrong-doing", + "5728ebcb3acd2414000e01dd": "plea of no contest", + "5728ec6a4b864d19001650aa": "Camp Mercury nuclear test site", + "5728ec6a4b864d19001650ab": "knowing that they faced arrest", + "5728ec6a4b864d19001650ac": "arrest. At a pre-arranged announced time, one at a time they stepped across the \"line\" and were immediately arrested", + "5728ec6a4b864d19001650ad": "nolo contendere", + "5728ec6a4b864d19001650ae": "suspended", + "5728ed94ff5b5019007da97c": "reminding their countrymen of injustice", + "5728ed94ff5b5019007da97d": "reminding their countrymen of injustice", + "5728ed94ff5b5019007da97e": "they must go to jail", + "5728ed94ff5b5019007da97f": "as part of a rule connected with civil disobedience", + "5728eef92ca10214002daab0": "plea bargain", + "5728eef92ca10214002daab1": "plead guilty to one misdemeanor count and receive no jail time", + "5728eef92ca10214002daab2": "solidarity", + "5728eef92ca10214002daab3": "civil", + "5728eef92ca10214002daab4": "Mohandas Gandhi", + "5728f50baf94a219006a9e55": "allocution", + "5728f50baf94a219006a9e56": "explaining their actions", + "5728f50baf94a219006a9e57": "mistreatment from government officials", + "5728f50baf94a219006a9e58": "lack of remorse, an attempt to avoid responsibility for her actions, and even a likelihood of repeating her illegal actions", + "5728f50baf94a219006a9e59": "allocution", + "5728facd4b864d1900165170": "to win an acquittal and avoid imprisonment or a fine", + "5728facd4b864d1900165171": "to win an acquittal", + "5728facd4b864d1900165172": "jury nullification", + "5728facd4b864d1900165173": "Vietnam War", + "5728facd4b864d1900165174": "A technical defense", + "5728fb6a1d04691400778ef5": "attribution", + "5728fb6a1d04691400778ef6": "neither conscientious nor of social benefit", + "5728fb6a1d04691400778ef7": "any great amount of it would undermine the law by encouraging general disobedience which is neither conscientious nor of social benefit", + "5728fb6a1d04691400778ef8": "denying having committed the crime, or by fleeing the jurisdiction", + "5728fb6a1d04691400778ef9": "attribution", + "5728fc9e1d04691400778f11": "Indirect civil disobedience", + "5728fc9e1d04691400778f12": "Indirect civil disobedience involves violating a law which is not, itself, the object of protest, whereas direct civil disobedience", + "5728fc9e1d04691400778f13": "Vietnam War", + "5728fc9e1d04691400778f14": "necessity defense", + "5728fc9e1d04691400778f15": "prosecutors have reasoned (correctly) that if they arrest fully informed jury leafleters", + "5728fd3c3f37b31900477f2b": "achieving crime control via incapacitation and deterrence", + "5728fd3c3f37b31900477f2d": "achieving crime control via incapacitation and deterrence", + "5728fd3c3f37b31900477f2e": "the state (including the judges", + "5728fd3c3f37b31900477f2f": "threat of punishment", + "57273a465951b619008f86ff": "Construction", + "57273a465951b619008f8700": "manufacturing", + "57273a465951b619008f8701": "six to nine percent", + "57273a465951b619008f8702": "planning,[citation needed] design, and financing", + "57273a465951b619008f8703": "a known client", + "57273cca708984140094db33": "An architect", + "57273cca708984140094db34": "An architect normally manages the job, and a construction manager, design engineer, construction engineer or project manager", + "57273cca708984140094db35": "effective planning", + "57273cca708984140094db36": "megaprojects", + "57273cca708984140094db37": "Those involved with the design and execution of the infrastructure in question", + "57273d8bf1498d1400e8f4fe": "buildings, infrastructure and industrial", + "57273d8bf1498d1400e8f4ff": "residential and non-residential", + "57273d8bf1498d1400e8f500": "heavy/highway, heavy civil or heavy engineering", + "57273d8bf1498d1400e8f501": "Infrastructure", + "57273d8bf1498d1400e8f502": "Industrial", + "57273e50dd62a815002e9a02": "a trade magazine for the construction industry", + "57273e50dd62a815002e9a03": "ENR", + "57273e50dd62a815002e9a04": "2014", + "57273e50dd62a815002e9a05": "transportation, sewer, hazardous waste and water", + "57273f27dd62a815002e9a0a": "building construction, heavy and civil engineering construction, and specialty trade contractors", + "57273f27dd62a815002e9a0b": "construction service firms", + "57273f27dd62a815002e9a0c": "The Standard Industrial Classification and the newer North American Industry Classification System", + "57273f27dd62a815002e9a0d": "firms engaged in managing construction projects without assuming direct financial responsibility for completion of the construction project", + "57274046dd62a815002e9a12": "Building construction", + "57274046dd62a815002e9a13": "small renovations", + "57274046dd62a815002e9a14": "the owner of the property", + "57274046dd62a815002e9a15": "structural collapse, cost overruns, and/or litigation", + "57274046dd62a815002e9a16": "make detailed plans and maintain careful oversight", + "572742bd5951b619008f8785": "local building authority regulations and codes of practice", + "572742bd5951b619008f8786": "Materials readily available in the area", + "572742bd5951b619008f8787": "a lot of waste", + "572742bd5951b619008f8788": "Cost of construction on a per square meter (or per square foot) basis for houses", + "572744aff1498d1400e8f588": "3D printing technology", + "572744aff1498d1400e8f589": "20 hours", + "572744aff1498d1400e8f58a": "2014", + "572744aff1498d1400e8f58b": "2 metres (6 ft 7 in)", + "572745c6708984140094db9a": "plan the physical proceedings", + "572745c6708984140094db99": "designs into reality", + "572745c6708984140094db9b": "the property owner", + "572745c6708984140094db9c": "a quantity surveyor", + "572745c6708984140094db9d": "the most cost efficient bidder", + "57274e0d708984140094dbe5": "previously separated specialties", + "57274e0d708984140094dbe6": "entirely separate companies", + "57274e0d708984140094dbe7": "one-stop shopping", + "57274e0d708984140094dbe8": "design build", + "57274e975951b619008f87f9": "design-build, partnering and construction management", + "57274e975951b619008f87fa": "architects, interior designers, engineers and constructors", + "57274e975951b619008f87fb": "establishing relationships with other necessary participants", + "57274f67708984140094dbf5": "preventable financial problems", + "57274f67708984140094dbf6": "builders ask for too little money to complete the project", + "57274f67708984140094dbf7": "when the present amount of funding cannot cover the current costs for labour and materials", + "57274f67708984140094dbf8": "Fraud", + "5727502f708984140094dc07": "Mortgage bankers, accountants, and cost engineers", + "5727502f708984140094dc08": "mortgage banker", + "5727502f708984140094dc09": "Accountants", + "5727502f708984140094dc0b": "identified change orders", + "5727502f708984140094dc0a": "Cost engineers and estimators", + "572750e8dd62a815002e9af0": "zoning and building code requirements", + "572750e8dd62a815002e9af1": "the owner", + "572750e8dd62a815002e9af2": "the desire to prevent things that are indisputably bad \u2013 bridge collapses or explosions", + "572750e8dd62a815002e9af3": "things that are a matter of custom or expectation", + "572750e8dd62a815002e9af4": "An attorney", + "572751b4708984140094dc1b": "A construction project", + "572751b4708984140094dc1c": "A contract", + "572751b4708984140094dc1d": "a delay costs money", + "572751b4708984140094dc1e": "each side is capable of performing the obligations set out", + "572751b4708984140094dc1f": "poorly drafted contracts", + "5727526cdd62a815002e9b0e": "relationship contracting", + "5727526cdd62a815002e9b0f": "Public-Private Partnering", + "5727526cdd62a815002e9b10": "Public-Private Partnering", + "5727526cdd62a815002e9b11": "co-operation", + "572753335951b619008f8853": "the architect or engineer", + "572753335951b619008f8854": "the architect or engineer", + "572753335951b619008f8855": "the architect's client and the main contractor", + "572753335951b619008f8856": "the main contractor", + "572753335951b619008f8857": "the building is ready to occupy", + "57275411dd62a815002e9b30": "The owner", + "57275411dd62a815002e9b31": "D&B contractors", + "57275411dd62a815002e9b32": "The owner", + "57275411dd62a815002e9b33": "a consortium of several contractors", + "57275411dd62a815002e9b34": "they design phase 2", + "572754fff1498d1400e8f660": "contractors", + "572754fff1498d1400e8f661": "damage", + "572754fff1498d1400e8f662": "electrical, water, sewage, phone, and cable", + "572754fff1498d1400e8f663": "the municipal building inspector", + "572754fff1498d1400e8f664": "an occupancy permit", + "572755b7708984140094dc4d": "$960 billion", + "572755b7708984140094dc4e": "$680 billion", + "572755b7708984140094dc4f": "667,000", + "572755b7708984140094dc50": "fewer than 10", + "572755b7708984140094dc51": "828,000", + "5727565ef1498d1400e8f674": "\u00a342,090", + "5727565ef1498d1400e8f675": "\u00a326,719", + "5727565ef1498d1400e8f676": "US/Canada", + "572756fe708984140094dc71": "Construction", + "572756fe708984140094dc72": "Falls", + "572756fe708984140094dc73": "electrocution, transportation accidents, and trench cave-ins", + "572756fe708984140094dc74": "Proper safety equipment", + "572746addd62a815002e9a5e": "independent schools", + "572746addd62a815002e9a5f": "academic scholarship", + "572746addd62a815002e9a60": "public (government) funding", + "572746addd62a815002e9a61": "the right to select their students", + "57274712708984140094dbad": "$45,000", + "57274712708984140094dbae": "tuition-free", + "57274712708984140094dbaf": "Australia", + "57274712708984140094dbb0": "North America", + "5727478cf1498d1400e8f59a": "lower sixth", + "5727478cf1498d1400e8f59b": "upper sixth", + "5727478cf1498d1400e8f59c": "prep schools", + "5727478cf1498d1400e8f59d": "peer tuitions", + "5727478cf1498d1400e8f59e": "the best teachers", + "5727482bf1498d1400e8f5a4": "Roman Catholic", + "5727482bf1498d1400e8f5a5": "Orthodox Christians", + "5727482bf1498d1400e8f5a6": "academic subjects", + "5727490bdd62a815002e9a82": "expulsion", + "5727490bdd62a815002e9a83": "a compulsory blazer", + "5727490bdd62a815002e9a84": "more expensive", + "57274971708984140094dbbb": "Presbyterian Church", + "57274971708984140094dbbc": "Catholic", + "57274971708984140094dbbd": "Sydney", + "57274971708984140094dbbe": "girls", + "57274a1edd62a815002e9a9a": "Article 7, Paragraph 4", + "57274a1edd62a815002e9a9b": "a second Gleichschaltung", + "57274a1edd62a815002e9a9c": "11.1%", + "57274a1edd62a815002e9a9d": "11.1%", + "57274a1edd62a815002e9a9e": "11.1%", + "57274a8ff1498d1400e8f5bc": "Sonderungsverbot", + "57274a8ff1498d1400e8f5bd": "Ersatzschulen", + "57274a8ff1498d1400e8f5be": "low tuition fees and/or offer scholarships", + "57274b35f1498d1400e8f5d4": "Erg\u00e4nzungsschulen", + "57274b35f1498d1400e8f5d5": "vocational schools", + "57274b35f1498d1400e8f5d6": "charging their students tuition fees", + "57274b35f1498d1400e8f5d7": "religious groups", + "57274beff1498d1400e8f5e4": "independent schools", + "57274beff1498d1400e8f5e5": "CBSE", + "57274beff1498d1400e8f5e6": "30", + "57274beff1498d1400e8f5e7": "union government", + "57274ca8dd62a815002e9aa4": "societies", + "57274ca8dd62a815002e9aa5": "India", + "57274ca8dd62a815002e9aa6": "Annual Status of Education Report", + "57274ca8dd62a815002e9aa7": "evaluates learning levels in rural India", + "57274ca8dd62a815002e9aa8": "English", + "57274d1cdd62a815002e9aae": "scoil phr\u00edobh\u00e1ideach", + "57274d1cdd62a815002e9aaf": "unusual because a certain number of teacher's salaries are paid by the State", + "57274d1cdd62a815002e9ab0": "\u20ac5,000", + "57274d1cdd62a815002e9ab1": "Society of Jesus", + "57274d1cdd62a815002e9ab2": "\u20ac25,000 per year", + "57274d9bf1498d1400e8f5f6": "1957", + "57274d9bf1498d1400e8f5f7": "Chinese", + "57274d9bf1498d1400e8f5f8": "English", + "57274d9bf1498d1400e8f5f9": "the National School system", + "57274d9bf1498d1400e8f5fa": "Over 60", + "57274e145951b619008f87e7": "aided' schools", + "57274e145951b619008f87e8": "fully funded by private parties", + "57274e145951b619008f87e9": "Kathmandu", + "57274e145951b619008f87ea": "Nepali", + "57274e145951b619008f87eb": "Nepali", + "57274eca5951b619008f87ff": "88", + "57274eca5951b619008f8800": "28,000", + "57274eca5951b619008f8801": "3.7%", + "57274eca5951b619008f8802": "Catholic", + "57274eca5951b619008f8803": "Auckland", + "57274f49f1498d1400e8f61e": "Anglican", + "57274f49f1498d1400e8f61f": "Wellington", + "57274f49f1498d1400e8f620": "Presbyterian", + "57274f49f1498d1400e8f621": "Christchurch", + "57274f49f1498d1400e8f622": "Society of St Pius X", + "5727500f708984140094dbfd": "7.5%", + "5727500f708984140094dbfe": "32%", + "5727500f708984140094dbff": "80%", + "5727500f708984140094dc00": "August 1992", + "5727500f708984140094dc01": "natural science", + "572750df5951b619008f882f": "The Education Service Contracting scheme", + "572750df5951b619008f8830": "Tuition Fee Supplement", + "572750df5951b619008f8831": "Private Education Student Financial Assistance", + "5727515f708984140094dc11": "The South African Schools Act of 1996", + "5727515f708984140094dc12": "1996", + "5727515f708984140094dc13": "independent", + "5727515f708984140094dc14": "traditional private schools", + "5727515f708984140094dc15": "early nineteenth", + "57275409708984140094dc35": "government schools formerly reserved for white children", + "57275409708984140094dc36": "better", + "57275409708984140094dc37": "higher school fees", + "572754dd708984140094dc3b": "Over 10%", + "572754dd708984140094dc3c": "10,000", + "572754dd708984140094dc3d": "700", + "572754dd708984140094dc3e": "The Knowledge School", + "572754dd708984140094dc3f": "voucher", + "572756265951b619008f886d": "13 years old", + "572756265951b619008f886e": "public schools", + "572756265951b619008f886f": "9 per cent", + "572756265951b619008f8870": "13", + "572756265951b619008f8871": "under \u00a33,000 to \u00a321,000", + "572757bef1498d1400e8f690": "Brown v. Board of Education of Topeka", + "572757bef1498d1400e8f691": "segregation academies", + "572757bef1498d1400e8f692": "South", + "572757bef1498d1400e8f693": "white", + "572757bef1498d1400e8f694": "African-American", + "572758e0f1498d1400e8f6ae": "religious organizations or private individuals", + "572758e0f1498d1400e8f6af": "First Amendment or individual state Blaine Amendments", + "572758e0f1498d1400e8f6b0": "Blaine Amendments", + "572758e0f1498d1400e8f6b1": "charter", + "572759665951b619008f8883": "Massachusetts", + "572759665951b619008f8884": "1852", + "572759665951b619008f8885": "1972", + "572759665951b619008f8886": "268 U.S. 510", + "572759665951b619008f8887": "Runyon v. McCrary", + "572759dbdd62a815002e9b94": "$40,000", + "572759dbdd62a815002e9b95": "$50,000", + "572759dbdd62a815002e9b96": "Groton School", + "572759dbdd62a815002e9b97": "fundraising drives", + "5727aa413acd2414000de921": "John Harvard", + "5727aa413acd2414000de922": "1977", + "5727aa413acd2414000de923": "James Bryant Conant", + "5727aa413acd2414000de924": "Association of American Universities", + "5727aa413acd2414000de925": "Charles W. Eliot", + "5727aeac3acd2414000de987": "Harvard Library", + "5727aeac3acd2414000de988": "79", + "5727aeac3acd2414000de989": "over 18 million", + "5727aeac3acd2414000de98a": "eight", + "5727aeac3acd2414000de98b": "150", + "5727aec03acd2414000de991": "Cambridge", + "5727aec03acd2414000de992": "$37.6 billion", + "5727aec03acd2414000de993": "Charles River", + "5727aec03acd2414000de994": "eleven", + "5727aec03acd2414000de995": "Harvard Yard", + "5727afa82ca10214002d93c2": "1636", + "5727afa82ca10214002d93c3": "Massachusetts Bay Colony", + "5727afa82ca10214002d93c4": "1638", + "5727afa82ca10214002d93c5": "1639", + "5727afa82ca10214002d93c6": "1650", + "5727b0892ca10214002d93e8": "Puritan", + "5727b0892ca10214002d93e9": "English university model", + "5727b0892ca10214002d93ea": "never", + "5727b8df3acd2414000dea99": "1804", + "5727b8df3acd2414000dea9a": "Samuel Webber", + "5727b8df3acd2414000dea9b": "1805", + "5727c0402ca10214002d9564": "Louis Agassiz", + "5727c0402ca10214002d9565": "intuition", + "5727c0402ca10214002d9566": "Thomas Reid and Dugald Stewart", + "5727c3b02ca10214002d95ba": "Charles W. Eliot", + "5727c3b02ca10214002d95bb": "Transcendentalist Unitarian convictions", + "5727c3b02ca10214002d95bc": "William Ellery Channing and Ralph Waldo Emerson", + "5727c55bff5b5019007d94ce": "James Bryant Conant", + "5727c55bff5b5019007d94cf": "identify, recruit, and support talented youth", + "5727c55bff5b5019007d94d0": "1945", + "5727c69d3acd2414000dec13": "four", + "5727c69d3acd2414000dec14": "1977", + "5727c69d3acd2414000dec15": "the proportion of female undergraduates steadily increased", + "5727c8863acd2414000dec49": "3 miles (5 km) west-northwest", + "5727c8863acd2414000dec4a": "twelve", + "5727c8863acd2414000dec4b": "Charles River", + "5727c8863acd2414000dec4c": "half a mile northwest", + "5727cc15ff5b5019007d9576": "Allston", + "5727cc15ff5b5019007d9577": "John W. Weeks Bridge", + "5727cc15ff5b5019007d9578": "Longwood", + "5727cd0f4b864d1900163d72": "fifty percent", + "5727cd0f4b864d1900163d73": "new and enlarged bridges, a shuttle service and/or a tram", + "5727cd0f4b864d1900163d74": "enhanced transit infrastructure", + "5727cebc2ca10214002d96f0": "2,400", + "5727cebc2ca10214002d96f1": "7,200", + "5727cebc2ca10214002d96f2": "14,000", + "5727cebc2ca10214002d96f3": "1875", + "5727cebc2ca10214002d96f4": "1858", + "5727cff1ff5b5019007d95c4": "$32 billion", + "5727cff1ff5b5019007d95c5": "30%", + "5727cff1ff5b5019007d95c6": "Allston Science Complex", + "5727cff1ff5b5019007d95c7": "$4.093 million", + "5727cff1ff5b5019007d95c8": "$159 million", + "5727d0f73acd2414000ded13": "late 1980s", + "5727d0f73acd2414000ded14": "Duke Kent-Brown", + "5727d0f73acd2414000ded15": "$230 million", + "5727d1c93acd2414000ded3f": "5.3%", + "5727d1c93acd2414000ded40": "2007", + "5727d1c93acd2414000ded41": "the program was believed to disadvantage low-income and under-represented minority applicants applying to selective universities", + "5727d1c93acd2414000ded42": "2016", + "5727d3843acd2414000ded69": "seven", + "5727d3843acd2414000ded6a": "eight", + "5727d3843acd2414000ded6b": "they consider this to adversely affect the quality of education", + "5727d4922ca10214002d977c": "early September and ending in mid-May", + "5727d4922ca10214002d977d": "four", + "5727d4922ca10214002d977e": "degrees summa cum laude", + "5727d4922ca10214002d977f": "60%", + "5727d6154b864d1900163e34": "$38,000", + "5727d6154b864d1900163e35": "$57,000", + "5727d6154b864d1900163e36": "between $120,000 and $180,000 pay no more than 10%", + "5727d6154b864d1900163e37": "$414 million", + "5727d6154b864d1900163e38": "88%", + "5727d6faff5b5019007d969a": "Widener Library", + "5727d6faff5b5019007d969c": "Cabot Science Library, Lamont Library, and Widener Library", + "5727d6faff5b5019007d969d": "Pusey Library", + "5727d6faff5b5019007d969b": "over 18 million", + "5727d88b4b864d1900163e5e": "three", + "5727d88b4b864d1900163e5f": "Western art from the Middle Ages to the present", + "5727d88b4b864d1900163e60": "Peabody Museum of Archaeology and Ethnology", + "5727d9c43acd2414000dee17": "2003", + "5727d9c43acd2414000dee18": "2011", + "5727d9c43acd2414000dee19": "second", + "5727da564b864d1900163e8e": "42", + "5727da564b864d1900163e8f": "Yale University", + "5727da564b864d1900163e90": "every two years", + "5727db85ff5b5019007d96fc": "1903", + "5727db85ff5b5019007d96fd": "1903", + "5727db85ff5b5019007d96fe": "1906", + "5727db85ff5b5019007d96ff": "Yale football team", + "5727dc473acd2414000dee43": "Lavietes Pavilion", + "5727dc473acd2414000dee44": "Malkin Athletic Center", + "5727dc473acd2414000dee45": "three", + "5727dd2e4b864d1900163eba": "23", + "5727dd2e4b864d1900163ebb": "Thames River", + "5727dd2e4b864d1900163ebc": "Cornell", + "5727dd2e4b864d1900163ebd": "2003", + "5727de862ca10214002d9860": "Ban Ki-moon", + "5727de862ca10214002d9861": "Sebasti\u00e1n Pi\u00f1era", + "5727de862ca10214002d9862": "Jos\u00e9 Mar\u00eda Figueres", + "5727de862ca10214002d9863": "Abul Maal Abdul Muhith", + "5727e0474b864d1900163f08": "Conan O'Brien", + "5727e0474b864d1900163f09": "Leonard Bernstein", + "5727e0474b864d1900163f0a": "Yo Yo Ma", + "5727e0474b864d1900163f0b": "W. E. B. Du Bois", + "5727e21e4b864d1900163f34": "Shing-Tung Yau", + "5727e21e4b864d1900163f35": "Alan Dershowitz and Lawrence Lessig", + "5727e21e4b864d1900163f36": "Stephen Greenblatt", + "5727c94bff5b5019007d954a": "Jacksonville", + "5727c94bff5b5019007d954b": "1,345,596", + "5727c94bff5b5019007d954c": "12th", + "5727c94bff5b5019007d954d": "Duval County", + "5727c94bff5b5019007d954e": "1968", + "5727cb4b2ca10214002d9676": "St. Johns River", + "5727cb4b2ca10214002d9677": "340 miles", + "5727cb4b2ca10214002d9678": "Fort Caroline", + "5727cb4b2ca10214002d9679": "Timucua", + "5727cb4b2ca10214002d967a": "Andrew Jackson", + "5727cd7dff5b5019007d958e": "third largest", + "5727cd7dff5b5019007d958f": "golf", + "5727cd7dff5b5019007d9590": "two", + "5727cd7dff5b5019007d9591": "Jacksonvillians", + "57280e1aff5b5019007d9bec": "thousands", + "57280e1aff5b5019007d9bed": "a University of North Florida", + "57280e1aff5b5019007d9bee": "Mocama", + "57280e1aff5b5019007d9bef": "the historical era", + "57280e1aff5b5019007d9bf0": "Ossachite", + "57280fd3ff5b5019007d9c26": "Jean Ribault", + "57280fd3ff5b5019007d9c27": "France", + "57280fd3ff5b5019007d9c28": "Pedro Men\u00e9ndez de Avil\u00e9s", + "57280fd3ff5b5019007d9c29": "fort San Mateo", + "57280fd3ff5b5019007d9c2a": "Fort Caroline", + "572810ec2ca10214002d9d06": "French and Indian War", + "572810ec2ca10214002d9d07": "constructed the King's Road connecting St. Augustine to Georgia", + "572810ec2ca10214002d9d08": "cattle were brought across the river", + "572810ec2ca10214002d9d09": "Britain ceded control of the territory back to Spain", + "572810ec2ca10214002d9d0a": "February 9, 1832", + "5728128cff5b5019007d9c76": "Confederate", + "5728128cff5b5019007d9c77": "the Brick Church", + "5728128cff5b5019007d9c78": "Battle of Olustee", + "5728128cff5b5019007d9c79": "Warfare and the long occupation", + "5728128cff5b5019007d9c7a": "1864", + "572815d9ff5b5019007d9cbc": "Reconstruction and the Gilded Age", + "572815d9ff5b5019007d9cbd": "Grover Cleveland", + "572815d9ff5b5019007d9cbe": "yellow fever outbreaks", + "572815d9ff5b5019007d9cbf": "extension of the Florida East Coast Railway", + "572815d9ff5b5019007d9cc0": "railroad", + "5728170d3acd2414000df443": "Spanish moss", + "5728170d3acd2414000df444": "2,000", + "5728170d3acd2414000df445": "declare martial law", + "5728170d3acd2414000df446": "Great Fire of 1901", + "57281940ff5b5019007d9d44": "New York\u2013based filmmakers", + "57281940ff5b5019007d9d45": "silent", + "57281940ff5b5019007d9d46": "Winter Film Capital of the World", + "57281940ff5b5019007d9d47": "Hollywood", + "57281ab63acd2414000df493": "The construction of highways", + "57281ab63acd2414000df494": "55.1%", + "57281ab63acd2414000df495": "white flight", + "57281ab63acd2414000df496": "Mayor W. Haydon Burns", + "57281ab63acd2414000df497": "World War II", + "57281bb84b864d190016449a": "Much of the city's tax base dissipated", + "57281bb84b864d190016449b": "unincorporated suburbs", + "57281bb84b864d190016449c": "annexing outlying communities in order to create the needed tax base to improve services throughout the county", + "57281bb84b864d190016449d": "Voters outside the city limits", + "57281d494b864d19001644be": "through the traditional old boy network", + "57281d494b864d19001644bf": "11", + "57281d494b864d19001644c0": "Jacksonville Consolidation", + "57281d494b864d19001644c1": "Lower taxes", + "57281edd3acd2414000df4eb": "consolidation referendum was held in 1967, voters approved the plan", + "57281edd3acd2414000df4ec": "Hans Tanzler", + "57281edd3acd2414000df4ed": "the Consolidated City of Jacksonville", + "57281edd3acd2414000df4ee": "The Better Jacksonville Plan", + "57281edd3acd2414000df4ef": "a half-penny sales tax", + "572820512ca10214002d9e72": "86.66%", + "572820512ca10214002d9e73": "St. Johns River", + "572820512ca10214002d9e74": "Trout River", + "572820512ca10214002d9e75": "13.34%", + "572820512ca10214002d9e76": "Baldwin", + "572821274b864d1900164510": "It has a height of 617 ft (188 m) and includes 42 floors", + "572821274b864d1900164511": "Barnett Center", + "572821274b864d1900164512": "617 ft", + "572821274b864d1900164513": "28", + "572821274b864d1900164514": "distinctive flared base", + "5728223cff5b5019007d9dc4": "humid subtropical", + "5728223cff5b5019007d9dc5": "May through September", + "5728223cff5b5019007d9dc6": "mild and sunny", + "5728223cff5b5019007d9dc7": "low latitude", + "57282358ff5b5019007d9dde": "104 \u00b0F (40 \u00b0C)", + "57282358ff5b5019007d9ddf": "thunderstorms", + "57282358ff5b5019007d9de0": "extremely high humidity", + "57282358ff5b5019007d9de1": "July", + "572824f13acd2414000df58f": "Hurricane Dora", + "572824f13acd2414000df590": "110 mph", + "572824f13acd2414000df591": "Beryl", + "572824f13acd2414000df592": "Saffir-Simpson Scale", + "572824f13acd2414000df593": "2008", + "572826634b864d19001645be": "Arab", + "572826634b864d19001645bf": "821,784", + "572826634b864d19001645c0": "twelfth", + "572826634b864d19001645c1": "Filipino", + "572827fc3acd2414000df5bb": "29.7%", + "572827fc3acd2414000df5bc": "23.9%", + "572827fc3acd2414000df5bd": "married couples", + "572827fc3acd2414000df5be": "91.3", + "5727e6cbff5b5019007d97ee": "40%", + "5727e6cbff5b5019007d97ef": "3.5 billion", + "5727e6cbff5b5019007d97f0": "$759,900", + "5727e6cbff5b5019007d97f1": "using net wealth", + "5727e6cbff5b5019007d97f2": "by using net wealth", + "5729d36b1d04691400779607": "40%", + "5729d36b1d04691400779608": "financial assets", + "5729d36b1d04691400779609": "nearly $41 trillion", + "5729d36b1d0469140077960a": "more than half", + "5729d36b1d0469140077960b": "due to a greater tendency to take on debts", + "5727e8424b864d1900163fc0": "400", + "5727e8424b864d1900163fc1": "New York Times", + "5727e8424b864d1900163fc2": "Inherited wealth", + "5727e8424b864d1900163fc3": "more wealth than half of all Americans combined", + "5729d44b1d04691400779611": "wealth", + "5729d44b1d04691400779612": "richest 1 percent", + "5729d44b1d04691400779613": "Inherited wealth", + "5729d44b1d04691400779614": "over 60 percent", + "5729d44b1d04691400779615": "Institute for Policy Studies", + "5727e9523acd2414000def95": "Neoclassical economics", + "5727e9523acd2414000def96": "productivity gap between highly-paid professions and lower-paid professions", + "5727e9523acd2414000def97": "differences in value added by different classifications of workers", + "5727e9523acd2414000def98": "inequality", + "5727e9523acd2414000def99": "marginal value added of each economic actor", + "5729d51d3f37b3190047858f": "differences in value added by labor, capital and land", + "5729d51d3f37b31900478590": "value added by different classifications of workers", + "5729d51d3f37b31900478591": "wages and profits", + "5729d51d3f37b31900478592": "worker, capitalist/business owner, landlord", + "5729d51d3f37b31900478593": "productivity gap between highly-paid professions and lower-paid professions", + "5727ea45ff5b5019007d986e": "The substitution of capital equipment for labor", + "5727ea45ff5b5019007d986f": "downward pressure on wages", + "5727ea45ff5b5019007d9870": "increasing unemployment", + "5727ea45ff5b5019007d9871": "downward pressure on wages", + "5729d609af94a219006aa661": "labor inputs", + "5729d609af94a219006aa662": "to reduce costs and maximize profits", + "5729d609af94a219006aa663": "capitalist firms", + "5729d609af94a219006aa664": "the productivity", + "5729d609af94a219006aa665": "stagnant", + "5727ec062ca10214002d99b6": "workers wages", + "5727ec062ca10214002d99b7": "supply and demand", + "5727ec062ca10214002d99b8": "understaffed", + "5727ec062ca10214002d99b9": "offering a higher wage the best of their labor", + "5727ec062ca10214002d99ba": "unfair", + "5729d878af94a219006aa66b": "the market", + "5729d878af94a219006aa66c": "prices", + "5729d878af94a219006aa66d": "wages", + "5729d878af94a219006aa66e": "markets", + "5729d878af94a219006aa66f": "high levels of inequality", + "5727ed2e3acd2414000df001": "high demand", + "5727ed2e3acd2414000df002": "low demand", + "5727ed2e3acd2414000df003": "high demand", + "5727ed2e3acd2414000df004": "collective bargaining, political influence, or corruption", + "5727ed2e3acd2414000df005": "Professional and labor organizations", + "5729da0faf94a219006aa675": "a low wage", + "5729da0faf94a219006aa676": "competition between workers", + "5729da0faf94a219006aa677": "due to the expendable nature of the worker in relation to his or her particular job", + "5729da0faf94a219006aa678": "low wage", + "5729da0faf94a219006aa679": "employers", + "5727ee372ca10214002d99ec": "entrepreneurship rates", + "5727ee372ca10214002d99ed": "self-employment", + "5727ee372ca10214002d99ee": "push\" motivations", + "5727ee372ca10214002d99ef": "achievement-oriented motivations", + "5727ee372ca10214002d99f0": "entrepreneurialism", + "5729de24af94a219006aa689": "higher economic inequality", + "5729de24af94a219006aa68a": "higher economic inequality", + "5729de24af94a219006aa68b": "Necessity-based entrepreneurship", + "5729de24af94a219006aa68c": "achievement-oriented motivations", + "5729de24af94a219006aa68d": "positive", + "5727ef664b864d1900164060": "A progressive tax", + "5727ef664b864d1900164061": "top tax rate", + "5727ef664b864d1900164062": "steeper tax progressivity", + "5727ef664b864d1900164063": "progressive tax system", + "5729e02f1d04691400779639": "the tax rate", + "5729e02f1d0469140077963a": "the level of the top tax rate", + "5729e02f1d0469140077963b": "steeper tax progressivity applied to social spending", + "5729e02f1d0469140077963c": "Gini index", + "5727f05b4b864d1900164068": "Education", + "5727f05b4b864d1900164069": "education", + "5727f05b4b864d190016406a": "lower incomes", + "5727f05b4b864d190016406b": "the poor", + "5727f05b4b864d190016406c": "lower aggregate savings and investment", + "5729e1101d04691400779641": "variation in individuals' access to education", + "5729e1101d04691400779642": "high wages", + "5729e1101d04691400779643": "lower wages", + "5729e1101d04691400779644": "lower incomes", + "5729e1101d04691400779645": "education raises incomes and promotes growth", + "5727f16c3acd2414000df05b": "increasing access to education", + "5727f16c3acd2414000df05c": "$105 billion", + "5727f16c3acd2414000df05d": "boom-and-bust cycles", + "5727f16c3acd2414000df05e": "economists with the Standard & Poor's rating agency", + "5729e1e36aef0514001550ba": "2014", + "5729e1e36aef0514001550bb": "2008-2009 recession", + "5729e1e36aef0514001550bc": "increasing access to education", + "5729e1e36aef0514001550bd": "$105 billion", + "5729e1e36aef0514001550be": "boom-and-bust cycles", + "5727f2714b864d1900164072": "1910\u20131940", + "5727f2714b864d1900164073": "decrease in the price of skilled labor", + "5727f2714b864d1900164074": "decrease in the price of skilled labor", + "5727f2714b864d1900164075": "low economic growth", + "5727f2714b864d1900164076": "decrease in wages", + "5729e2b76aef0514001550ce": "1910\u20131940", + "5729e2b76aef0514001550cf": "decrease in the price of skilled labor", + "5729e2b76aef0514001550d0": "it differs from the present high school education, which is regarded as a stepping-stone to acquire college and advanced degrees", + "5729e2b76aef0514001550d1": "Education", + "5729e2b76aef0514001550d2": "continued gender inequality in education", + "5727f6723acd2414000df0e7": "continental European countries", + "5727f6723acd2414000df0e8": "continental European countries", + "5727f6723acd2414000df0ea": "little", + "5727f6723acd2414000df0e9": "Anglo-American liberal policies", + "5729e38daf94a219006aa69d": "economic inequality", + "5729e38daf94a219006aa69e": "social exclusion", + "5729e38daf94a219006aa69f": "CEPR", + "5729e38daf94a219006aa6a0": "little", + "5729e38daf94a219006aa6a1": "lower", + "5727f7523acd2414000df10d": "Scandinavia", + "5727f7523acd2414000df10e": "high inequality", + "5727f7523acd2414000df10f": "decline of organized labor", + "5727f7523acd2414000df110": "decline of organized labor", + "5729e4291d04691400779651": "Sociologist", + "5729e4291d04691400779652": "University of Washington", + "5729e4291d04691400779653": "the decline of organized labor", + "5729e4291d04691400779654": "high", + "5729e4291d04691400779655": "weak labor movements", + "5727fc37ff5b5019007d9a18": "reduced wages as a result of the competition, while low-skilled workers in the poor countries may see increased wages", + "5727fc37ff5b5019007d9a19": "reduced wages", + "5727fc37ff5b5019007d9a1a": "trade liberalisation", + "5727fc37ff5b5019007d9a1b": "machine labor", + "5729f1283f37b319004785d7": "a global to a domestic scale", + "5729f1283f37b319004785d8": "low-skilled workers", + "5729f1283f37b319004785d9": "trade liberalisation", + "5729f1283f37b319004785da": "minor", + "5729f1283f37b319004785db": "machine labor", + "5727fd123acd2414000df185": "53%", + "5727fd123acd2414000df186": "40%", + "5727fd123acd2414000df187": "a difference in earnings between women and men", + "5727fd123acd2414000df188": "males", + "5729f1c13f37b319004785e7": "Gender", + "5729f1c13f37b319004785e8": "males in the labor market", + "5729f1c13f37b319004785e9": "women", + "5729f1c13f37b319004785ea": "Thomas Sowell", + "5729f1c13f37b319004785eb": "a difference", + "5727ff083acd2414000df1ab": "social welfare programs", + "5727ff083acd2414000df1ac": "lower", + "5727ff083acd2414000df1ad": "it acquires more capital", + "5727ff083acd2414000df1ae": "social welfare programs", + "5729f24baf94a219006aa6dd": "Economist", + "5729f24baf94a219006aa6de": "levels of economic inequality", + "5729f24baf94a219006aa6df": "more capital", + "5729f24baf94a219006aa6e0": "more wealth and income", + "5729f24baf94a219006aa6e1": "social welfare programs, more developed countries move back to lower levels of inequality", + "57287b322ca10214002da3be": "1910 to 1940 and thereafter", + "57287b322ca10214002da3bf": "after the 1970s", + "57287b322ca10214002da3c0": "manufacturing", + "57287b322ca10214002da3c1": "manufacturing", + "5729f3883f37b319004785f1": "Kuznets", + "5729f3883f37b319004785f2": "Kuznets curve", + "5729f3883f37b319004785f3": "very weak", + "5729f3883f37b319004785f4": "income inequality will eventually decrease", + "5729f3883f37b319004785f5": "another Kuznets' cycle is occurring, specifically the move from the manufacturing sector to the service sector", + "57287c2bff5b5019007da26c": "Wealth concentration", + "57287c2bff5b5019007da26d": "the means to invest in new sources of creating wealth or to otherwise leverage the accumulation of wealth", + "57287c2bff5b5019007da26e": "wealth condensation", + "57287c2bff5b5019007da26f": "return of capital", + "5729f4273f37b319004785fb": "the possession of already-wealthy individuals or entities", + "5729f4273f37b319004785fc": "those who already hold wealth", + "5729f4273f37b319004785fd": "wealth condensation", + "5729f4273f37b319004785fe": "Thomas Piketty", + "5729f4273f37b319004785ff": "higher returns", + "5729f4e46aef051400155157": "market forces", + "5729f4e46aef051400155156": "Economist", + "5729f4e46aef051400155158": "rare and desired", + "5729f4e46aef051400155159": "political power", + "5729f4e46aef05140015515a": "rent-seeking", + "5729f60caf94a219006aa6ef": "inequality", + "5729f60caf94a219006aa6f0": "human capital is neglected for high-end consumption", + "5729f60caf94a219006aa6f1": "life expectancy", + "5729f60caf94a219006aa6f2": "inequality", + "5729f60caf94a219006aa6f3": "lower", + "572a05eb3f37b31900478653": "2013", + "572a05eb3f37b31900478654": "rising inequality", + "572a05eb3f37b31900478655": "negative", + "572a05eb3f37b31900478656": "social dislocation, unrest and conflict", + "572a05eb3f37b31900478657": "economic", + "572a06866aef0514001551be": "British", + "572a06866aef0514001551bf": "lower", + "572a06866aef0514001551c0": "lower", + "572a06866aef0514001551c2": "23", + "572a06866aef0514001551c1": "social goods", + "572a070c6aef0514001551c8": "better health and longer lives", + "572a070c6aef0514001551c9": "among poorer countries", + "572a070c6aef0514001551ca": "life expectancy", + "572a070c6aef0514001551cb": "Americans", + "572a070c6aef0514001551cc": "Life expectancy", + "572a07a86aef0514001551d2": "income inequality", + "572a07a86aef0514001551d3": "Richard Wilkinson and Kate Pickett", + "572a07a86aef0514001551d4": "nine", + "572a07a86aef0514001551d5": "countries with bigger income inequalities", + "572a07a86aef0514001551d6": "greater equality but not per capita income", + "572a0a391d046914007796df": "inequality", + "572a0a391d046914007796e0": "homicides", + "572a0a391d046914007796e1": "over fifty", + "572a0a391d046914007796e3": "differences in the amount of inequality in each province or state", + "572a0a391d046914007796e2": "tenfold", + "572a0bafaf94a219006aa765": "economic inequality", + "572a0bafaf94a219006aa766": "distributive efficiency", + "572a0bafaf94a219006aa767": "a great deal of utility", + "572a0bafaf94a219006aa768": "decreases", + "572a0bafaf94a219006aa769": "higher aggregate utility", + "572a0c541d046914007796f3": "consumption, rather than income", + "572a0c541d046914007796f4": "Conservative", + "572a0c541d046914007796f5": "2001", + "572a0c541d046914007796f6": "Thomas B. Edsall", + "572a0c541d046914007796f7": "journalist", + "572a0d21af94a219006aa783": "Central Banking economist", + "572a0d21af94a219006aa784": "systematic economic inequalities", + "572a0d21af94a219006aa785": "the Financial crisis of 2007\u201308", + "572a0d21af94a219006aa786": "easier credit to the lower and middle income earners", + "572a0d21af94a219006aa787": "unsustainable monetary stimulation", + "572a0e0e1d04691400779707": "inequality in wealth and income", + "572a0e0e1d04691400779708": "the quality of a country's institutions and high levels of education", + "572a0e0e1d04691400779709": "declines", + "572a0e0e1d0469140077970a": "higher GDP growth", + "572a0e0e1d0469140077970b": "The poor and the middle class", + "572a0ecb1d04691400779717": "economists", + "572a0ecb1d04691400779718": "economic growth", + "572a0ecb1d04691400779719": "subsequent long-run economic growth", + "572a0ecb1d0469140077971a": "it is a waste of resources", + "572a0ecb1d0469140077971b": "inequality-associated effects", + "572a1046af94a219006aa78d": "evidence in 2009 that both global inequality and inequality within countries prevent growth by limiting aggregate demand", + "572a1046af94a219006aa78e": "limiting aggregate demand", + "572a1046af94a219006aa78f": "Economist", + "572a1046af94a219006aa790": "increasing importance of human capital in development", + "572a1046af94a219006aa791": "widespread education", + "572a11663f37b31900478693": "1993", + "572a11663f37b31900478694": "detrimental", + "572a11663f37b31900478695": "the channels through which inequality may affect economic growth", + "572a11663f37b31900478696": "redistributive taxation", + "572a11663f37b31900478697": "politically and socially unstable", + "572a12381d0469140077972d": "reduce", + "572a12381d0469140077972e": "encourage", + "572a12381d0469140077972c": "growth and investment", + "572a12381d0469140077972b": "Harvard", + "572a12381d0469140077972f": "between 1960 and 2000", + "572a13841d0469140077973b": "Kuznets curve hypothesis", + "572a13841d0469140077973c": "from 1914 to 1945 wars", + "572a13841d0469140077973d": "Thomas Piketty", + "572a13841d0469140077973e": "Economist", + "572a13841d0469140077973f": "wars and \"violent economic and political shocks", + "572a18a4af94a219006aa7df": "1970s", + "572a18a4af94a219006aa7e0": "reduced consumer demand", + "572a18a4af94a219006aa7e1": "risen with increased income inequality", + "572a18a4af94a219006aa7e2": "several years", + "572a18a4af94a219006aa7e3": "more equality in the income distribution", + "572a1a5c6aef051400155284": "special efforts", + "572a1a5c6aef051400155285": "the existing level of inequality", + "572a1a5c6aef051400155286": "the same reduction", + "572a1a5c6aef051400155287": "United Nations", + "572a1a5c6aef051400155288": "reducing poverty", + "572a1ba46aef05140015528e": "much land and housing", + "572a1ba46aef05140015528f": "through various associations and other arrangements", + "572a1ba46aef051400155290": "extra-legal ownership", + "572a1ba46aef051400155291": "200", + "572a1ba46aef051400155292": "government land", + "572a1c943f37b319004786e1": "affordable housing", + "572a1c943f37b319004786e2": "quality rental units", + "572a1c943f37b319004786e3": "the demand for higher quality housing increased", + "572a1c943f37b319004786e4": "gentrification of older neighbourhoods", + "572a1c943f37b319004786e5": "ad valorem property tax policy", + "572a1dbb3f37b319004786f5": "everyone", + "572a1dbb3f37b319004786f6": "their finances", + "572a1dbb3f37b319004786f7": "aspirational consumption", + "572a1dbb3f37b319004786f8": "taking on debt", + "572a1dbb3f37b319004786f9": "greater inequality and potential economic instability", + "572a1f086aef0514001552c0": "created", + "572a1f086aef0514001552c1": "environmental degradation", + "572a1f086aef0514001552c2": "this", + "572a1f086aef0514001552c3": "If (as WWF argued), population levels would start to drop to a sustainable level", + "572a1fe16aef0514001552d0": "private ownership of the means of production by a class of owners", + "572a1fe16aef0514001552d1": "a small portion of the population lives off unearned property income", + "572a1fe16aef0514001552d2": "a wage or salary", + "572a1fe16aef0514001552d3": "socially owned", + "572a1fe16aef0514001552d4": "reflective", + "572a20816aef0514001552e4": "Robert Nozick", + "572a20816aef0514001552e5": "taxation", + "572a20816aef0514001552e6": "force", + "572a20816aef0514001552e7": "forceful taking of property", + "572a20816aef0514001552e8": "when they improve society as a whole", + "572a213e6aef0514001552ee": "capability deprivation", + "572a213e6aef0514001552ef": "the end itself", + "572a213e6aef0514001552f0": "to \u201cwid[en] people\u2019s choices and the level of their achieved well-being", + "572a213e6aef0514001552f1": "to \u201cwid[en] people\u2019s choices and the level of their achieved well-being", + "572a213e6aef0514001552f2": "the ability to pursue valued goals", + "572a2224af94a219006aa823": "they are in some way deprived of earning as much income as they would otherwise", + "572a2224af94a219006aa824": "earn as much as a healthy young man", + "572a2224af94a219006aa825": "gender roles and customs", + "572a2224af94a219006aa826": "fear of their lives", + "572a2224af94a219006aa827": "a better relevant income", + "5727efabff5b5019007d98e2": "BBC", + "5727efabff5b5019007d98e3": "1963", + "5727efabff5b5019007d98e4": "TARDIS", + "5727efabff5b5019007d98e5": "a blue British police box", + "5727efabff5b5019007d98e6": "science-fiction", + "5727f0b1ff5b5019007d98f2": "1963 to 1989", + "5727f0b1ff5b5019007d98f3": "Russell T Davies", + "5727f0b1ff5b5019007d98f4": "Torchwood", + "5727f0b1ff5b5019007d98f5": "BBC Wales", + "5727f0b1ff5b5019007d98f6": "Russell T Davies", + "5727f18c3acd2414000df063": "Twelve", + "5727f18c3acd2414000df064": "Peter Capaldi", + "5727f18c3acd2414000df065": "The Time of the Doctor", + "5727f18c3acd2414000df066": "after sustaining an injury which would be fatal to most other species", + "5727f18c3acd2414000df067": "new personality", + "5727f2583acd2414000df087": "Gallifrey", + "5727f2583acd2414000df088": "Mark I Type 40 TARDIS", + "5727f2583acd2414000df089": "Time and Relative Dimension in Space", + "5727f2583acd2414000df08a": "chameleon circuit", + "5727f2583acd2414000df08b": "a malfunction in the chameleon circuit", + "5727f3193acd2414000df0a5": "rarely", + "5727f3193acd2414000df0a6": "the Master", + "5727f3193acd2414000df0a7": "regenerate", + "5727f3193acd2414000df0a8": "humans", + "5727f3193acd2414000df0a9": "Time Lord", + "5727f44c2ca10214002d9a32": "23 November 1963", + "5727f44c2ca10214002d9a33": "aliens", + "5727f44c2ca10214002d9a34": "the programme was not permitted to contain any \"bug-eyed monsters\"", + "5727f44c2ca10214002d9a35": "Terry Nation", + "5727f44c2ca10214002d9a36": "25 minutes", + "5727f5622ca10214002d9a44": "26", + "5727f5622ca10214002d9a45": "Jonathan Powell", + "5727f5622ca10214002d9a46": "Doctor Who: More Than 30 Years in the TARDIS", + "5727f5622ca10214002d9a47": "the series would return", + "5727f5622ca10214002d9a48": "BBC 1", + "5727f678ff5b5019007d9956": "relaunch the show", + "5727f678ff5b5019007d9957": "Philip Segal", + "5727f678ff5b5019007d9958": "Fox", + "5727f678ff5b5019007d9959": "9.1 million", + "5727f678ff5b5019007d995a": "UK", + "5727f746ff5b5019007d9960": "Rose", + "5727f746ff5b5019007d9961": "2005", + "5727f746ff5b5019007d9963": "2009", + "5727f746ff5b5019007d9964": "Chris Chibnall", + "5727f746ff5b5019007d9962": "Christmas Day specials", + "5727f8342ca10214002d9a7c": "1963\u20131989", + "5727f8342ca10214002d9a7d": "The 2005 version of Doctor Who", + "5727f8342ca10214002d9a7e": "2005", + "5727f8342ca10214002d9a7f": "Battlestar Galactica and Bionic Woman", + "5727f8342ca10214002d9a80": "Mission Impossible", + "5727fc7f4b864d1900164160": "30 November 1963", + "5727fc7f4b864d1900164161": "ten minutes", + "5727fc7f4b864d1900164162": "ten minutes", + "5727fc7f4b864d1900164163": "assassination of US President John F. Kennedy", + "5727fc7f4b864d1900164164": "a series of power blackouts", + "5727fdb94b864d190016417c": "Hiding behind (or 'watching from behind') the sofa", + "5727fdb94b864d190016417d": "the Museum of the Moving Image in London", + "5727fdb94b864d190016417e": "the Museum of the Moving Image", + "5727fdb94b864d190016417f": "scariest TV show of all time", + "5727fdb94b864d1900164180": "Digital Spy", + "5727fed73acd2414000df1a1": "Doctor Who", + "5727fed73acd2414000df1a2": "3%", + "5727fed73acd2414000df1a3": "Philip Howard", + "5727fed73acd2414000df1a4": "Monopoly", + "5727fed73acd2414000df1a5": "Times", + "5727ffb5ff5b5019007d9a8c": "the TARDIS", + "5727ffb5ff5b5019007d9a8d": "a police box as a time machine", + "5727ffb5ff5b5019007d9a8e": "time machine", + "5727ffb5ff5b5019007d9a8f": "the Metropolitan Police Authority", + "5727ffb5ff5b5019007d9a90": "2002", + "572800b03acd2414000df1f1": "26", + "572800b03acd2414000df1f2": "6 December 1989", + "572800b03acd2414000df1f3": "12", + "572800b03acd2414000df1f4": "The Master", + "572800b03acd2414000df1f5": "Black Guardian Trilogy", + "572801823acd2414000df1fb": "2005", + "572801823acd2414000df1fc": "60 minutes", + "572801823acd2414000df1fd": "Christmas Day", + "572801823acd2414000df1fe": "Journey's End", + "572801823acd2414000df1ff": "2010", + "5728023a4b864d19001641f4": "826", + "5728023a4b864d19001641f5": "25-minute", + "5728023a4b864d19001641f6": "eight", + "5728023a4b864d19001641f7": "60 minutes", + "5728023a4b864d19001641f8": "2009", + "572803493acd2414000df229": "William Hartnell and Patrick Troughton", + "572803493acd2414000df22a": "97", + "572803493acd2414000df22b": "3, 4, & 5", + "572803493acd2414000df22c": "1978", + "572803493acd2414000df22d": "1964 and 1973", + "572804522ca10214002d9b94": "bought prints for broadcast", + "572804522ca10214002d9b95": "fans", + "572804522ca10214002d9b97": "Mission to the Unknown", + "572804522ca10214002d9b96": "8 mm cine", + "572804522ca10214002d9b98": "tape recordings", + "572805363acd2414000df26d": "the BBC", + "572805363acd2414000df26e": "Cosgrove Hall", + "572805363acd2414000df26f": "1968", + "572805363acd2414000df270": "Theta-Sigma", + "572805363acd2414000df271": "November 2006", + "57280757ff5b5019007d9b42": "regeneration", + "57280757ff5b5019007d9b43": "the Doctor's third on-screen regeneration", + "57280757ff5b5019007d9b44": "William Hartnell's poor health", + "57280757ff5b5019007d9b45": "regeneration\" was not initially conceived of until the Doctor's third on-screen regeneration", + "57280757ff5b5019007d9b46": "change of appearance", + "572808bf4b864d190016429a": "12", + "572808bf4b864d190016429b": "13", + "572808bf4b864d190016429c": "The Time of the Doctor", + "572808bf4b864d190016429d": "The Deadly Assassin and Mawdryn Undead", + "572808bf4b864d190016429e": "1996", + "572809ab4b864d19001642ae": "John Hurt", + "572809ab4b864d19001642af": "The Day of the Doctor", + "572809ab4b864d19001642b0": "Michael Jayston", + "572809ab4b864d19001642b1": "The Trial of a Time Lord", + "572809ab4b864d19001642b2": "McGann and Eccleston", + "57280b2b2ca10214002d9c66": "Eleventh Doctor", + "57280b2b2ca10214002d9c67": "The Three Doctors", + "57280b2b2ca10214002d9c68": "David Tennant", + "57280b2b2ca10214002d9c6a": "The Space Museum", + "57280b2b2ca10214002d9c69": "The Day of the Doctor", + "57280cac2ca10214002d9ca8": "Peter Davison, Colin Baker and Sylvester McCoy", + "57280cac2ca10214002d9ca9": "Zagreus", + "57280cac2ca10214002d9caa": "Peter Davison, Colin Baker, Sylvester McCoy and Paul McGann", + "57280cac2ca10214002d9cab": "Colin Baker and Sylvester McCoy", + "57280cac2ca10214002d9cac": "2003", + "57280e323acd2414000df349": "The Time of the Doctor", + "57280e323acd2414000df34a": "The Brain of Morbius", + "57280e323acd2414000df34b": "Mawdryn Undead", + "57280e323acd2414000df34c": "The Brain of Morbius", + "57280e323acd2414000df34d": "1983", + "57280f0d3acd2414000df35b": "An Unearthly Child", + "57280f0d3acd2414000df35c": "Susan Foreman", + "57280f0d3acd2414000df35d": "2005", + "57280f0d3acd2414000df35e": "destroyed", + "57280f0d3acd2414000df35f": "Smith and Jones", + "5728103eff5b5019007d9c30": "human", + "5728103eff5b5019007d9c31": "The Deadly Assassin", + "5728103eff5b5019007d9c33": "Jo Grant", + "5728103eff5b5019007d9c34": "audience surrogates, through which the audience would discover information about the Doctor who was to act as a mysterious father figure", + "5728103eff5b5019007d9c32": "Romana", + "572811434b864d190016438c": "female", + "572811434b864d190016438d": "Rose Tyler (Billie Piper), Martha Jones (Freema Agyeman), and Donna Noble", + "572811434b864d190016438e": "The Eleventh Doctor", + "572811434b864d190016438f": "Pearl Mackie", + "572811434b864d1900164390": "Catherine Tate", + "572812142ca10214002d9d2a": "Russell T Davies", + "572812142ca10214002d9d2b": "series 1", + "572812142ca10214002d9d2c": "Cybermen", + "572812142ca10214002d9d2d": "series 3", + "572812142ca10214002d9d2e": "Zygons", + "572812eaff5b5019007d9c80": "The Dalek race", + "572812eaff5b5019007d9c81": "Skaro", + "572812eaff5b5019007d9c82": "mobility", + "572812eaff5b5019007d9c83": "Davros", + "572812eaff5b5019007d9c84": "eyestalk", + "572813b52ca10214002d9d68": "The Master", + "572813b52ca10214002d9d69": "the Doctor's archenemy", + "572813b52ca10214002d9d6a": "Eric Roberts", + "572813b52ca10214002d9d6b": "Professor Moriarty to the Doctor's Sherlock Holmes", + "572813b52ca10214002d9d6c": "Roger Delgado", + "572814882ca10214002d9d72": "Michelle Gomez", + "572814882ca10214002d9d73": "Utopia", + "572814882ca10214002d9d74": "2014", + "572814882ca10214002d9d75": "Missy", + "572814882ca10214002d9d76": "Michelle Gomez", + "572816213acd2414000df429": "Ron Grainer", + "572816213acd2414000df42a": "BBC Radiophonic Workshop", + "572816213acd2414000df42b": "musique concr\u00e8te", + "572816213acd2414000df42c": "1979\u201380", + "572816213acd2414000df42d": "\"Did I write that?\"", + "5728177f2ca10214002d9db0": "Peter Howell", + "5728177f2ca10214002d9db1": "John Debney", + "5728177f2ca10214002d9db2": "Seventh", + "5728177f2ca10214002d9db3": "John Debney", + "572817802ca10214002d9db4": "The Christmas Invasion", + "5728185f3acd2414000df45b": "Voyage of the Damned", + "5728185f3acd2414000df45d": "Classic FM", + "5728185f3acd2414000df45c": "Voyage of the Damned", + "5728185f3acd2414000df45e": "228", + "5728185f3acd2414000df45f": "Gold", + "572819864b864d190016447e": "Jon Pertwee", + "572819864b864d190016447f": "Mankind", + "572819864b864d1900164480": "24", + "572819864b864d1900164481": "Doctorin' the Tardis", + "572819864b864d1900164482": "Mankind", + "57281a952ca10214002d9dea": "Dudley Simpson", + "57281a952ca10214002d9deb": "Planet of Giants", + "57281a952ca10214002d9dec": "first 15 years", + "57281a952ca10214002d9ded": "Planet of Giants", + "57281a952ca10214002d9dee": "The Talons of Weng-Chiang", + "57281bbc2ca10214002d9dfa": "BBC National Orchestra of Wales", + "57281bbc2ca10214002d9dfb": "David Tennant", + "57281bbc2ca10214002d9dfc": "27 July 2008", + "57281bbc2ca10214002d9dfd": "Music of the Spheres", + "57281bbc2ca10214002d9dfe": "Murray Gold and Ben Foster", + "57281cb22ca10214002d9e1e": "Six", + "57281cb22ca10214002d9e1f": "the second and third", + "57281cb22ca10214002d9e20": "music from the 2008\u20132010 specials", + "57281cb22ca10214002d9e21": "The Next Doctor to End of Time Part 2", + "57281cb22ca10214002d9e22": "8 November 2010", + "57281f203acd2414000df4f5": "The Day of the Doctor", + "57281f203acd2414000df4f6": "the Twelfth Doctor", + "57281f203acd2414000df4f7": "current Doctor Who logo", + "57281f203acd2414000df4f8": "The logo", + "57281f203acd2414000df4f9": "The Day of the Doctor", + "57282036ff5b5019007d9d9c": "the assassination of John F. Kennedy", + "57282036ff5b5019007d9d9d": "BBC One channel", + "57282036ff5b5019007d9d9e": "1970s", + "57282036ff5b5019007d9d9f": "circa 1964\u20131965", + "57282036ff5b5019007d9da0": "BBC Three", + "572821ceff5b5019007d9db2": "2005", + "572821ceff5b5019007d9db3": "Its late 1980s performance of three to five million viewers was seen as poor", + "572821ceff5b5019007d9db4": "Coronation Street", + "572821ceff5b5019007d9db5": "most popular", + "572821ceff5b5019007d9db6": "2005", + "5728231fff5b5019007d9dd4": "PBS", + "5728231fff5b5019007d9dd5": "New Zealand", + "5728231fff5b5019007d9dd6": "Edmonton, Canada", + "5728231fff5b5019007d9dd7": "15", + "5728231fff5b5019007d9dd8": "23 November", + "5728245b2ca10214002d9ed6": "ABC", + "5728245b2ca10214002d9ed7": "partial funding", + "5728245b2ca10214002d9ed8": "SyFy", + "5728245b2ca10214002d9ed9": "weekly screenings", + "5728245b2ca10214002d9eda": "ABC", + "572825714b864d1900164590": "1976", + "572825714b864d1900164591": "The Talons of Weng-Chiang", + "572825714b864d1900164592": "YTV", + "572825714b864d1900164593": "The Talons of Weng-Chiang", + "572825714b864d1900164594": "Judith Merril", + "572826762ca10214002d9f2c": "Christopher Eccleston", + "572826762ca10214002d9f2d": "excerpts from the Doctor Who Confidential documentary", + "572826762ca10214002d9f2e": "The Christmas Invasion", + "572826762ca10214002d9f2f": "9 October 2006", + "572826762ca10214002d9f30": "Thanksgiving", + "5728274cff5b5019007d9e26": "United Kingdom, Australia, Canada and the United States", + "5728274cff5b5019007d9e27": "Eight original series serials", + "5728274cff5b5019007d9e28": "Doctor Who (The Infinite Quest", + "5728274cff5b5019007d9e29": "Spearhead from Space", + "5728274cff5b5019007d9e2a": "2009", + "572828383acd2414000df5c3": "Trevor Martin", + "572828383acd2414000df5c4": "Doctor Who \u2013 The Ultimate Adventure", + "572828383acd2414000df5c5": "The Curse of the Daleks", + "572828383acd2414000df5c6": "Doctor Who \u2013 The Ultimate Adventure", + "572828383acd2414000df5c7": "David Banks", + "572829532ca10214002d9fa2": "Torchwood", + "572829532ca10214002d9fa3": "22 October 2006", + "572829532ca10214002d9fa4": "2008", + "572829532ca10214002d9fa5": "Children of Earth", + "572829532ca10214002d9fa6": "Torchwood: Miracle Day", + "57282f204b864d190016468a": "Elisabeth Sladen", + "57282f204b864d190016468b": "24 September 2007", + "57282f204b864d190016468c": "2009", + "57282f204b864d190016468d": "2010", + "57282f204b864d190016468e": "the death of Elisabeth Sladen", + "5728303e4b864d19001646aa": "Dimensions in Time", + "5728303e4b864d19001646ab": "Children in Need", + "5728303e4b864d19001646ac": "EastEnders", + "5728303e4b864d19001646ad": "darkened", + "5728303e4b864d19001646ae": "Pulfrich effect", + "572831512ca10214002da04a": "Doctor Who and the Curse of Fatal Death", + "572831512ca10214002da04b": "four", + "572831512ca10214002da04c": "Richard E. Grant, Jim Broadbent, Hugh Grant and Joanna Lumley", + "572831512ca10214002da04d": "Joanna Lumley", + "572831512ca10214002da04e": "head writer and executive producer", + "572833662ca10214002da086": "Star Trek: The Next Generation", + "572833662ca10214002da087": "Blue Harvest\" and \"420", + "572833662ca10214002da088": "Queer as Folk", + "572833662ca10214002da089": "Oliver", + "572833662ca10214002da08a": "Brisingr and High Wizardry", + "572834524b864d1900164716": "The Chase", + "572834524b864d1900164717": "21-minute", + "572834524b864d1900164718": "Doctor Who and the Pescatons", + "572834524b864d1900164719": "1966", + "572834524b864d190016471a": "Slipback", + "572835854b864d190016472e": "the Fifth, Sixth and Seventh Doctors", + "572835854b864d190016472f": "Destiny of the Doctor", + "572835854b864d1900164730": "Big Finish Productions", + "572835854b864d1900164731": "1999", + "572835854b864d1900164732": "2012", + "572836732ca10214002da0dc": "1991", + "572836732ca10214002da0dd": "mid-sixties", + "572836732ca10214002da0de": "since 1979", + "572836732ca10214002da0df": "Panini", + "572836732ca10214002da0e0": "BBC Books", + "572837402ca10214002da0f4": "1960s", + "572837402ca10214002da0f5": "BBC Television", + "572837402ca10214002da0f6": "producers", + "572837402ca10214002da0f7": "the BBC", + "572838323acd2414000df737": "2006", + "572838323acd2414000df738": "2005\u20132010", + "572838323acd2414000df739": "2011", + "572838323acd2414000df73a": "Michelle Gomez", + "572838323acd2414000df73b": "BAFTA", + "57283a392ca10214002da118": "Guinness World Records", + "57283a392ca10214002da119": "Doctor Who", + "57283a392ca10214002da11a": "electronic", + "57283a392ca10214002da11b": "2013", + "57283a392ca10214002da11c": "its 50th anniversary special", + "57283b91ff5b5019007d9fa4": "11", + "57283b91ff5b5019007d9fa5": "Doctor Who", + "57283b91ff5b5019007d9fa6": "third", + "57283b91ff5b5019007d9fa7": "SFX magazine", + "57283b91ff5b5019007d9fa8": "eight", + "57283ce72ca10214002da14c": "Best Drama Series", + "57283ce72ca10214002da14d": "five", + "57283ce72ca10214002da14e": "five", + "57283ce72ca10214002da14f": "2009", + "57283ce72ca10214002da150": "2010 Mind Mental Health Media Awards", + "57283dbeff5b5019007d9fc6": "six", + "57283dbeff5b5019007d9fc7": "over 200", + "57283dbeff5b5019007d9fc8": "over 200", + "57283dbeff5b5019007d9fc9": "Matt Smith", + "57283dbeff5b5019007d9fca": "The Waters of Mars", + "57283e652ca10214002da166": "Spike Milligan", + "57283e652ca10214002da167": "Jon Culshaw", + "57283e652ca10214002da168": "invades his bathroom", + "57283e652ca10214002da16a": "Doctor Who fandom", + "57283e652ca10214002da169": "BBC Dead Ringers", + "57283c464b864d19001647c8": "private research", + "57283c464b864d19001647c9": "1890", + "57283c464b864d19001647ca": "seven", + "57283c464b864d19001647cb": "four", + "57283c464b864d19001647cc": "5,000 students in the College and around 15,000", + "57283db6ff5b5019007d9fbc": "various academic disciplines", + "57283db6ff5b5019007d9fbd": "Chicago's physics department", + "57283db6ff5b5019007d9fbe": "Stagg Field", + "57283db6ff5b5019007d9fbf": "University of Chicago Press", + "57283db6ff5b5019007d9fc0": "2020", + "57283f014b864d19001647e8": "American Baptist Education Society", + "57283f014b864d19001647e9": "John D. Rockefeller", + "57283f014b864d19001647ea": "William Rainey Harper", + "57283f014b864d19001647eb": "1891", + "57283f014b864d19001647ec": "1892", + "57284142ff5b5019007da00a": "John D. Rockefeller", + "57284142ff5b5019007da00b": "Silas B. Cobb", + "57284142ff5b5019007da00c": "Cobb Lecture Hall", + "57284142ff5b5019007da00d": "$100,000", + "57284142ff5b5019007da00e": "Charles L. Hutchinson", + "572843304b864d1900164848": "Shimer College", + "572843304b864d1900164849": "1896", + "572843304b864d190016484a": "made a grade of A for all four years", + "572843304b864d190016484b": "Several University of Chicago professors", + "572843304b864d190016484c": "1910", + "57284456ff5b5019007da05c": "Robert Maynard Hutchins", + "57284456ff5b5019007da060": "the Common Core", + "57284456ff5b5019007da05f": "to emphasize academics over athletics", + "57284456ff5b5019007da05e": "24-year", + "57284456ff5b5019007da05d": "1929", + "57284618ff5b5019007da0a8": "1950s", + "57284618ff5b5019007da0a9": "increasing crime and poverty", + "57284618ff5b5019007da0aa": "after their second year", + "57284618ff5b5019007da0ab": "Hyde Park", + "57284618ff5b5019007da0ac": "allowed very young students to attend college", + "572847ff3acd2414000df869": "1962", + "572847ff3acd2414000df86a": "off-campus rental policies", + "572847ff3acd2414000df86b": "1967", + "572847ff3acd2414000df86c": "two", + "572847ff3acd2414000df86d": "social and political action", + "572849b4ff5b5019007da0f2": "mid-2000s", + "572849b4ff5b5019007da0f3": "Milton Friedman Institute", + "572849b4ff5b5019007da0f4": "$200 million", + "572849b4ff5b5019007da0f5": "Chicago Theological Seminary", + "572849b4ff5b5019007da0f6": "David G. Booth", + "57284b904b864d19001648e2": "Main Quadrangles", + "57284b904b864d19001648e3": "six", + "57284b904b864d19001648e4": "Henry Ives Cobb", + "57284b904b864d19001648e5": "Magdalen Tower", + "57284b904b864d19001648e6": "Christ Church Hall", + "57284d484b864d1900164900": "1940s", + "57284d484b864d1900164901": "Eero Saarinen", + "57284d484b864d1900164902": "School of Social Service Administration", + "57284d484b864d1900164903": "Harris School of Public Policy Studies", + "57284d484b864d1900164904": "2003", + "57284e9fff5b5019007da150": "Singapore, London, and the downtown Streeterville neighborhood of Chicago", + "57284e9fff5b5019007da151": "the Seine", + "57284e9fff5b5019007da152": "2010", + "57284e9fff5b5019007da153": "Renmin University", + "57284e9fff5b5019007da154": "2015", + "5728501aff5b5019007da166": "a board of trustees", + "5728501aff5b5019007da167": "50", + "5728501aff5b5019007da168": "fourteen", + "5728501aff5b5019007da169": "Andrew Alper", + "5728501aff5b5019007da16a": "Daniel Diermeier", + "5728510f4b864d1900164936": "Higher Learning Commission", + "5728510f4b864d1900164937": "four", + "5728510f4b864d1900164938": "seven", + "57285213ff5b5019007da180": "50", + "57285213ff5b5019007da181": "28", + "57285213ff5b5019007da182": "five", + "57285213ff5b5019007da183": "New Collegiate Division", + "572853e8ff5b5019007da188": "Common Core", + "572853e8ff5b5019007da189": "17", + "572853e8ff5b5019007da18a": "intense", + "572853e8ff5b5019007da18b": "Uni in the USA", + "572855973acd2414000df925": "University of Chicago Laboratory Schools", + "572855973acd2414000df926": "Sonia Shankman Orthogenic School", + "572855973acd2414000df927": "four", + "572855973acd2414000df928": "public charter schools", + "572855973acd2414000df929": "University of Chicago campus", + "572856beff5b5019007da190": "six", + "572856beff5b5019007da191": "9.8 million", + "572856beff5b5019007da192": "Regenstein Library", + "572856beff5b5019007da193": "2011", + "572856beff5b5019007da194": "1.3 million", + "57285841ff5b5019007da19a": "12", + "57285841ff5b5019007da19b": "113", + "57285841ff5b5019007da19c": "Oriental Institute", + "57285841ff5b5019007da19d": "Fermilab", + "57285841ff5b5019007da19e": "Sunspot, New Mexico", + "57286010ff5b5019007da1ca": "shaping ideas about the free market", + "57286010ff5b5019007da1cb": "Chicago Pile-1", + "57286010ff5b5019007da1cc": "the Miller\u2013Urey experiment", + "57286010ff5b5019007da1cd": "1953", + "572861cc4b864d190016495e": "1933", + "572861cc4b864d190016495f": "2000", + "572861cc4b864d1900164960": "1996", + "572861cc4b864d1900164961": "2002", + "572861cc4b864d1900164962": "Several thousand", + "572863363acd2414000df985": "5,792", + "572863363acd2414000df986": "3,468", + "572863363acd2414000df987": "5,984", + "572863363acd2414000df988": "5,792", + "572863363acd2414000df989": "international students", + "572864542ca10214002da2de": "University Athletic Association", + "572864542ca10214002da2df": "NCAA's Division III", + "572864542ca10214002da2e0": "Big Ten Conference", + "572864542ca10214002da2e1": "Jay Berwanger", + "572864542ca10214002da2e2": "University President Robert Maynard Hutchins de-emphasized varsity athletics in 1939 and dropped football", + "5728659f4b864d190016498a": "400", + "5728659f4b864d190016498b": "Recognized Student Organizations", + "5728659f4b864d190016498c": "University of Chicago College Bowl Team", + "5728659f4b864d190016498d": "Doc Films", + "5728659f4b864d190016498e": "the nation's second oldest continuously running student improvisational theater troupe Off-Off Campus", + "5728667eff5b5019007da1fc": "graduate and undergraduate students", + "5728667eff5b5019007da1fd": "an Executive Committee", + "5728667eff5b5019007da1fe": "two", + "5728667eff5b5019007da1ff": "$2 million", + "572867543acd2414000df9a1": "fifteen", + "572867543acd2414000df9a2": "seven", + "572867543acd2414000df9a3": "Alpha Phi Omega", + "572867543acd2414000df9a4": "Four", + "572867543acd2414000df9a5": "ten", + "5728683b3acd2414000df9af": "May", + "5728683b3acd2414000df9b0": "1987", + "5728683b3acd2414000df9b1": "Festival of the Arts", + "5728683b3acd2414000df9b2": "Kuviasungnerk/Kangeiko", + "5728683b3acd2414000df9b3": "Summer Breeze", + "57286951ff5b5019007da20e": "Satya Nadella", + "57286951ff5b5019007da20f": "Satya Nadella", + "57286951ff5b5019007da210": "Larry Ellison", + "57286951ff5b5019007da211": "Satya Nadella", + "57286951ff5b5019007da212": "James O. McKinsey", + "57286ab72ca10214002da31e": "Saul Alinsky", + "57286ab72ca10214002da31f": "David Axelrod", + "57286ab72ca10214002da320": "Robert Bork", + "57286ab72ca10214002da321": "Masaaki Shirakawa", + "57286ab72ca10214002da322": "Eliot Ness", + "57286bf84b864d19001649d4": "Allan Bloom", + "57286bf84b864d19001649d6": "Kurt Vonnegut", + "57286bf84b864d19001649d2": "Lauren Oliver", + "57286bf84b864d19001649d5": "Allan Bloom", + "57286bf84b864d19001649d3": "Philip Roth", + "57286d7d4b864d19001649e0": "Philip Glass", + "57286d7d4b864d19001649e1": "Alex Seropian", + "57286d7d4b864d19001649e2": "Halo", + "57286d7d4b864d19001649e3": "Ed Asner", + "57286d7d4b864d19001649e4": "Mike Nichols", + "57286ec63acd2414000df9d1": "Carl Sagan", + "57286ec63acd2414000df9d2": "John M. Grunsfeld", + "57286ec63acd2414000df9d3": "David Suzuki", + "57286ec63acd2414000df9d4": "John B. Goodenough", + "57286ec63acd2414000df9d5": "Clair Cameron Patterson", + "572870b2ff5b5019007da222": "Milton Friedman", + "572870b2ff5b5019007da223": "Margaret Thatcher", + "572870b2ff5b5019007da224": "Paul Samuelson", + "572870b2ff5b5019007da225": "Eugene Fama", + "572871bc4b864d1900164a04": "David Graeber and Donald Johanson", + "572871bc4b864d1900164a05": "Samuel Reshevsky", + "572871bc4b864d1900164a06": "Samuel P. Huntington", + "572872dd2ca10214002da37e": "A. A. Michelson", + "572872dd2ca10214002da37f": "Robert A. Millikan", + "572872dd2ca10214002da380": "Arthur H. Compton", + "572872dd2ca10214002da381": "Edward Teller", + "572872dd2ca10214002da382": "Maria Goeppert-Mayer", + "5728742cff5b5019007da246": "James Henry Breasted", + "5728742cff5b5019007da247": "Alberto Calder\u00f3n", + "5728742cff5b5019007da248": "Ted Fujita", + "5728742cff5b5019007da249": "Glenn T. Seaborg", + "5728742cff5b5019007da24a": "Charles Brenton Huggins and Janet Rowley", + "5728759cff5b5019007da25b": "Raghuram Rajan", + "5728759cff5b5019007da25a": "Goldman Sachs", + "5728759cff5b5019007da25c": "David Bevington", + "5728759cff5b5019007da25d": "John Mearsheimer and Robert Pape", + "5728759cff5b5019007da25e": "Neil Shubin and Paul Sereno", + "57285ed5ff5b5019007da1b6": "Great Yuan", + "57285ed5ff5b5019007da1b7": "Great Yuan", + "57285ed5ff5b5019007da1b8": "Kublai Khan", + "57285ed5ff5b5019007da1b9": "Kublai Khan", + "57285ed5ff5b5019007da1ba": "1271", + "572860e03acd2414000df977": "the Mongol Empire", + "572860e03acd2414000df978": "Ming dynasty", + "572860e03acd2414000df979": "Ming dynasty", + "572860e03acd2414000df97a": "Genghis Khan", + "57286192ff5b5019007da1dc": "1271", + "57286192ff5b5019007da1dd": "Commentaries on the Classic of Changes (I Ching) section regarding Qi\u00e1n", + "57286192ff5b5019007da1de": "Mongol dynasty\" or \"Mongol Dynasty of China", + "57286192ff5b5019007da1df": "Great Yuan Great Mongol State", + "57286192ff5b5019007da1e0": "Great Khan", + "572863c72ca10214002da2d4": "Mongol and Turkic tribes of the steppes", + "572863c72ca10214002da2d5": "1206", + "572863c72ca10214002da2d6": "\u00d6gedei Khan", + "572863c72ca10214002da2d7": "1206", + "572863c72ca10214002da2d8": "third son", + "572864dd4b864d1900164976": "the Jin", + "572864dd4b864d1900164977": "Xiao Zhala", + "572864dd4b864d1900164978": "Khitan", + "572864dd4b864d1900164979": "10,000", + "572864dd4b864d190016497a": "3", + "5728661e2ca10214002da2e8": "Han Chinese", + "5728661e2ca10214002da2e9": "Jin dynasty", + "5728661e2ca10214002da2ea": "Interethnic marriage between Han and Jurchen", + "5728661e2ca10214002da2eb": "Shi Bingzhi", + "5728661e2ca10214002da2ec": "Song dynasty", + "572867212ca10214002da2f2": "M\u00f6ngke Khan", + "572867212ca10214002da2f3": "southern China", + "572867212ca10214002da2f4": "1259", + "572867212ca10214002da2f5": "Ariq B\u00f6ke", + "572867212ca10214002da2f6": "Zhongtong", + "572867d72ca10214002da2fc": "Ogedei", + "572867d72ca10214002da2fd": "the south", + "572867d72ca10214002da2fe": "prince Wonjong", + "572867d72ca10214002da2ff": "northeast border", + "572867d72ca10214002da300": "1262", + "572869b84b864d19001649ae": "preserving Mongol interests in China", + "572869b84b864d19001649b0": "Imperial Secretariat", + "572869b84b864d19001649b2": "Han Chinese", + "572869b84b864d19001649b1": "three", + "572869b84b864d19001649af": "salt and iron", + "57286b003acd2414000df9c1": "Karakorum in Mongolia", + "57286b003acd2414000df9c2": "Khanbaliq", + "57286b003acd2414000df9c3": "1264", + "57286b003acd2414000df9c4": "Zhongdu", + "57286b003acd2414000df9c5": "Confucian propriety and ancestor veneration", + "57286bb84b864d19001649c8": "commercial, scientific, and cultural", + "57286bb84b864d19001649c9": "Mongol peace", + "57286bb84b864d19001649ca": "southern China", + "57286bb84b864d19001649cb": "southern China to Daidu in the north", + "57286bb84b864d19001649cc": "Marco Polo", + "57286c8cff5b5019007da218": "Song Emperor", + "57286c8cff5b5019007da219": "1115\u20131234", + "57286c8cff5b5019007da21a": "1115\u20131234", + "57286c8cff5b5019007da21b": "Kong Duancao", + "57286c8cff5b5019007da21c": "30,000", + "57286d4f2ca10214002da328": "northern China", + "57286d4f2ca10214002da329": "1268 and 1273", + "57286d4f2ca10214002da32a": "Yangzi River basin", + "57286d4f2ca10214002da32b": "Hangzhou", + "57286d4f2ca10214002da32c": "drowned", + "57286dfa2ca10214002da332": "1279", + "57286dfa2ca10214002da333": "an inauspicious typhoon", + "57286dfa2ca10214002da334": "Vietnam \u0110\u1ea1i Vi\u1ec7t", + "57286dfa2ca10214002da335": "Battle of B\u1ea1ch \u0110\u1eb1ng", + "57286dfa2ca10214002da336": "1288", + "57286ead2ca10214002da346": "1253", + "57286ead2ca10214002da347": "Zhenjin", + "57286ead2ca10214002da348": "1285", + "57286ead2ca10214002da349": "Emperor Chengzong", + "57286ead2ca10214002da34a": "1294 to 1307", + "57286f373acd2414000df9db": "Buyantu Khan", + "57286f373acd2414000df9dc": "support and adopt mainstream Chinese culture", + "57286f373acd2414000df9dd": "Li Meng", + "57286f373acd2414000df9de": "Department of State Affairs", + "57286f373acd2414000df9df": "1313", + "57286fa83acd2414000df9e5": "Emperor Gegeen Khan", + "57286fa83acd2414000df9e6": "1321 to 1323", + "57286fa83acd2414000df9e7": "Baiju", + "57286fa83acd2414000df9e8": "the comprehensive institutions of the Great Yuan", + "57286fa83acd2414000df9e9": "five", + "5728705c2ca10214002da35a": "Shangdu", + "5728705c2ca10214002da35b": "the War of the Two Capitals", + "5728705c2ca10214002da35c": "four days", + "5728705c2ca10214002da35d": "El Tem\u00fcr", + "5728705c2ca10214002da35e": "Ragibagh", + "5728710c3acd2414000df9ef": "cultural contribution", + "5728710c3acd2414000df9f0": "Academy of the Pavilion of the Star of Literature", + "5728710c3acd2414000df9f1": "1329", + "5728710c3acd2414000df9f2": "Jingshi Dadian", + "5728710c3acd2414000df9f3": "Confucianism", + "572871bd3acd2414000dfa03": "1332", + "572871bd3acd2414000dfa04": "Emperor Ningzong", + "572871bd3acd2414000dfa05": "13", + "572871bd3acd2414000dfa06": "nine", + "572871bd3acd2414000dfa07": "Liao, Jin, and Song", + "572872822ca10214002da374": "struggle, famine, and bitterness", + "572872822ca10214002da375": "the Mongols beyond the Middle Kingdom saw them as too Chinese", + "572872822ca10214002da376": "the army and the populace", + "572872822ca10214002da377": "Outlaws", + "572872822ca10214002da378": "intrigues and rivalries", + "57287338ff5b5019007da232": "late 1340s onwards", + "57287338ff5b5019007da233": "Red Turban Rebellion", + "57287338ff5b5019007da234": "fear of betrayal", + "57287338ff5b5019007da235": "Red Turban rebels", + "57287338ff5b5019007da236": "1368\u20131644", + "572878942ca10214002da3a2": "communications between Yuan dynasty and its ally and subordinate in Persia, the Ilkhanate", + "572878942ca10214002da3a3": "communications between Yuan dynasty", + "572878942ca10214002da3a4": "Ilkhanate", + "572878942ca10214002da3a5": "carrots, turnips, new varieties of lemons, eggplants, and melons, high-quality granulated sugar, and cotton", + "572879574b864d1900164a14": "Western", + "572879574b864d1900164a15": "Nestorianism and Roman Catholicism", + "572879574b864d1900164a16": "Taoism", + "572879574b864d1900164a17": "Confucian", + "572879574b864d1900164a18": "travel literature, cartography, geography, and scientific education", + "57287b4a4b864d1900164a28": "Marco Polo", + "57287b4a4b864d1900164a29": "Cambaluc", + "57287b4a4b864d1900164a2a": "Il milione", + "57287b4a4b864d1900164a2b": "Il milione", + "57287b4a4b864d1900164a2c": "through contact with Persian traders", + "57287c142ca10214002da3d0": "Guo Shoujing", + "57287c142ca10214002da3d1": "365.2425 days of the year", + "57287c142ca10214002da3d2": "granaries", + "57287c142ca10214002da3d3": "Beijing", + "57287c142ca10214002da3d4": "sorghum", + "57287ccb2ca10214002da3da": "non-native Chinese people", + "57287ccb2ca10214002da3db": "Eternal Heaven", + "57287ccb2ca10214002da3dc": "Song dynasty and the Ming dynasty", + "57287ccb2ca10214002da3dd": "Song dynasty and the Ming dynasty", + "57287ccb2ca10214002da3de": "a period of foreign domination", + "57287d4a2ca10214002da3e4": "Han Chinese, Khitans, Jurchens, Mongols, and Tibetan Buddhists", + "57287d4a2ca10214002da3e5": "Tang, Song, as well as Khitan Liao and Jurchen Jin dynasties", + "57287d4a2ca10214002da3e6": "Liu Bingzhong and Yao Shu", + "57287d4a2ca10214002da3e7": "traditional Chinese tripartite", + "57287d4a2ca10214002da3e8": "civil, military, and censorial offices", + "57287ddf3acd2414000dfa3f": "the Privy Council", + "57287ddf3acd2414000dfa40": "since the Sui and Tang dynasties", + "57287ddf3acd2414000dfa41": "Mongols and Semuren", + "57287ddf3acd2414000dfa42": "native Chinese dynasties", + "57287e512ca10214002da3f8": "1269", + "57287e512ca10214002da3f9": "Mongolian, Tibetan, and Chinese", + "57287e512ca10214002da3fa": "converse well in the language", + "57287e512ca10214002da3fb": "Tugh Temur", + "57287e512ca10214002da3fc": "Emperor Wenzong", + "57287ee3ff5b5019007da274": "1290", + "57287ee3ff5b5019007da275": "1291", + "57287ee3ff5b5019007da276": "harvests of their Chinese tenants eaten up by costs of equipping and dispatching men for their tours of duty", + "57287f6a3acd2414000dfa51": "painting, mathematics, calligraphy, poetry, and theater", + "57287f6a3acd2414000dfa52": "painting, poetry, and calligraphy", + "57287f6a3acd2414000dfa53": "Song dynasty", + "57287f6a3acd2414000dfa54": "the qu", + "57287f6a3acd2414000dfa55": "zaju", + "57287fec4b864d1900164a3c": "western khanates", + "57287fec4b864d1900164a3d": "Buddhism", + "57287fec4b864d1900164a3e": "Tibetan Buddhism", + "57287fec4b864d1900164a3f": "Bureau of Buddhist and Tibetan Affairs", + "57287fec4b864d1900164a40": "Sakya", + "5728804b4b864d1900164a46": "1249", + "5728804b4b864d1900164a47": "1314", + "5728804b4b864d1900164a48": "matrices", + "5728804b4b864d1900164a49": "polynomial algebra", + "5728804b4b864d1900164a4a": "1303", + "5728809f2ca10214002da40c": "applied mathematics", + "5728809f2ca10214002da40d": "cubic interpolation formula", + "5728809f2ca10214002da40e": "the Shoushi Li", + "5728809f2ca10214002da40f": "the Shoushi Li", + "5728809f2ca10214002da410": "1281", + "572881022ca10214002da416": "non-Mongol physicians", + "572881022ca10214002da417": "herbal remedies", + "572881022ca10214002da418": "herbal remedies", + "572881022ca10214002da419": "Imperial Academy of Medicine", + "572881022ca10214002da41a": "it ensured a high income", + "572881704b864d1900164a50": "Four Great Schools\" that the Yuan inherited from the Jin dynasty. All four", + "572881704b864d1900164a51": "based on the same intellectual foundation", + "572881704b864d1900164a52": "Under the Mongols, the practice of Chinese medicine spread to other parts of the empire", + "572881704b864d1900164a53": "acupuncture, moxibustion, pulse diagnosis, and various herbal drugs and elixirs", + "572881704b864d1900164a54": "1347", + "572881d34b864d1900164a5a": "Muslim medicine", + "572881d34b864d1900164a5b": "Jesus the Interpreter", + "572881d34b864d1900164a5c": "1263", + "572881d34b864d1900164a5d": "humoral system", + "572881d34b864d1900164a5e": "yin-yang and wuxing philosophy", + "572882242ca10214002da420": "through Kingdom of Qocho and Tibetan intermediaries", + "572882242ca10214002da421": "Wang Zhen", + "572882242ca10214002da422": "12th century", + "572882242ca10214002da423": "T\u00f6regene Khatun", + "572882242ca10214002da424": "1273", + "5728827b2ca10214002da42a": "chao", + "5728827b2ca10214002da42b": "bark of mulberry trees", + "5728827b2ca10214002da42c": "1275", + "5728827b2ca10214002da42d": "woodblocks", + "5728827b2ca10214002da42e": "1294", + "572883153acd2414000dfa6f": "patrimonial feudalism and the traditional Chinese autocratic-bureaucratic system", + "572883153acd2414000dfa70": "Mongolian patrimonial feudalism and the traditional Chinese autocratic-bureaucratic system", + "572883153acd2414000dfa71": "various allied groups from Central Asia and the western end of the empire", + "572883153acd2414000dfa72": "The unequal treatment is possibly due to the fear of transferring power to the ethnic Chinese under their rule", + "572883153acd2414000dfa73": "Ilkhanate", + "572883a33acd2414000dfa79": "Central Asian Muslims", + "572883a33acd2414000dfa7a": "Han Chinese and Khitans", + "572883a33acd2414000dfa7b": "Besh Baliq, Almaliq, and Samarqand", + "572883a33acd2414000dfa7c": "artisans and farmers", + "572883a33acd2414000dfa7d": "Qara-Khitay", + "57288428ff5b5019007da28e": "circumcision", + "57288428ff5b5019007da28f": "Kosher butchering", + "57288428ff5b5019007da290": "Zhu Yuanzhang", + "57288428ff5b5019007da291": "thanks", + "57288428ff5b5019007da292": "The Muslims in the semu class", + "5728848cff5b5019007da298": "Frederick W. Mote", + "5728848cff5b5019007da299": "social power and wealth", + "5728848cff5b5019007da29a": "rich and well socially standing", + "5728848cff5b5019007da29b": "ill treated", + "572885023acd2414000dfa83": "Northern Chinese", + "572885023acd2414000dfa84": "Northern Chinese", + "572885023acd2414000dfa85": "southern China withstood and fought to the last before caving in", + "572885023acd2414000dfa86": "southern China withstood and fought to the last before caving in", + "572885023acd2414000dfa87": "private southern Chinese manufacturers and merchants", + "5728855d3acd2414000dfa8d": "Uighurs of the Kingdom of Qocho", + "5728855d3acd2414000dfa8e": "Karluk Kara-Khanid ruler", + "5728855d3acd2414000dfa8f": "Korean King", + "5728855d3acd2414000dfa90": "the Uighurs surrendered to the Mongols first", + "572885c44b864d1900164a78": "Central Region", + "572885c44b864d1900164a79": "Central Secretariat", + "572885c44b864d1900164a7a": "Khanbaliq", + "572885c44b864d1900164a7b": "Beijing", + "572885c44b864d1900164a7c": "Zhongshu Sheng", + "5728dab94b864d1900164f96": "Africa", + "5728dab94b864d1900164f97": "East African Community", + "5728dab94b864d1900164f98": "Nairobi", + "5728dab94b864d1900164f99": "Tanzania", + "5728dab94b864d1900164f9a": "45 million", + "5728de0e2ca10214002da9dc": "tropical", + "5728de0e2ca10214002da9dd": "cooler", + "5728de0e2ca10214002da9de": "Mount Kenya", + "5728de0e2ca10214002da9df": "Somalia and Ethiopia", + "5728de0e2ca10214002da9e0": "safaris", + "5728ef8d2ca10214002daac2": "since the Lower Paleolithic period", + "5728ef8d2ca10214002daac3": "first millennium AD", + "5728ef8d2ca10214002daac4": "Bantu and Nilotic", + "5728ef8d2ca10214002daac5": "19th century", + "5728ef8d2ca10214002daac6": "December 1963", + "5728f5376aef0514001548c4": "Mount Kenya", + "5728f5376aef0514001548c5": "Kikuyu, Embu and Kamba words Kirinyaga, Kirenyaa and Kiinyaa", + "5728f5376aef0514001548c6": "God's resting place", + "5728f9342ca10214002dab52": "Kenia and Kegnia", + "5728f9342ca10214002dab53": "a very precise notation of a correct African pronunciation", + "5728f9342ca10214002dab54": "Joseph Thompsons", + "5728f9342ca10214002dab55": "1882", + "5728f9cf4b864d1900165166": "lion, leopard, buffalo, rhinoceros, and elephant", + "5728f9cf4b864d1900165167": "lion, leopard, buffalo, rhinoceros, and elephant", + "5728f9cf4b864d1900165168": "Masai Mara", + "5728f9cf4b864d1900165169": "June and September", + "5728f9cf4b864d190016516a": "2,900 kilometres", + "5728fa576aef051400154920": "more than 20 million years ago", + "5728fa576aef051400154921": "Pleistocene epoch", + "5728fa576aef051400154922": "Richard Leakey", + "5728fa576aef051400154923": "1.6-million-year-old", + "5728fa576aef051400154924": "Mary Leakey and Louis Leakey", + "5728fd9b3f37b31900477f3b": "The Swahili", + "5728fd9b3f37b31900477f3c": "Mombasa", + "5728fd9b3f37b31900477f3d": "Duarte Barbosa", + "5728fea1af94a219006a9ef5": "the Kenyan Coast", + "5728fea1af94a219006a9ef6": "Malindi", + "5728fea1af94a219006a9ef7": "14th century", + "5729024f1d04691400778f5f": "August 1914", + "5729024f1d04691400778f60": "British East Africa (as the Protectorate was generally known) and German East Africa", + "5729024f1d04691400778f61": "Lt Col Paul von Lettow-Vorbeck", + "5729024f1d04691400778f62": "guerrilla warfare campaign", + "5729024f1d04691400778f63": "Northern Rhodesia", + "572903d96aef0514001549a4": "The central highlands", + "572903d96aef0514001549a5": "itinerant farmers", + "572903d96aef0514001549a6": "banned the growing of coffee", + "572903d96aef0514001549a7": "80,000", + "5729046aaf94a219006a9f4d": "15 January 1954", + "5729046aaf94a219006a9f4e": "effectively placed Nairobi under military siege", + "5729046aaf94a219006a9f4f": "24 April 1954", + "5729046aaf94a219006a9f50": "4,686", + "5729046aaf94a219006a9f51": "Swynnerton Plan", + "572906e23f37b31900477f8d": "1957", + "572906e23f37b31900477f8e": "Kenya African National Union", + "572906e23f37b31900477f8f": "12 December 1963", + "572906e23f37b31900477f90": "1963", + "572906e23f37b31900477f91": "Republic of Kenya", + "572909406aef0514001549dc": "queuing) system, where voters were supposed to line up behind their favoured candidates instead of a secret ballot", + "572909406aef0514001549dd": "widespread agitation for constitutional reform", + "572909406aef0514001549de": "Daniel arap Moi", + "572909ebaf94a219006a9fc5": "presidential representative democratic republic", + "572909ebaf94a219006a9fc6": "head of state and head of government", + "572909ebaf94a219006a9fc7": "the government", + "572909ebaf94a219006a9fc8": "the government and the National Assembly and the Senate", + "572909ebaf94a219006a9fc9": "Judiciary", + "57290b21af94a219006a9fcf": "low", + "57290b21af94a219006a9fd0": "prevalence of public sector corruption", + "57290b21af94a219006a9fd1": "139th", + "57290b21af94a219006a9fd2": "curbing corruption from the Kenyan government", + "57290d811d04691400778fcf": "Party of National Unity", + "57290d811d04691400778fd0": "the Orange Democratic Movement (ODM)", + "57290d811d04691400778fd1": "complicity", + "57290d811d04691400778fd2": "Odinga", + "57290e153f37b31900477fd9": "programmes", + "57290e153f37b31900477fda": "the Truth, Justice and Reconciliation Commission", + "57290e153f37b31900477fdb": "Evangelical Lutheran Church in Kenya", + "57290e153f37b31900477fdc": "Kenya National Dialogue and Reconciliation process", + "57290ee2af94a219006a9fff": "28 February 2008", + "57290ee2af94a219006aa000": "Kenya's second Prime Minister", + "57290ee2af94a219006aa001": "PNU and ODM camps", + "57290ee2af94a219006aa002": "depending on each party's strength in Parliament", + "57290ee2af94a219006aa003": "until the end of the current Parliament", + "57290f963f37b31900477feb": "co-ordinate and supervise the functions of the Government", + "57290f963f37b31900477fec": "Jakaya Kikwete", + "57290f963f37b31900477fed": "Nairobi's Harambee House", + "57290f963f37b31900477fee": "29 February 2008", + "57290f963f37b31900477fef": "the two political parties would share power equally", + "572913626aef051400154a30": "would eliminate the position of Prime Minister and simultaneously reduce the powers of the President", + "572913626aef051400154a31": "4 August 2010", + "572913626aef051400154a32": "more power to local governments", + "572913626aef051400154a33": "27 August 2010", + "572913626aef051400154a34": "the Second Republic", + "572914441d04691400779025": "December 2014", + "572914441d04691400779026": "it infringed on democratic freedoms", + "572914441d04691400779027": "Opposition politicians, human rights groups, and nine Western countries", + "572914441d04691400779028": "it infringed on democratic freedoms", + "572914441d04691400779029": "The governments of the United States, Britain, Germany and France", + "572914f46aef051400154a46": "US President Barack Obama chose not to visit the country", + "572914f46aef051400154a47": "Barack Obama", + "572914f46aef051400154a48": "China", + "572914f46aef051400154a49": "July 2015", + "572915621d0469140077902f": "peacekeeping", + "572915621d04691400779030": "violence that subsequently engulfed the country", + "572915621d04691400779031": "human rights violations", + "572915e43f37b31900478005": "Kenya\u2019s armed forces", + "572915e43f37b31900478006": "Because the operations of the armed forces have been traditionally cloaked by the ubiquitous blanket of \u201cstate security", + "572915e43f37b31900478007": "credible claims of corruption were made with regard to recruitment and procurement of Armoured Personnel Carriers", + "572915e43f37b31900478008": "the wisdom and prudence of certain decisions of procurement", + "572916f16aef051400154a56": "Human Development Index", + "572916f16aef051400154a57": "Kenya", + "572916f16aef051400154a58": "less than $1.25", + "572916f16aef051400154a59": "frontier market", + "572917743f37b3190047800d": "rapid expansion in telecommunication and financial activity", + "572917743f37b3190047800f": "food security", + "572917743f37b31900478010": "Industry and manufacturing", + "572917743f37b3190047800e": "75%", + "572917ff6aef051400154a5e": "61%", + "572917ff6aef051400154a5f": "tourism", + "572917ff6aef051400154a60": "steady growth", + "572917ff6aef051400154a62": "coastal beaches and the game reserves", + "572917ff6aef051400154a61": "Germany and the United Kingdom", + "572918bd3f37b31900478016": "24%", + "572918bd3f37b31900478017": "tea, horticultural produce, and coffee", + "572918bd3f37b31900478015": "Agriculture", + "572918bd3f37b31900478018": "weather", + "57291a7b1d0469140077903f": "International Crops Research Institute for the Semi-Arid Tropics", + "57291a7b1d04691400779040": "drought resistant", + "57291a7b1d04691400779041": "by stimulating the growth of local seed production and agro-dealer networks for distribution and marketing", + "57291a7b1d04691400779042": "increase local producer prices by 20\u201325%", + "57291a7b1d04691400779043": "local producer prices", + "57291b461d04691400779049": "fertile highlands", + "57291b461d0469140077904a": "Tea, coffee, sisal, pyrethrum, corn, and wheat", + "57291b461d0469140077904b": "semi-arid savanna", + "57291b461d0469140077904c": "53%", + "57291b461d0469140077904d": "Kenyans for Kenya", + "57291beb1d04691400779053": "Kenya", + "57291beb1d04691400779054": "14%", + "57291beb1d04691400779055": "Nairobi, Mombasa and Kisumu", + "57291beb1d04691400779056": "small-scale manufacturing of household goods, motor-vehicle parts, and farm implements", + "57291d9e3f37b31900478035": "African Growth and Opportunity Act", + "57291d9e3f37b31900478036": "2000", + "57291dfaaf94a219006aa09b": "hydroelectric stations at dams along the upper Tana River", + "57291dfaaf94a219006aa09c": "along the upper Tana River", + "57291dfaaf94a219006aa09d": "1997", + "57291f153f37b31900478043": "Turkana", + "57291f153f37b31900478044": "10 billion", + "57291f153f37b31900478045": "Exploration", + "57291f153f37b31900478046": "20% to 25%", + "57291fb4af94a219006aa0b1": "$474 million", + "57291fb4af94a219006aa0b2": "largest source of foreign direct investment", + "57291fb4af94a219006aa0b3": "gain support", + "57291fb4af94a219006aa0b4": "Base Titanium, a subsidiary of Base resources of Australia, shipped its first major consignment of minerals to China", + "57291fb4af94a219006aa0b5": "environmental and social problems", + "57292046af94a219006aa0bb": "Asian Economic Tigers", + "57292046af94a219006aa0bc": "an economic development programme", + "57292046af94a219006aa0bd": "National Climate Change Action Plan", + "57292046af94a219006aa0be": "it hopes will put the country in the same league as the Asian Economic Tigers", + "57292046af94a219006aa0bf": "climate will be a central issue in the renewed Medium Term Plan", + "572920d73f37b31900478055": "agriculture", + "572920d73f37b31900478056": "30%", + "572920d73f37b31900478057": "9\u201318", + "572920d73f37b31900478058": "poverty, the lack of access to education and weak government institutions", + "572921646aef051400154a78": "English", + "572921646aef051400154a79": "English and Swahili", + "572921646aef051400154a7a": "commerce, schooling and government", + "572921646aef051400154a7b": "in the country", + "572922206aef051400154a8a": "Christian", + "572922206aef051400154a8b": "Protestant", + "572922206aef051400154a8c": "3 million", + "572922206aef051400154a8d": "Nairobi", + "57292449af94a219006aa0dd": "2.4%", + "57292449af94a219006aa0de": "Sixty percent", + "57292449af94a219006aa0df": "Christian", + "57292449af94a219006aa0e0": "300,000", + "572924b53f37b31900478067": "Nurses", + "572924b53f37b31900478068": "official registers include those who have died or left the profession", + "572924b53f37b31900478069": "65,000", + "572924b53f37b3190047806a": "7,000", + "572925491d046914007790c3": "Diseases of poverty", + "572925491d046914007790c4": "Half", + "572925491d046914007790c5": "Preventable diseases like malaria, HIV/AIDS, pneumonia, diarrhoea and malnutrition", + "572925491d046914007790c6": "weak policies, corruption, inadequate health workers, weak management and poor leadership", + "572925491d046914007790c7": "15 million", + "572925a81d046914007790cd": "British colonists", + "572925a81d046914007790ce": "12 December 1963", + "572925a81d046914007790cf": "Ominde Commission", + "572925a81d046914007790d0": "introduce changes that would reflect the nation's sovereignty", + "572925a81d046914007790d1": "7\u20134\u20132\u20133", + "572926086aef051400154ac2": "look at both the possibilities of setting up a second university in Kenya", + "572926086aef051400154ac3": "8\u20134\u20134 system", + "572926086aef051400154ac4": "8\u20134\u20134 system", + "572926086aef051400154ac5": "1992", + "572926653f37b31900478079": "January 1985", + "572926653f37b3190047807a": "vocational subjects", + "572926653f37b3190047807b": "the assumption that the new structure would enable school drop-outs at all levels either to be self-employed or to secure employment in the informal sector", + "572926653f37b3190047807c": "January 2003", + "572926653f37b3190047807d": "70%", + "572926d23f37b31900478083": "six years", + "572926d23f37b31900478084": "12 years", + "572926d23f37b31900478085": "join a vocational youth/village polytechnic or make their own arrangements for an apprenticeship program", + "572926d23f37b31900478086": "join a polytechnic or other technical college and study for three years or proceed directly to the university and study for four years", + "5729276c1d046914007790d7": "85%", + "5729276c1d046914007790d8": "three to five", + "5729276c1d046914007790d9": "admission to Standard One", + "5729276c1d046914007790da": "those who proceed to secondary school or vocational training", + "5729276c1d046914007790db": "Kenya Certificate of Secondary Education", + "572927d06aef051400154ade": "Kenya National Library Service", + "572927d06aef051400154adf": "establish, equip, manage and maintain national and public libraries in the country", + "572927d06aef051400154ae0": "peoples university", + "572927d06aef051400154ae1": "it is open to all irrespective of age, literacy level and has materials relevant to people of all walks of life", + "5729281baf94a219006aa11f": "cricket, rallying, football, rugby union and boxing", + "5729281baf94a219006aa120": "dominance in middle-distance and long-distance athletics", + "5729281baf94a219006aa121": "Kenyan athletes", + "5729281baf94a219006aa122": "Morocco and Ethiopia", + "572928bf6aef051400154af0": "six", + "572928bf6aef051400154af1": "several medals", + "572928bf6aef051400154af2": "IAAF Golden League jackpot", + "572928bf6aef051400154af3": "the defection of a number of Kenyan athletes to represent other countries", + "572928bf6aef051400154af4": "economic or financial factors", + "5729293d3f37b3190047809f": "volleyball", + "5729293d3f37b319004780a0": "Cricket", + "5729293d3f37b319004780a1": "2003", + "5729293d3f37b319004780a2": "Rakep Patel", + "5729293d3f37b319004780a3": "March 2007", + "57292994af94a219006aa131": "Safari Rally", + "57292994af94a219006aa132": "Safari Rally", + "57292994af94a219006aa133": "Bj\u00f6rn Waldeg\u00e5rd, Hannu Mikkola, Tommi M\u00e4kinen, Shekhar Mehta, Carlos Sainz and Colin McRae", + "572929d56aef051400154b0a": "three", + "572929d56aef051400154b0b": "4 pm", + "572929d56aef051400154b0c": "tea or porridge with bread, chapati, mahamri, boiled sweet potatoes or yams", + "572929d56aef051400154b0d": "Ugali with vegetables, sour milk, meat, fish or any other stew", + "57293b843f37b31900478133": "Intergovernmental Panel on Climate Change", + "57293b843f37b31900478134": "the World Meteorological Organization (WMO) and the United Nations Environment Programme (UNEP)", + "57293b843f37b31900478135": "greenhouse gas concentrations in the atmosphere", + "57293b843f37b31900478136": "United Nations Framework Convention on Climate Change", + "57293b843f37b31900478137": "Resolution 43/53", + "57293bc91d0469140077919b": "Hoesung Lee", + "57293bc91d0469140077919c": "Korean", + "57293bc91d0469140077919d": "Ismail El Gizouli", + "57293bc91d0469140077919e": "Hoesung Lee", + "57293bc91d0469140077919f": "February 2015", + "57293c246aef051400154bb8": "representatives appointed by governments and organizations", + "57293c246aef051400154bb9": "322", + "57293c246aef051400154bba": "322 persons in attendance at Sessions with about seven-eighths of participants being from governmental organizations", + "57293c246aef051400154bbb": "seven-eighths", + "57293ca73f37b3190047815b": "1989", + "57293ca73f37b3190047815c": "United Nations Environment Programme (UNEP) and the World Meteorological Organization (WMO)", + "57293ca73f37b3190047815e": "IPCC Trust Fund", + "57293ca73f37b3190047815f": "Financial Regulations", + "57293ca73f37b3190047815d": "IPCC Trust Fund", + "57293d116aef051400154bc8": "carry out research", + "57293d116aef051400154bc9": "published sources", + "57293d116aef051400154bca": "non-peer-reviewed sources", + "57293d116aef051400154bcb": "model results, reports from government agencies and non-governmental organizations, and industry journals", + "57293d6d1d046914007791b7": "two", + "57293d6d1d046914007791b8": "ten to fifteen", + "57293d6d1d046914007791b9": "ten to fifteen", + "57293d6d1d046914007791ba": "The coordinating lead authors", + "57293d6d1d046914007791bb": "Working Group chairs", + "57293e221d046914007791d5": "substantially increasing the atmospheric concentrations", + "57293e221d046914007791d6": "an additional warming of the Earth's surface", + "57293e221d046914007791d7": "over half", + "57293e221d046914007791d8": "business as usual", + "57293e221d046914007791d9": "0.3 to 0.6 \u00b0C", + "57293e983f37b3190047818b": "2001", + "57293e983f37b3190047818c": "16", + "57293e983f37b3190047818d": "Science", + "57293e983f37b3190047818e": "90%", + "57293e983f37b3190047818f": "between 1.4 and 5.8", + "57293f353f37b3190047819b": "Richard Lindzen", + "57293f353f37b3190047819c": "the full WGI report", + "57293f353f37b3190047819d": "John Houghton", + "57293f353f37b3190047819e": "co-chair", + "57293f353f37b3190047819f": "scientific evidence", + "57293f8a6aef051400154bde": "follows the same procedures as for IPCC Assessment Reports", + "57293f8a6aef051400154bdf": "2011", + "57293f8a6aef051400154be0": "2011", + "57293f8a6aef051400154be1": "requested by governments", + "572940246aef051400154bec": "Data Distribution Centre and the National Greenhouse Gas Inventories Programme", + "572940246aef051400154bed": "default emission factors", + "572940246aef051400154bee": "fuel consumption, industrial production", + "572940246aef051400154bef": "WMO Executive Council", + "572940973f37b319004781a5": "date", + "572940973f37b319004781a6": "the poor application of well-established IPCC procedures", + "572940973f37b319004781a7": "WWF report", + "572940973f37b319004781a8": "2035 has been correctly quoted by the IPCC from the WWF report", + "572941273f37b319004781ad": "chairman", + "572941273f37b319004781ae": "the direction of making it seem like climate change is more serious by overstating the impact", + "572941273f37b319004781af": "climate expert", + "572941273f37b319004781b0": "Himalayan glaciers", + "572941273f37b319004781b1": "generally unfounded and also marginal", + "57294209af94a219006aa201": "1999", + "57294209af94a219006aa202": "Michael E. Mann, Raymond S. Bradley and Malcolm K. Hughes", + "57294209af94a219006aa203": "hockey stick graph", + "57294209af94a219006aa204": "Jones et al. 1998, Pollack, Huang & Shen 1998, Crowley & Lowery 2000 and Briffa 2000", + "57294279af94a219006aa209": "between 1000 and 1900", + "57294279af94a219006aa20a": "Fred Singer", + "57294279af94a219006aa20b": "Capitol Hill", + "57294279af94a219006aa20c": "18 July 2000", + "57294279af94a219006aa20d": "Committee on Commerce, Science and Transportation hearing", + "572943ab1d04691400779219": "Rep. Joe Barton", + "572943ab1d0469140077921a": "Ed Whitfield", + "572943ab1d0469140077921b": "23 June 2005", + "572943ab1d0469140077921c": "Sherwood Boehlert", + "572943ab1d0469140077921d": "Sherwood Boehlert", + "572944e03f37b319004781e2": "2007", + "572944e03f37b319004781e1": "2007", + "572944e03f37b319004781e4": "Ten", + "572944e03f37b319004781e5": "divergence", + "572944e03f37b319004781e3": "Ten", + "572945b11d0469140077922f": "1 February 2007", + "572945b11d04691400779230": "compared IPCC 2001 projections on temperature and sea level change with observations", + "572945b11d04691400779231": "compared IPCC 2001 projections on temperature and sea level change with observations", + "572945b11d04691400779232": "compared IPCC 2001 projections on temperature and sea level change", + "572949306aef051400154c68": "projected rises in sea levels", + "572949306aef051400154c69": "0.5\u20131.4 m", + "572949306aef051400154c6a": "0.5\u20131.4 m", + "572949306aef051400154c6b": "2001", + "57294baaaf94a219006aa26b": "a long-time participant", + "57294baaaf94a219006aa26c": "Michael Oppenheimer", + "57294baaaf94a219006aa26d": "IPCC consensus approach", + "57294e6b1d04691400779275": "global regulation", + "57294e6b1d04691400779276": "Climate Change", + "57294e6b1d04691400779277": "states and governments", + "5729506d6aef051400154cac": "Sheldon Ungar", + "5729506d6aef051400154cad": "varying regional cost-benefit analysis and burden-sharing conflicts", + "5729506d6aef051400154cae": "regional burden sharing conflicts", + "5729506d6aef051400154caf": "UK government", + "5729517d6aef051400154cc8": "scientific papers", + "5729517d6aef051400154cc9": "any significant new evidence or events that change our understanding of climate science", + "5729517d6aef051400154cca": "IPCC", + "572951f16aef051400154cce": "five", + "572951f16aef051400154ccf": "Nature", + "572951f16aef051400154cd0": "tightening the selection of lead authors and contributors, to dumping it in favor of a small permanent body", + "572951f16aef051400154cd1": "employ a full-time staff and remove government oversight from its processes", + "572953013f37b3190047824d": "to conduct photosynthesis", + "572953013f37b3190047824e": "energy-storage molecules ATP and NADPH", + "572953013f37b3190047824f": "energy-storage molecules ATP", + "572953013f37b31900478250": "Calvin cycle", + "572953013f37b31900478251": "1", + "5729544c3f37b31900478257": "pinch in two", + "5729544c3f37b31900478258": "environmental factors like light color and intensity", + "5729544c3f37b31900478259": "contain their own DNA", + "5729544c3f37b3190047825a": "a photosynthetic cyanobacterium", + "5729544c3f37b3190047825b": "they circulate and are moved around within plant cells", + "572956c86aef051400154d1a": "plants and algae", + "572956c86aef051400154d1b": "Russian", + "572956c86aef051400154d1c": "biologist", + "572956c86aef051400154d1d": "1905", + "572956c86aef051400154d1e": "Andreas Schimper", + "572957361d046914007792cf": "Cyanobacteria", + "572957361d046914007792d0": "phylum", + "572957361d046914007792d2": "they have two cell membranes", + "572957361d046914007792d3": "peptidoglycan", + "572957361d046914007792d1": "blue-green algae", + "572957ad1d046914007792d9": "eukaryotic cell", + "572957ad1d046914007792da": "Somewhere around a billion years ago", + "572957ad1d046914007792db": "lipid-bilayer membranes", + "572957ad1d046914007792dc": "phagosomal membrane", + "572957ad1d046914007792dd": "many of its genes were lost or transferred to the nucleus of the host", + "5729582b1d046914007792e3": "the same thing as chloroplast", + "5729582b1d046914007792e4": "three", + "5729582b1d046914007792e5": "red algal chloroplast lineage", + "5729582b1d046914007792e6": "green chloroplast lineage", + "5729582b1d046914007792e7": "green chloroplast lineage", + "572958cc6aef051400154d2a": "glaucophyte", + "572958cc6aef051400154d2b": "glaucophyte", + "572958cc6aef051400154d2c": "glaucophyte chloroplasts", + "572958cc6aef051400154d2d": "carboxysome", + "572958cc6aef051400154d2e": "icosahedral", + "57295a116aef051400154d44": "chlorophyll a and phycobilins", + "57295a116aef051400154d45": "phycobilisomes", + "57295a116aef051400154d46": "phycobilin phycoerytherin", + "57295a116aef051400154d47": "catch more sunlight", + "57295a116aef051400154d48": "starch", + "57295b5b1d04691400779315": "lost their phycobilisomes", + "57295b5b1d04691400779316": "accessory pigments that override the chlorophylls' green colors", + "57295b5b1d04691400779317": "lost the peptidoglycan wall between their double membrane, and have replaced it with an intermembrane space", + "57295b5b1d04691400779318": "use in chloroplast division", + "57295b5b1d04691400779319": "chlorophyll b", + "572961f61d04691400779359": "double membrane", + "572961f61d0469140077935a": "additional membranes outside of the original two", + "572961f61d0469140077935b": "when a nonphotosynthetic eukaryote engulfed a chloroplast-containing alga", + "572961f61d0469140077935c": "outside of the original two", + "572961f61d0469140077935d": "its chloroplast", + "572962953f37b319004782f5": "pyrenoid and thylakoids stacked in groups of three", + "572962953f37b319004782f6": "common flagellated", + "572962953f37b319004782f7": "stacked in groups of three", + "572962953f37b319004782f8": "Starch", + "572962953f37b319004782f9": "the membrane of the primary endosymbiont", + "572963221d04691400779385": "cryptomonads", + "572963221d04691400779386": "red-algal derived", + "572963221d04691400779387": "a nucleomorph", + "572963221d04691400779388": "granules found in the periplastid space", + "572963221d04691400779389": "stacks of two", + "572963876aef051400154dd2": "helicosproidia", + "572963876aef051400154dd3": "chromalveolates", + "572963876aef051400154dd4": "the malaria parasite", + "572963876aef051400154dd5": "red algal derived chloroplast", + "572963876aef051400154dd6": "amylopectin starch granules", + "5729645b3f37b31900478321": "fatty acids, isopentenyl pyrophosphate, iron-sulfur clusters, and carry out part of the heme pathway", + "5729645b3f37b31900478322": "apicomplexan-related", + "5729645b3f37b31900478323": "isopentenyl pyrophosphate synthesis", + "5729645b3f37b31900478324": "all photosynthetic function", + "5729645b3f37b31900478325": "four", + "572965566aef051400154e00": "critical photosynthesis-related genes", + "572965566aef051400154e01": "chloroplasts", + "572965566aef051400154e02": "triplet-stacked", + "572965566aef051400154e03": "red algal endosymbiont's original cell membrane", + "572965e73f37b3190047832b": "fucoxanthin dinophyte", + "572965e73f37b3190047832c": "fucoxanthin dinophyte", + "572965e73f37b3190047832d": "four", + "572965e73f37b3190047832e": "a six membraned chloroplast", + "572966626aef051400154e13": "cryptophyte", + "572966626aef051400154e14": "old ones", + "572966626aef051400154e12": "two-membraned chloroplast", + "572966626aef051400154e15": "a two-membraned chloroplast", + "572966ebaf94a219006aa391": "heterokontophyte", + "572966ebaf94a219006aa392": "diatom", + "572966ebaf94a219006aa393": "up to five", + "572966ebaf94a219006aa394": "entire diatom endosymbiont", + "572966ebaf94a219006aa395": "granules in the dinophyte host's cytoplasm", + "572967e31d046914007793b1": "dinophyte nucleus", + "572967e31d046914007793b2": "Lepidodinium", + "572967e31d046914007793b3": "peridinin chloroplast", + "572967e31d046914007793b4": "green algal derived chloroplast", + "572967e31d046914007793b5": "green algal derived chloroplast", + "5729686d1d046914007793c1": "that first set of endosymbiotic events", + "5729686d1d046914007793c2": "an exception that acquired a photosynthetic cyanobacterial endosymbiont", + "5729686d1d046914007793c3": "about a million", + "5729686d1d046914007793c4": "850", + "5729686d1d046914007793c5": "three million", + "572968cf1d046914007793cb": "ctDNA, or cpDNA", + "572968cf1d046914007793cc": "plastome", + "572968cf1d046914007793cd": "1962", + "572968cf1d046914007793ce": "1986", + "572968cf1d046914007793cf": "two Japanese research teams", + "57296977af94a219006aa3bd": "inverted repeats", + "57296977af94a219006aa3be": "direct repeats", + "57296977af94a219006aa3bf": "stabilize the rest of the chloroplast genome", + "572969f51d046914007793dd": "electron microscopy", + "572969f51d046914007793de": "two", + "572969f51d046914007793e0": "theta intermediary form", + "572969f51d046914007793df": "double displacement loop", + "572969f51d046914007793e1": "rolling circle mechanism", + "57296a65af94a219006aa3c3": "A \u2192 G deamination gradients", + "57296a65af94a219006aa3c4": "single stranded", + "57296a65af94a219006aa3c5": "linear and replicates through homologous recombination", + "57296a65af94a219006aa3c6": "through homologous recombination", + "57296a65af94a219006aa3c7": "circular chromosomes", + "57296ab93f37b31900478369": "bacteriophage T4", + "57296ab93f37b3190047836a": "linear", + "57296ab93f37b3190047836b": "linear", + "57296ab93f37b3190047836c": "via a D loop mechanism", + "57296b151d046914007793f1": "Endosymbiotic gene transfer", + "57296b151d046914007793f2": "lost chloroplast's existence", + "57296b151d046914007793f3": "heterokontophyte", + "57296b151d046914007793f4": "heterokontophyte", + "57296bf96aef051400154e52": "nonfunctional pseudogenes", + "57296bf96aef051400154e53": "around half", + "57296bf96aef051400154e54": "participating in cell division, protein routing, and even disease resistance", + "57296bf96aef051400154e55": "the cell membrane", + "57296c5c3f37b3190047837f": "a ribosome in the cytosol", + "57296c5c3f37b31900478380": "on a ribosome in the cytosol", + "57296c5c3f37b31900478381": "helps many proteins bind the polypeptide, keeping it from folding prematurely", + "57296c5c3f37b31900478382": "keeping it from folding prematurely", + "57296cb21d04691400779403": "lens-shaped", + "57296cb21d04691400779404": "5\u20138 \u03bcm in diameter and 1\u20133 \u03bcm thick", + "57296cb21d04691400779405": "1\u20133 \u03bcm", + "57296cb21d04691400779406": "a net", + "57296cb21d04691400779407": "cup", + "57296d1b1d0469140077940d": "The fact that chloroplasts are surrounded by a double membrane", + "57296d1b1d0469140077940e": "not true", + "57296d1b1d0469140077940f": "homologous", + "57296d8d1d0469140077941d": "mitochondrial double membrane", + "57296d8d1d0469140077941e": "run proton pumps and carry out oxidative phosphorylation across to generate ATP energy", + "57296d8d1d0469140077941f": "to generate ATP energy", + "57296d8d1d04691400779420": "internal thylakoid system", + "57296d8d1d04691400779421": "internal thylakoid system", + "57296de03f37b3190047839b": "Stromules", + "57296de03f37b3190047839c": "stroma-containing tubule", + "57296de03f37b3190047839d": "to increase the chloroplast's surface area for cross-membrane transport", + "57296de03f37b3190047839e": "1962", + "57296e43af94a219006aa3e5": "chloroplasts of C4 plants", + "57296e43af94a219006aa3e6": "chloroplasts of C4 plants", + "57296e43af94a219006aa3e7": "The chloroplast peripheral reticulum", + "57296e43af94a219006aa3e8": "increase the chloroplast's surface area for cross-membrane transport between its stroma and the cell cytoplasm", + "57296e43af94a219006aa3e9": "thylakoids and intermembrane space", + "57296eb01d04691400779435": "to synthesize a small fraction of their proteins", + "57296eb01d04691400779436": "two-thirds", + "57296eb01d04691400779437": "two-thirds", + "57296eb01d04691400779438": "shine-dalgarno sequence recognition", + "57296eb01d04691400779439": "translation initiation", + "57296eee6aef051400154e8e": "plastoglobulus", + "57296eee6aef051400154e8f": "spherical", + "57296eee6aef051400154e90": "lipids and proteins", + "57296eee6aef051400154e91": "45\u201360 nanometers across", + "57296eee6aef051400154e92": "lipid monolayer", + "57296f3caf94a219006aa3fb": "a thylakoid", + "57296f3caf94a219006aa3fc": "thylakoid network", + "57296f3caf94a219006aa3fd": "attached directly to their parent thylakoid", + "57296f3caf94a219006aa3fe": "old or stressed chloroplasts", + "57296f85af94a219006aa403": "higher plants", + "57296f85af94a219006aa404": "spherical", + "57296f85af94a219006aa405": "spherical and highly refractive bodies", + "57296f85af94a219006aa406": "starch", + "57296f85af94a219006aa407": "de novo", + "57296fd71d0469140077943f": "helical thylakoid model", + "57296fd71d04691400779440": "circular", + "57296fd71d04691400779441": "two to a hundred", + "57296fd71d04691400779442": "two to a hundred", + "57296fd71d04691400779443": "helicoid stromal thylakoids", + "5729703d3f37b319004783bb": "light energy", + "5729703d3f37b319004783bc": "light energy", + "5729703d3f37b319004783bd": "energize electrons", + "5729703d3f37b319004783be": "pump hydrogen ions into the thylakoid space", + "5729703d3f37b319004783bf": "a dam turbine", + "572970916aef051400154eba": "two", + "572970916aef051400154ebb": "pancake-shaped circular disks about 300\u2013600 nanometers in diameter", + "572970916aef051400154ebc": "in contact with the stroma", + "572970916aef051400154ebe": "pancake-shaped", + "572970916aef051400154ebd": "300\u2013600 nanometers in diameter", + "57297103af94a219006aa423": "about thirty", + "57297103af94a219006aa424": "help transfer and dissipate excess energy", + "57297103af94a219006aa425": "help transfer and dissipate excess energy", + "57297103af94a219006aa426": "bright red-orange carotenoid", + "57297103af94a219006aa427": "orange-red zeaxanthin", + "5729714daf94a219006aa42d": "a third group of pigments", + "5729714daf94a219006aa42e": "red algae red", + "5729714daf94a219006aa42f": "red algae red", + "5729714daf94a219006aa430": "relatively large protein complexes", + "5729714daf94a219006aa431": "40 nanometers", + "572971af6aef051400154ede": "rubisco", + "572971af6aef051400154edf": "it has trouble distinguishing between carbon dioxide and oxygen", + "572971af6aef051400154ee0": "trouble distinguishing between carbon dioxide and oxygen", + "572971af6aef051400154ee1": "Calvin cycle", + "572971af6aef051400154ee2": "ATP energy", + "5729723c6aef051400154ee8": "light reactions", + "5729723c6aef051400154ee9": "rubisco", + "5729723c6aef051400154eea": "normal grana and thylakoids", + "5729723c6aef051400154eeb": "a four-carbon compound", + "5729723c6aef051400154eec": "each stage of photosynthesis", + "5729729a1d0469140077948b": "green", + "5729729a1d0469140077948c": "chloroplasts", + "5729729a1d0469140077948d": "parenchyma cells", + "5729729a1d0469140077948e": "collenchyma tissue", + "5729729a1d0469140077948f": "A plant cell which contains chloroplasts", + "572972f46aef051400154ef2": "in the stems", + "572972f46aef051400154ef3": "the leaves", + "572972f46aef051400154ef6": "8\u201315", + "572972f46aef051400154ef4": "half a million", + "572972f46aef051400154ef5": "mesophyll", + "5729735c3f37b319004783fb": "low-light conditions", + "5729735c3f37b319004783fc": "along the plant cell's cell wall or turning sideways", + "5729735c3f37b319004783fd": "photooxidative damage", + "5729735c3f37b319004783fe": "ability to distribute chloroplasts so that they can take shelter behind each other or spread out", + "5729735c3f37b319004783ff": "Mitochondria", + "572973ccaf94a219006aa449": "two", + "572973ccaf94a219006aa44a": "infected cells seal themselves off and undergo programmed cell death", + "572973ccaf94a219006aa44b": "infected cells release signals warning the rest of the plant of a pathogen's presence", + "572973ccaf94a219006aa44c": "purposely damaging their photosynthetic system", + "572973ccaf94a219006aa44d": "reactive oxygen species", + "57297427af94a219006aa453": "salicylic acid, jasmonic acid, nitric oxide and reactive oxygen species", + "57297427af94a219006aa454": "After detecting stress in a cell", + "57297427af94a219006aa455": "pass on their signal to an unknown second messenger molecule", + "57297427af94a219006aa456": "signals from the chloroplast that regulate gene expression in the nucleus", + "572974923f37b3190047840b": "photosynthesis", + "572974923f37b3190047840c": "photosynthesis", + "572974923f37b3190047840d": "food in the form of sugars", + "572974923f37b3190047840e": "Water (H2O) and carbon dioxide (CO2)", + "572974923f37b3190047840f": "Water (H2O) and carbon dioxide (CO2)", + "572975073f37b31900478415": "use the potential energy stored in an H+, or hydrogen ion gradient to generate ATP energy", + "572975073f37b31900478416": "thylakoid space", + "572975073f37b31900478417": "up to a thousand times as many", + "572975073f37b31900478418": "adenosine triphosphate", + "572975073f37b31900478419": "adenosine triphosphate", + "572975511d046914007794a7": "NADP+", + "572975511d046914007794a8": "cyclic photophosphorylation", + "572975511d046914007794a9": "C4 plants", + "572975511d046914007794aa": "more ATP than NADPH", + "572975a3af94a219006aa465": "The Calvin cycle", + "572975a3af94a219006aa466": "unstable six-carbon molecules", + "572975a3af94a219006aa467": "3-phosphoglyceric acid, or 3-PGA", + "572975a3af94a219006aa468": "one out of every six", + "572976183f37b31900478431": "glucose monomers", + "572976183f37b31900478432": "Under conditions such as high atmospheric CO2 concentrations", + "572976183f37b31900478433": "distorting the grana and thylakoids", + "572976183f37b31900478434": "Waterlogged", + "572976183f37b31900478435": "photosynthesis-depressing factor", + "572976791d046914007794af": "add O2 instead of CO2 to RuBP", + "572976791d046914007794b0": "when the oxygen concentration is too high", + "572976791d046914007794b1": "it consumes ATP and oxygen, releases CO2, and produces no sugar", + "572976791d046914007794b2": "up to half", + "572976791d046914007794b3": "a distinct chloroplast dimorphism", + "572976cfaf94a219006aa493": "in their stroma", + "572976cfaf94a219006aa494": "cysteine and methionine", + "572976cfaf94a219006aa495": "trouble crossing membranes to get to where it is needed", + "572976cfaf94a219006aa496": "whether the organelle carries out the last leg of the pathway or if it happens in the cytosol", + "57297725af94a219006aa49b": "Chloroplasts", + "57297725af94a219006aa49c": "undifferentiated proplastids", + "57297725af94a219006aa49d": "in an adult plant's apical meristems", + "57297725af94a219006aa49e": "formation of starch-storing amyloplasts", + "5729779b6aef051400154f62": "proplastids may develop into an etioplast stage before becoming chloroplasts", + "5729779b6aef051400154f63": "a plastid that lacks chlorophyll", + "5729779b6aef051400154f64": "invaginations", + "5729779b6aef051400154f65": "yellow chlorophyll precursor stocked", + "5729779b6aef051400154f66": "Gymnosperms", + "572977fbaf94a219006aa4ad": "proplastids", + "572977fbaf94a219006aa4ae": "pigment-filled plastids", + "572977fbaf94a219006aa4af": "chloroplasts", + "572977fbaf94a219006aa4b0": "chromoplasts", + "572977fbaf94a219006aa4b1": "chloroplasts and other plastids", + "5729784b1d046914007794c9": "filaments", + "5729784b1d046914007794ca": "assemble into filaments", + "5729784b1d046914007794cb": "Z-ring", + "5729784b1d046914007794cc": "within the chloroplast's stroma", + "5729784b1d046914007794cd": "the chloroplast is cleaved more or less evenly", + "5729789b6aef051400154f6c": "plastid-dividing rings", + "5729789b6aef051400154f6d": "two", + "5729789b6aef051400154f6e": "5 nanometers across", + "5729789b6aef051400154f6f": "5 nanometers across", + "5729789b6aef051400154f70": "chloroplasts have a third plastid-dividing ring located in the chloroplast's intermembrane space", + "572978e66aef051400154f76": "Light", + "572978e66aef051400154f78": "white", + "572978e66aef051400154f79": "dumbbell-shaped chloroplasts", + "572978e66aef051400154f77": "white", + "57297991af94a219006aa4b7": "developers of genetically modified crops. Since, in most flowering plants, chloroplasts are not inherited from the male parent", + "57297991af94a219006aa4b8": "environmental risks", + "57297991af94a219006aa4b9": "3 in 1,000,000", + "57297991af94a219006aa4ba": "genetically modified plants that are biologically contained", + "57296d571d04691400779413": "positive divisors other than 1", + "57296d571d04691400779414": "a composite number", + "57296d571d04691400779415": "The fundamental theorem of arithmetic", + "57296d571d04691400779416": "primes that is unique up to ordering", + "57296d571d04691400779417": "one can include arbitrarily many instances of 1 in any factorization", + "57296f293f37b319004783a3": "primality", + "57296f293f37b319004783a4": "trial division", + "57296f293f37b319004783a5": "trial division. It consists of testing whether n is a multiple of any integer between 2 and . Algorithms much more efficient than trial division", + "57296f293f37b319004783a6": "trial division", + "57296f293f37b319004783a7": "22,338,618", + "572970c11d04691400779463": "infinitely many", + "572970c11d04691400779464": "Euclid", + "572970c11d04691400779465": "statistical", + "572970c11d04691400779466": "prime number theorem", + "572970c11d04691400779467": "end of the 19th century", + "5729727baf94a219006aa437": "Goldbach's conjecture", + "5729727baf94a219006aa438": "twin prime conjecture", + "5729727baf94a219006aa439": "algebraic", + "5729727baf94a219006aa43a": "public-key cryptography", + "5729727baf94a219006aa43b": "the twin prime conjecture", + "572973f76aef051400154f0a": "2", + "572973f76aef051400154f0b": "1, 2, and n", + "572973f76aef051400154f0c": "odd prime", + "572973f76aef051400154f0d": "9", + "572973f76aef051400154f0e": "numbers ending in 0 or 5 are multiples of 5", + "57297547af94a219006aa45b": "1", + "57297547af94a219006aa45c": "Christian Goldbach", + "57297547af94a219006aa45d": "Christian Goldbach", + "57297547af94a219006aa45e": "10,006,721", + "57297547af94a219006aa45f": "a prime", + "57297781af94a219006aa4a3": "Euclid's fundamental theorem of arithmetic", + "57297781af94a219006aa4a4": "1 were considered a prime", + "57297781af94a219006aa4a6": "sum of divisors function", + "57297781af94a219006aa4a5": "sum of divisors function", + "57297781af94a219006aa4a7": "eliminate all multiples of 1", + "572978f91d046914007794d3": "Rhind papyrus", + "572978f91d046914007794d4": "Ancient Greeks", + "572978f91d046914007794d5": "Euclid's Elements", + "572978f91d046914007794d6": "Euclid", + "572978f91d046914007794d7": "a simple method to compute primes", + "57297a276aef051400154f88": "1640", + "57297a276aef051400154f89": "Euler", + "57297a276aef051400154f8a": "22n + 1", + "57297a276aef051400154f8c": "2p \u2212 1", + "57297a276aef051400154f8b": "n = 4 (or 216 + 1)", + "57297bc9af94a219006aa4c7": "trial division", + "57297bc9af94a219006aa4c8": "a complete list of primes up to is known", + "57297bc9af94a219006aa4c9": "1 and less than or equal to the square root of n", + "57297bc9af94a219006aa4cb": "three", + "57297bc9af94a219006aa4ca": "square root of n", + "57297d421d046914007794e5": "two", + "57297d421d046914007794e6": "probabilistic (or \"Monte Carlo\") and deterministic algorithms", + "57297d421d046914007794e7": "probabilistic (or \"Monte Carlo\") and deterministic algorithms", + "57297d421d046914007794e8": "deterministic", + "57297d421d046914007794e9": "1/(1-p)n", + "57297ed93f37b3190047845f": "Fermat primality test", + "57297ed93f37b31900478460": "the fact (Fermat's little theorem) that np\u2261n (mod p) for any n if p is a prime number", + "57297ed93f37b31900478461": "composite numbers", + "57297ed93f37b31900478462": "Baillie-PSW, Miller-Rabin, and Solovay-Strassen tests", + "57297ed93f37b31900478463": "Baillie-PSW, Miller-Rabin, and Solovay-Strassen tests", + "572980f9af94a219006aa4d1": "2p + 1 with p prime", + "572980f9af94a219006aa4d2": "2p \u2212 1", + "572980f9af94a219006aa4d3": "Lucas\u2013Lehmer test", + "572980f9af94a219006aa4d4": "Sophie Germain primes", + "572980f9af94a219006aa4d5": "Sophie Germain primes", + "572982e66aef051400154f92": "distributed computing", + "572982e66aef051400154f93": "2009", + "572982e66aef051400154f94": "US$100,000", + "572982e66aef051400154f95": "Electronic Frontier Foundation", + "572982e76aef051400154f96": "256kn + 1, 256k(n + 1) \u2212 1", + "572985011d04691400779501": "floor function", + "572985011d04691400779502": "Chebyshev", + "572985011d04691400779503": "n > 3", + "572985011d04691400779504": "there always exists at least one prime number p with n < p < 2n \u2212 2", + "572985011d04691400779505": "Wilson's theorem", + "572987e46aef051400154fa2": "Dirichlet's theorem on arithmetic progressions", + "572987e46aef051400154fa3": "Dirichlet's theorem", + "572987e46aef051400154fa4": "1/6", + "572987e46aef051400154fa5": "at most one prime number", + "572987e46aef051400154fa6": "infinitely many prime numbers", + "572989846aef051400154fc0": "The zeta function", + "572989846aef051400154fc1": "\u03b6(1", + "572989846aef051400154fc2": "exceeds any given number", + "572989846aef051400154fc3": "exceeds any given number", + "572989846aef051400154fc4": "identity", + "57298ef11d0469140077952d": "1859", + "57298ef11d0469140077952e": "s = \u22122, \u22124", + "57298ef11d0469140077952f": "random noise", + "57298ef11d04691400779530": "asymptotic", + "57298ef11d04691400779531": "asymptotic", + "57299021af94a219006aa50c": "Goldbach's conjecture", + "57299021af94a219006aa50b": "1912", + "57299021af94a219006aa50d": "all numbers up to n = 2 \u00b7 1017", + "57299021af94a219006aa50e": "Vinogradov's theorem", + "57299021af94a219006aa50f": "Chen's theorem", + "572991943f37b319004784a1": "Polignac's conjecture", + "572991943f37b319004784a2": "pairs of primes with difference 2", + "572991943f37b319004784a3": "Polignac's conjecture", + "572991943f37b319004784a4": "n2 + 1", + "572991943f37b319004784a5": "H. Brocard's conjecture", + "57299326af94a219006aa515": "number theory", + "57299326af94a219006aa516": "G. H. Hardy", + "57299326af94a219006aa517": "1970s", + "57299326af94a219006aa518": "hash tables and pseudorandom number generators", + "57299326af94a219006aa519": "pseudorandom", + "572995d46aef051400154fe8": "recurring", + "572995d46aef051400154fe9": "recurring decimal", + "572995d46aef051400154fea": "+ 1", + "572995d46aef051400154feb": "n \u2212 1", + "572995d46aef051400154fec": "The fraction 1/p expressed likewise in base q (rather than base 10) has similar effect", + "572996c73f37b319004784b3": "RSA and the Diffie\u2013Hellman key exchange", + "572996c73f37b319004784b4": "RSA and the Diffie\u2013Hellman key exchange", + "572996c73f37b319004784b5": "512", + "572996c73f37b319004784b6": "modular", + "572996c73f37b319004784b7": "1024", + "572998673f37b319004784d5": "Magicicada", + "572998673f37b319004784d6": "as grubs underground", + "572998673f37b319004784d7": "17 years", + "572998673f37b319004784d8": "the prime number intervals between emergences make it very difficult for predators to evolve", + "572998673f37b319004784d9": "2% higher", + "57299a6f6aef051400155016": "minimality or indecomposability", + "57299a6f6aef051400155017": "smallest subfield", + "57299a6f6aef051400155019": "as a connected sum of prime knots", + "57299a6f6aef05140015501a": "any object can be, essentially uniquely, decomposed into its prime components", + "57299a6f6aef051400155018": "it cannot be written as the knot sum of two nontrivial knots", + "57299c2c6aef051400155020": "commutative ring R", + "57299c2c6aef051400155021": "Prime numbers", + "57299c2c6aef051400155022": "Prime numbers", + "57299c2c6aef051400155023": "given x and y in R such that p divides the product xy", + "57299c2c6aef051400155024": "if it is not a unit", + "57299d1c1d04691400779581": "The fundamental theorem of arithmetic", + "57299d1c1d04691400779582": "Gaussian integers Z[i]", + "57299d1c1d04691400779583": "a + bi", + "57299d1c1d04691400779584": "arbitrary integers", + "57299d1c1d04691400779585": "Gaussian primes, whereas rational primes of the form 4k + 1", + "57299ec43f37b3190047850d": "ring theory", + "57299ec43f37b3190047850e": "Prime ideals", + "57299ec43f37b3190047850f": "algebraic", + "57299ec43f37b31900478510": "The fundamental theorem of arithmetic", + "57299ec43f37b31900478511": "Noetherian", + "5729a03f1d04691400779593": "Prime ideals", + "5729a03f1d04691400779594": "ramification in geometry", + "5729a03f1d04691400779595": "the ring of integers of quadratic number fields", + "5729a03f1d04691400779596": "solvability of quadratic equations", + "5729a26d6aef05140015505a": "gets smaller", + "5729a26d6aef05140015505b": "completed (or local) fields", + "5729a26d6aef05140015505c": "p-adic norm", + "5729a26d6aef05140015505d": "local-global principle", + "5729a3716aef05140015506a": "Olivier Messiaen", + "5729a3716aef05140015506b": "La Nativit\u00e9 du Seigneur (1935) and Quatre \u00e9tudes de rythme", + "5729a3716aef05140015506c": "La Nativit\u00e9 du Seigneur (1935) and Quatre \u00e9tudes de rythme", + "5729a3716aef05140015506d": "third", + "5729a3716aef05140015506e": "the movements of nature, movements of free and unequal durations", + "572f5533a23a5019007fc55b": "Swiss canton of Graub\u00fcnden in the southeastern Swiss Alps", + "572f5533a23a5019007fc55c": "the Rhineland and eventually empties into the North Sea in the Netherlands", + "572f5533a23a5019007fc55d": "Cologne", + "572f5533a23a5019007fc55e": "the Danube", + "572f5533a23a5019007fc55f": "1,230 km (760 mi)", + "572fe1d404bcaa1900d76e37": "Swiss canton of Graub\u00fcnden in the southeastern Swiss Alps", + "572fe1d404bcaa1900d76e3a": "Netherlands", + "572fe1d404bcaa1900d76e3b": "1,230 km (760 mi)", + "572f55e8a23a5019007fc56b": "Gaulish name R\u0113nos", + "572f55e8a23a5019007fc56c": "Rhin", + "572f55e8a23a5019007fc56d": "*R\u012bnaz", + "572f55e8a23a5019007fc56e": "1st century BC", + "572fe288a23a5019007fcad7": "Gaulish name R\u0113nos", + "572fe288a23a5019007fcad8": "Rhin", + "572fe288a23a5019007fcada": "Rijn", + "572fe288a23a5019007fcad9": "*R\u012bnaz", + "572fe288a23a5019007fcadb": "Rhijn", + "572f567cb2c2fd140056803f": "Rhine-kilometers\" (Rheinkilometer", + "572f567cb2c2fd1400568040": "1939", + "572f567cb2c2fd1400568041": "Old Rhine Bridge at Constance", + "572f567cb2c2fd1400568042": "Hoek van Holland (1036.20 km). The river length is significantly shortened from the river's natural course", + "572f567cb2c2fd1400568043": "canalisation projects", + "572fe393947a6a140053cdba": "Rhine-kilometers", + "572fe393947a6a140053cdbb": "1939", + "572fe393947a6a140053cdbc": "Old Rhine Bridge at Constance", + "572fe393947a6a140053cdbe": "number of canalisation projects completed in the 19th and 20th century", + "572fe393947a6a140053cdbd": "Hoek van Holland", + "572f5703a23a5019007fc573": "north", + "572f5703a23a5019007fc574": "86 km", + "572f5703a23a5019007fc575": "Rhine Valley", + "572f5703a23a5019007fc576": "Sargans", + "572f5703a23a5019007fc577": "Liechtenstein", + "572fe41e04bcaa1900d76e4b": "near Chur", + "572fe41e04bcaa1900d76e4c": "86 km long", + "572fe41e04bcaa1900d76e4d": "599 m to 396 m", + "572fe41e04bcaa1900d76e4e": "Rhine Valley", + "572fe41e04bcaa1900d76e4f": "Liechtenstein", + "572f57c704bcaa1900d7686d": "Lake Constance", + "572f57c704bcaa1900d7686e": "Alter Rhein", + "572f57c704bcaa1900d7686f": "a modern canalized section", + "572f57c704bcaa1900d76870": "Isel", + "572f57c704bcaa1900d76871": "Donkey", + "572fe4a304bcaa1900d76e55": "Lake Constance", + "572fe4a304bcaa1900d76e56": "a modern canalized section", + "572fe4a304bcaa1900d76e57": "Alter Rhein", + "572fe4a304bcaa1900d76e58": "small islands", + "572fe4a304bcaa1900d76e59": "Alemannic dialect, the singular is pronounced \"Isel", + "572f5875947a6a140053c89a": "near Diepoldsau", + "572f5875947a6a140053c89b": "to counteract the constant flooding and strong sedimentation in the western Rhine Delta", + "572f5875947a6a140053c89c": "strong sedimentation", + "572f5875947a6a140053c89d": "parallel to the canalized Rhine into the lake", + "572f5875947a6a140053c89e": "will silt up the lake", + "572fe53104bcaa1900d76e69": "Fu\u00dfach", + "572fe53104bcaa1900d76e6b": "to counteract the constant flooding and strong sedimentation in the western Rhine Delta", + "572fe53104bcaa1900d76e6a": "near Diepoldsau", + "572fe53104bcaa1900d76e6c": "Dornbirner Ach", + "572fe53104bcaa1900d76e6d": "continuous input of sediment", + "572f58d9a23a5019007fc57d": "three", + "572f58d9a23a5019007fc580": "lower lake", + "572f58d9a23a5019007fc57e": "Seerhein", + "572f58d9a23a5019007fc581": "Swiss-Austrian border", + "572f58d9a23a5019007fc57f": "upper lake", + "572fe60fb2c2fd140056858b": "three", + "572fe60fb2c2fd140056858c": "Austria", + "572fe60fb2c2fd140056858d": "Alps", + "572fe60fb2c2fd140056858e": "near the Alps", + "572fe60fb2c2fd140056858f": "Baden-W\u00fcrttemberg", + "572f59b4a23a5019007fc587": "greater density of cold water", + "572f59b4a23a5019007fc58a": "Lake \u00dcberlingen", + "572f59b4a23a5019007fc588": "Upper Lake", + "572f59b4a23a5019007fc58b": "entire length", + "572f59b4a23a5019007fc589": "Lindau", + "572fe92204bcaa1900d76e95": "Upper Lake", + "572fe92204bcaa1900d76e96": "Lindau", + "572fe92204bcaa1900d76e97": "Lake \u00dcberlingen", + "572fe92204bcaa1900d76e98": "Rhine Gutter", + "572fe92204bcaa1900d76e99": "water level", + "572f609ca23a5019007fc5af": "westward", + "572f609ca23a5019007fc5b0": "river Aare", + "572f609ca23a5019007fc5b1": "more than doubles the Rhine's water discharge, to an average of nearly 1,000 m3/s", + "572f609ca23a5019007fc5b2": "Finsteraarhorn", + "572f609ca23a5019007fc5b3": "Basel", + "572fe9b3947a6a140053cde0": "westward", + "572fe9b3947a6a140053cde1": "river Aare", + "572fe9b3947a6a140053cde2": "more than doubles the Rhine's water discharge, to an average of nearly 1,000 m3/s", + "572fe9b3947a6a140053cde3": "Finsteraarhorn", + "572fe9b3947a6a140053cde4": "German-Swiss", + "572f60f4947a6a140053c8ea": "Basel", + "572f60f4947a6a140053c8eb": "Rhine knee", + "572f60f4947a6a140053c8ec": "the Central Bridge", + "572f60f4947a6a140053c8ed": "300 km", + "572f60f4947a6a140053c8ee": "40 km", + "572fec30947a6a140053cdf2": "Basel", + "572fec30947a6a140053cdf3": "Rhine knee", + "572fec30947a6a140053cdf4": "North", + "572fec30947a6a140053cdf5": "High Rhine", + "572fec30947a6a140053cdf6": "the Central Bridge", + "572f64ccb2c2fd14005680b7": "19th", + "572f64ccb2c2fd14005680b8": "increased", + "572f64ccb2c2fd14005680b9": "fell significantly", + "572f64ccb2c2fd14005680ba": "Grand Canal d'Alsace", + "572f64ccb2c2fd14005680bb": "large compensation pools", + "572feddda23a5019007fcb5b": "Upper Rhine region", + "572feddda23a5019007fcb5c": "19th Century", + "572feddda23a5019007fcb5d": "increased and the ground water level fell significantly", + "572feddda23a5019007fcb5e": "fell significantly", + "572feddda23a5019007fcb5f": "the Grand Canal d'Alsace was dug", + "572f65e9b2c2fd14005680cc": "Moselle", + "572f65e9b2c2fd14005680cd": "more than 300 m3/s", + "572f65e9b2c2fd14005680cb": "The Rhine", + "572f65e9b2c2fd14005680ce": "Moselle", + "572f65e9b2c2fd14005680cf": "400 m (1,300 ft)", + "572ff07304bcaa1900d76ef5": "Germany", + "572ff07304bcaa1900d76ef6": "Germany", + "572ff07304bcaa1900d76ef7": "the Neckar, the Main and, later, the Moselle", + "572ff07304bcaa1900d76ef8": "France", + "572ff07304bcaa1900d76ef9": "2,290 m3/s", + "572f6a0ba23a5019007fc5eb": "the Middle Rhine", + "572f6a0ba23a5019007fc5ec": "Rhine Gorge", + "572f6a0ba23a5019007fc5ed": "by erosion", + "572f6a0ba23a5019007fc5ee": "the Romantic Rhine", + "572ff12e04bcaa1900d76eff": "the Middle Rhine", + "572ff12e04bcaa1900d76f00": "the Rhine Gorge", + "572ff12e04bcaa1900d76f02": "many castles and vineyards", + "572ff12e04bcaa1900d76f03": "the Romantic Rhine", + "572f6c85947a6a140053c940": "industry", + "572f6c85947a6a140053c942": "Duisburg", + "572f6c85947a6a140053c943": "The Ruhr", + "572f6c85947a6a140053c944": "drinking water", + "572f6c85947a6a140053c941": "Lower Rhine", + "572ff293947a6a140053ce52": "a major source of water pollution", + "572ff293947a6a140053ce53": "Lower Rhine", + "572ff293947a6a140053ce54": "Switzerland", + "572ff293947a6a140053ce55": "Duisburg", + "572ff293947a6a140053ce56": "The Ruhr", + "572f6ec7a23a5019007fc621": "tourism", + "572f6ec7a23a5019007fc622": "R\u00fcdesheim am Rhein", + "572f6ec7a23a5019007fc623": "Lorelei", + "572f6ec7a23a5019007fc624": "the Middle Rhine Valley", + "572ff35f947a6a140053ce66": "tourism", + "572ff35f947a6a140053ce67": "UNESCO World Heritage Site", + "572ff35f947a6a140053ce68": "R\u00fcdesheim am Rhein", + "572ff35f947a6a140053ce69": "Lorelei", + "572ff35f947a6a140053ce6a": "Near Sankt Goarshausen", + "572f7588947a6a140053c984": "Duisburg", + "572f7588947a6a140053c985": "Wesel-Datteln Canal", + "572f7588947a6a140053c986": "Lippe", + "572f7588947a6a140053c987": "Emmerich Rhine Bridge", + "572f7588947a6a140053c988": "400 m", + "572ff430a23a5019007fcba9": "The Lower Rhine", + "572ff430a23a5019007fcbaa": "Rhine-Ruhr region", + "572ff430a23a5019007fcbab": "Duisport", + "572ff430a23a5019007fcbac": "Emmerich Rhine Bridge", + "572ff430a23a5019007fcbad": "400 m", + "572f76d1b2c2fd1400568154": "the Meuse", + "572f76d1b2c2fd1400568153": "Rijn", + "572f76d1b2c2fd1400568155": "Two thirds", + "572ff4ca04bcaa1900d76f24": "farther west", + "572ff4ca04bcaa1900d76f25": "farther west, through the Waal", + "572ff4ca04bcaa1900d76f26": "the Meuse", + "572ff4ca04bcaa1900d76f27": "Oude Maas", + "572f7b33947a6a140053c9a2": "Pannerdens Kanaal", + "572f7b33947a6a140053c9a3": "Nederrijn", + "572f7b33947a6a140053c9a4": "the Lek", + "572f7b33947a6a140053c9a5": "Wijk bij Duurstede", + "572ff56304bcaa1900d76f2d": "Pannerdens Kanaal and redistributes", + "572ff56304bcaa1900d76f2e": "Nederrijn", + "572ff56304bcaa1900d76f2f": "one ninth", + "572ff56304bcaa1900d76f30": "the Lek", + "572ff56304bcaa1900d76f31": "Wijk bij Duurstede", + "572ff5fcb2c2fd1400568657": "Rijn", + "572ff5fcb2c2fd1400568658": "draining the surrounding land and polders", + "572ff5fcb2c2fd1400568659": "Kromme Rijn", + "572ff5fcb2c2fd140056865a": "Kromme Rijn", + "572ff5fcb2c2fd140056865b": "sluice", + "572ff673b2c2fd1400568669": "Rhine-Meuse Delta", + "572ff673b2c2fd140056866a": "Millingen aan de Rijn", + "572ff673b2c2fd140056866b": "Rhine-Meuse Delta", + "572ff7ab04bcaa1900d76f51": "Waal and Pannerdens Kanaal", + "572ff7ab04bcaa1900d76f52": "three", + "572ff7ab04bcaa1900d76f53": "Waal", + "572ff7ab04bcaa1900d76f55": "Old Meuse", + "572ff7ab04bcaa1900d76f54": "the Rip", + "572ff83ab2c2fd1400568681": "St. Elizabeth's flood", + "572ff83ab2c2fd1400568682": "1421", + "572ff83ab2c2fd1400568683": "just south of today's line Merwede-Oude Maas to the North Sea", + "572ff83ab2c2fd1400568685": "1421 to 1904", + "572ff83ab2c2fd1400568684": "an archipelago-like estuary", + "572ff890a23a5019007fcbce": "drainage channels", + "572ff890a23a5019007fcbcf": "The construction of Delta Works", + "572ff890a23a5019007fcbcd": "dammed", + "572ff890a23a5019007fcbd0": "second half of the 20th Century", + "572ff935b2c2fd140056869b": "tidal delta", + "572ff935b2c2fd140056869c": "tidal currents", + "572ff935b2c2fd140056869d": "strong tidal currents could tear huge areas of land into the sea", + "572ff935b2c2fd140056869e": "Zaltbommel", + "572ffa79a23a5019007fcbe9": "Tethys sea", + "572ffa79a23a5019007fcbeb": "Jurassic Period", + "572ffa79a23a5019007fcbec": "Mediterranean geography", + "572ffa79a23a5019007fcbea": "Triassic", + "572ffa79a23a5019007fcbed": "Iberia", + "572ffb02b2c2fd14005686b7": "N\u2013S rift system", + "572ffb02b2c2fd14005686b8": "Upper Rhine Graben", + "572ffb02b2c2fd14005686b9": "the Miocene", + "572ffb02b2c2fd14005686ba": "Rhone and Danube", + "572ffc0f947a6a140053cef0": "stream capture", + "572ffc0f947a6a140053cef1": "Pliocene period", + "572ffc0f947a6a140053cef2": "down to the Vosges Mountains", + "572ffce5a23a5019007fcc15": "geological period of the Ice Ages", + "572ffce5a23a5019007fcc16": "six", + "572ffce5a23a5019007fcc17": "120 m (390 ft)", + "572ffce5a23a5019007fcc18": "northwest", + "572ffce5a23a5019007fcc19": "offshore of Brest, France", + "572ffd75b2c2fd14005686e5": "~74,000", + "572ffd75b2c2fd14005686e6": "Pleistocene", + "572ffd75b2c2fd14005686e7": "west", + "572ffd75b2c2fd14005686e8": "120 m (390 ft)", + "572ffd75b2c2fd14005686e9": "The English Channel, the Irish Channel and most of the North Sea were dry land", + "572fff45947a6a140053cf26": "a glacier", + "572fff45947a6a140053cf27": "A tundra", + "572fff45947a6a140053cf28": "ca. 22,000\u201314,000 yr BP", + "572fff45947a6a140053cf29": "ice-sheets", + "572fff45947a6a140053cf2a": "loess", + "572fffb404bcaa1900d76fef": "22,000 years ago", + "572fffb404bcaa1900d76ff0": "thaw", + "572fffb404bcaa1900d76ff1": "the Rhine", + "572fffb404bcaa1900d76ff2": "13,000 BP", + "572fffb404bcaa1900d76ff3": "9000 BP", + "573003dd947a6a140053cf42": "7500 yr ago", + "573003dd947a6a140053cf43": "Rates of sea-level rise", + "573003dd947a6a140053cf44": "last 7000 years", + "573003dd947a6a140053cf45": "ongoing tectonic subsidence", + "573003dd947a6a140053cf46": "about 1\u20133 cm (0.39\u20131.18 in) per century", + "5730042804bcaa1900d77011": "~11,700 years ago", + "5730042804bcaa1900d77014": "~8,000 years ago", + "5730042804bcaa1900d77012": "Late-Glacial valley", + "5730042804bcaa1900d77013": "Netherlands", + "57300580b2c2fd140056874d": "~3000 yr BP", + "57300580b2c2fd140056874f": "increasing land clearance", + "57300580b2c2fd140056874e": "sediment load", + "57300580b2c2fd1400568751": "11\u201313th century AD", + "57300580b2c2fd1400568750": "80", + "5730069004bcaa1900d7702d": "North Sea", + "5730069004bcaa1900d7702e": "the North Sea", + "5730069004bcaa1900d7702f": "to the north", + "5730069004bcaa1900d77030": "IJsselmeer", + "5730069004bcaa1900d77031": "three", + "57300761947a6a140053cf9a": "1st century BC", + "57300761947a6a140053cf9b": "Germania", + "57300761947a6a140053cf9c": "6th century BC", + "57300761947a6a140053cf9d": "Maurus Servius Honoratus", + "573007fab2c2fd140056876b": "AD 14", + "573007fab2c2fd140056876c": "upper Danube", + "573007fab2c2fd140056876d": "until the empire fell", + "573007fab2c2fd140056876f": "eastwards", + "573007fab2c2fd140056876e": "Frankfurt", + "57300888b2c2fd1400568775": "eight", + "57300888b2c2fd1400568777": "Pannonian troops", + "57300888b2c2fd1400568778": "oppidum Ubiorum", + "57300888b2c2fd1400568776": "whether a state or threat of war existed", + "57300888b2c2fd1400568779": "oppidum Ubiorum", + "57300911947a6a140053cfb6": "5th century", + "57300911947a6a140053cfb7": "kingdoms of Francia", + "57300911947a6a140053cfb8": "dragons rock", + "57300911947a6a140053cfb9": "Siegfried", + "57300911947a6a140053cfba": "Hagen", + "573009a004bcaa1900d7704f": "6th century", + "573009a004bcaa1900d77050": "10th century", + "573009a004bcaa1900d77051": "Lower Lorraine", + "573009a004bcaa1900d77052": "Archduke Sigismund of Austria", + "573009a004bcaa1900d77053": "1469", + "57300a25a23a5019007fcc97": "the Peace of Westphalia", + "57300a25a23a5019007fcc98": "Establishing \"natural borders", + "57300a25a23a5019007fcc99": "Napoleon", + "57300a25a23a5019007fcc9a": "1806", + "57300a25a23a5019007fcc9b": "1840", + "57300a9a04bcaa1900d77063": "end of World War I", + "57300a9a04bcaa1900d77064": "1930", + "57300a9a04bcaa1900d77065": "German army", + "57300a9a04bcaa1900d77066": "helping Adolf Hitler's rise to power", + "57300a9a04bcaa1900d77067": "1936", + "57300bf504bcaa1900d77087": "Arnhem", + "57300bf504bcaa1900d77088": "a formidable natural obstacle", + "57300bf504bcaa1900d77089": "September 1944", + "57300bf504bcaa1900d7708a": "Ludendorff Bridge", + "57300bf504bcaa1900d7708b": "an invasion of Western Europe during the Cold War", + "57300c67947a6a140053cff0": "1,230 kilometres", + "57300c67947a6a140053cff1": "Knaurs Lexikon", + "57300c67947a6a140053cff3": "a typographical error", + "57300c67947a6a140053cff2": "1,230 kilometres", + "57300c68947a6a140053cff4": "2010", + "572fac17947a6a140053cb54": "1998", + "572fac17947a6a140053cb55": "Scotland Act 1998", + "572fac17947a6a140053cb56": "the areas in which it can make laws", + "572fac17947a6a140053cb57": "Parliament of the United Kingdom", + "572fac17947a6a140053cb58": "Westminster", + "572facb0a23a5019007fc863": "the lack of a Parliament of Scotland", + "572facb0a23a5019007fc864": "three", + "572facb0a23a5019007fc865": "due to the outbreak of the First World War", + "572facb0a23a5019007fc866": "late 1960s", + "572facb0a23a5019007fc867": "a directly elected Scottish Assembly to legislate for the majority of domestic Scottish affairs", + "572fad30a23a5019007fc86d": "North Sea", + "572fad30a23a5019007fc86e": "North Sea", + "572fad30a23a5019007fc870": "1974", + "572fad30a23a5019007fc86f": "the revenues from the oil were not benefitting Scotland", + "572fad30a23a5019007fc871": "1978", + "572fadcbb2c2fd1400568329": "Edinburgh", + "572fadcbb2c2fd140056832a": "40%", + "572fadcbb2c2fd140056832c": "51.6%", + "572fadcbb2c2fd140056832b": "The 1979 Scottish devolution referendum to establish a devolved Scottish Assembly failed", + "572fadcbb2c2fd140056832d": "32.9%", + "572fae4b04bcaa1900d76bdf": "a Scottish Parliament", + "572fae4b04bcaa1900d76be0": "the Conservative Party", + "572fae4b04bcaa1900d76be1": "1989", + "572fae4b04bcaa1900d76be2": "blueprint for devolution in 1995, the Convention", + "572faec7b2c2fd1400568333": "a new Scottish Parliament Building, in the Holyrood area of Edinburgh", + "572faec7b2c2fd1400568334": "Enric Miralles", + "572faec7b2c2fd1400568335": "Spanish", + "572faec7b2c2fd1400568336": "leaf-shaped", + "572faec7b2c2fd1400568337": "Queen Elizabeth II", + "572faf74b2c2fd1400568349": "the meeting of the Church's General Assembly", + "572faf74b2c2fd1400568347": "Holyrood was being constructed, the Parliament's temporary home was the General Assembly Hall of the Church of Scotland on the Royal Mile in Edinburgh", + "572faf74b2c2fd1400568348": "the courtyard", + "572faf74b2c2fd140056834b": "University of Aberdeen", + "572faf74b2c2fd140056834a": "Strathclyde Regional Council debating chamber in Glasgow", + "572fb059947a6a140053cb80": "City of Edinburgh Council", + "572fb059947a6a140053cb81": "Lothian Regional Council on George IV Bridge", + "572fb059947a6a140053cb82": "demolished", + "572fb059947a6a140053cb83": "Parliament's visitors' centre and shop", + "572fb059947a6a140053cb84": "the main hall", + "572fb42904bcaa1900d76c15": "one MSP", + "572fb42904bcaa1900d76c16": "Tricia Marwick", + "572fb42904bcaa1900d76c17": "secret ballot", + "572fb42904bcaa1900d76c18": "129", + "572fb42904bcaa1900d76c19": "A vote clerk", + "572fbb04a23a5019007fc8f7": "the Presiding Officer", + "572fbb04a23a5019007fc8f8": "the Parliamentary Bureau", + "572fbb04a23a5019007fc8f9": "five or more seats", + "572fbb04a23a5019007fc8fa": "The Presiding Officer", + "572fbea404bcaa1900d76c5b": "a hemicycle", + "572fbea404bcaa1900d76c5c": "reflects the desire to encourage consensus amongst elected members", + "572fbea404bcaa1900d76c5d": "131", + "572fbea404bcaa1900d76c5e": "2", + "572fbea404bcaa1900d76c5f": "cannot vote", + "572fbf21a23a5019007fc938": "Scottish rivers", + "572fbf21a23a5019007fc937": "silver", + "572fbf21a23a5019007fc93a": "the Queen", + "572fbf21a23a5019007fc939": "Wisdom, Compassion, Justice and Integrity", + "572fbf21a23a5019007fc93b": "a glass case suspended from the lid", + "572fbfa504bcaa1900d76c73": "April and October", + "572fbfa504bcaa1900d76c74": "debating chamber", + "572fbfa504bcaa1900d76c75": "the public", + "572fbfa504bcaa1900d76c76": "free", + "572fbfa504bcaa1900d76c77": "the Official Report", + "572fc043a23a5019007fc95d": "Wednesdays", + "572fc043a23a5019007fc95e": "up to four minutes", + "572fc043a23a5019007fc960": "the Presiding Officer", + "572fc043a23a5019007fc95f": "religious beliefs", + "572fc043a23a5019007fc961": "nominate speakers", + "572fc41f947a6a140053cc80": "The Presiding Officer", + "572fc41f947a6a140053cc81": "speaks in chamber debates and the amount of time for which they are allowed to speak", + "572fc41f947a6a140053cc82": "different viewpoints and political parties", + "572fc41f947a6a140053cc83": "ministers or party leaders", + "572fc41f947a6a140053cc84": "Gaelic", + "572fc49d04bcaa1900d76ccb": "5 pm", + "572fc49d04bcaa1900d76ccc": "Decision Time", + "572fc49d04bcaa1900d76ccd": "vote", + "572fc49d04bcaa1900d76cce": "by means of electronic consoles on their desks", + "572fc49d04bcaa1900d76ccf": "seconds", + "572fc5a1947a6a140053cc8a": "The outcome of most votes", + "572fc5a1947a6a140053cc8b": "political parties", + "572fc5a1947a6a140053cc8c": "whips", + "572fc5a1947a6a140053cc8e": "moral", + "572fc5a1947a6a140053cc8d": "those who do are unlikely to reach higher political ranks in their parties", + "572fc659b2c2fd1400568447": "Immediately after Decision Time", + "572fc659b2c2fd1400568449": "issues which may be of interest to a particular area", + "572fc659b2c2fd1400568448": "45 minutes", + "572fc659b2c2fd140056844a": "other members", + "572fc659b2c2fd140056844b": "winds up\" the debate", + "572fc6f204bcaa1900d76cf5": "in committee", + "572fc6f204bcaa1900d76cf6": "stronger", + "572fc6f204bcaa1900d76cf7": "there is no revising chamber", + "572fc6f204bcaa1900d76cf8": "principal role of committees in the Scottish Parliament is to take evidence from witnesses, conduct inquiries and scrutinise legislation", + "572fc6f204bcaa1900d76cf9": "other locations throughout Scotland", + "572fc78d04bcaa1900d76d07": "MSPs", + "572fc78d04bcaa1900d76d08": "the balance of parties across Parliament", + "572fc78d04bcaa1900d76d09": "functions", + "572fc78d04bcaa1900d76d0a": "Mandatory Committees", + "572fc78d04bcaa1900d76d0b": "fourth", + "572fc80b04bcaa1900d76d11": "at the beginning of each parliamentary session", + "572fc80b04bcaa1900d76d12": "one", + "572fc80b04bcaa1900d76d13": "Subject Committees", + "572fc80b04bcaa1900d76d14": "Subject Committees", + "572fc8a904bcaa1900d76d1f": "A further type of committee", + "572fc8a904bcaa1900d76d20": "large-scale development projects", + "572fc8a904bcaa1900d76d21": "Private bills", + "572fc8a904bcaa1900d76d22": "Private Bill Committees", + "572fca7eb2c2fd1400568473": "The Scotland Act 1998", + "572fca7eb2c2fd1400568474": "Queen Elizabeth II", + "572fca7eb2c2fd1400568475": "devolved competencies", + "572fca7eb2c2fd1400568476": "the Parliament of the United Kingdom at Westminster", + "572fca7eb2c2fd1400568477": "the Parliament", + "572fcb6da23a5019007fc9f1": "Schedule 5", + "572fcb6da23a5019007fc9f2": "the Scottish Parliament", + "572fcb6da23a5019007fc9f3": "All matters that are not specifically reserved", + "572fcb6da23a5019007fc9f4": "3 pence in the pound", + "572fcb6da23a5019007fc9f5": "The 2012", + "572fcc43b2c2fd140056847d": "Reserved matters", + "572fcc43b2c2fd140056847e": "The Scottish Parliament", + "572fcc43b2c2fd140056847f": "Westminster", + "572fcc43b2c2fd1400568480": "Scotland Parliament", + "572fcd86947a6a140053ccda": "Bills", + "572fcd86947a6a140053ccdb": "the Scottish Government", + "572fcd86947a6a140053ccdc": "a private member", + "572fcd86947a6a140053ccdd": "an outside proposer", + "572fcd86947a6a140053ccde": "in a number of stages", + "572fce12a23a5019007fca11": "the first, or introductory", + "572fce13a23a5019007fca12": "Explanatory Notes", + "572fce13a23a5019007fca13": "whether the bill is within the legislative competence of the Parliament", + "572fce13a23a5019007fca14": "in the relevant committee or committees", + "572fce13a23a5019007fca15": "Stage 2", + "572fd1c4947a6a140053cd02": "Stage 3", + "572fd1c4947a6a140053cd03": "two", + "572fd1c4947a6a140053cd04": "final vote", + "572fd1c4947a6a140053cd05": "wrecking amendments", + "572fd1c4947a6a140053cd06": "After a general debate on the final form of the bill, members proceed to vote at Decision Time", + "572fd264b2c2fd14005684a9": "the Monarch", + "572fd264b2c2fd14005684aa": "the Presiding Officer submits it to the Monarch for royal assent", + "572fd264b2c2fd14005684ab": "4-week", + "572fd264b2c2fd14005684ac": "the Supreme Court of the United Kingdom", + "572fd264b2c2fd14005684ad": "\"The Bill for this Act of the Scottish Parliament was passed by the Parliament on [Date] and received royal assent on [Date]\"", + "572fd47fa23a5019007fca55": "The party", + "572fd47fa23a5019007fca57": "Any member", + "572fd47fa23a5019007fca56": "First Minister", + "572fd47fa23a5019007fca58": "the elected MSPs", + "572fd47fa23a5019007fca59": "the Sovereign", + "572fd6aa04bcaa1900d76d9f": "May", + "572fd6aa04bcaa1900d76da0": "May", + "572fd6aa04bcaa1900d76da1": "the Presiding Officer", + "572fd6aa04bcaa1900d76da3": "supplant it", + "572fd6aa04bcaa1900d76da2": "28", + "572fd73e947a6a140053cd32": "Several procedures", + "572fd73e947a6a140053cd33": "MSPs", + "572fd73e947a6a140053cd34": "a statement", + "572fd73e947a6a140053cd35": "issues related to the substance of the statement", + "572fd7b8947a6a140053cd3a": "Parliamentary time", + "572fd7b8947a6a140053cd3b": "Thursday", + "572fd7b8947a6a140053cd3c": "any member of the Scottish Government", + "572fd7b8947a6a140053cd3d": "issues under their jurisdiction", + "572fd7b8947a6a140053cd3e": "four", + "572fd8efb2c2fd14005684f9": "73", + "572fd8efb2c2fd14005684fb": "2005", + "572fd8efb2c2fd14005684fa": "one", + "572fd8efb2c2fd14005684fd": "their dispersed population and distance from the Scottish Parliament in Edinburgh", + "572fd8efb2c2fd14005684fc": "55,000", + "572fda6fb2c2fd140056850b": "proportionally to the number of votes received in the second vote of the ballot using the d'Hondt method", + "572fda6fb2c2fd140056850c": "d'Hondt method", + "572fda6fb2c2fd140056850d": "quotient", + "572fda6fb2c2fd140056850e": "constituency seats", + "572fda6fb2c2fd140056850f": "iteratively", + "572fdb17b2c2fd140056851d": "a number of qualifications", + "572fdb17b2c2fd140056851e": "1981", + "572fdb17b2c2fd140056851f": "over the age of 18", + "572fdb17b2c2fd1400568520": "police and the armed forces", + "572fdb17b2c2fd1400568521": "Mental Health (Care and Treatment) (Scotland) Act 2003", + "572fdbb004bcaa1900d76dd9": "Scottish Parliament", + "572fdbb004bcaa1900d76dda": "Labour", + "572fdbb004bcaa1900d76ddb": "151 votes", + "572fdbb004bcaa1900d76ddc": "eight", + "572fdbb004bcaa1900d76ddd": "Scottish independence", + "572fdc34a23a5019007fca93": "the Conservatives", + "572fdc34a23a5019007fca94": "Edinburgh Pentlands", + "572fdc34a23a5019007fca95": "five seats", + "572fdc34a23a5019007fca96": "Annabel Goldie", + "572fdc34a23a5019007fca97": "Cameron", + "572fdd03a23a5019007fca9d": "procedural", + "572fdd03a23a5019007fca9e": "domestic legislation of the Scottish Parliament", + "572fdd03a23a5019007fca9f": "the West Lothian question", + "572fdd03a23a5019007fcaa0": "Conservative", + "572fdd03a23a5019007fcaa1": "England", + "572ff626947a6a140053ce8e": "Islamism", + "572ff626947a6a140053ce8f": "all spheres", + "572ff626947a6a140053ce90": "reordering", + "572ff626947a6a140053ce91": "two poles", + "572ff626947a6a140053ce92": "revolution or invasion", + "572ff760b2c2fd1400568677": "democratic process", + "572ff760b2c2fd1400568678": "Palestine", + "572ff760b2c2fd1400568679": "seeking to abolish the state of Israel", + "572ff760b2c2fd140056867a": "democracy", + "572ff760b2c2fd140056867b": "religious", + "572ff86004bcaa1900d76f65": "\"vanguard of change and Islamic reform\" centered around the Muslim Brotherhood", + "572ff86004bcaa1900d76f66": "Sunni pan-Islamism", + "572ff86004bcaa1900d76f67": "sharia", + "572ff86004bcaa1900d76f68": "democracy", + "572ff86004bcaa1900d76f69": "to maintain their legitimacy", + "572ff932a23a5019007fcbd5": "political", + "572ff932a23a5019007fcbd6": "Islam", + "572ff932a23a5019007fcbd7": "supporters believe their views merely reflect Islam, while the contrary idea that Islam is, or can be, apolitical is an error", + "572ff932a23a5019007fcbd8": "illiberal Islamic regimes", + "572ff932a23a5019007fcbd9": "religion from politics", + "572ffabf04bcaa1900d76f9f": "Islamism", + "572ffabf04bcaa1900d76fa0": "Americans", + "572ffabf04bcaa1900d76fa1": "a historical fluke of the \"short-lived era of the heyday of secular Arab nationalism between 1945 and 1970\"", + "572ffabf04bcaa1900d76fa2": "between 1945 and 1970", + "572ffabf04bcaa1900d76fa3": "quietist/non-political Islam", + "572ffbaa947a6a140053cee7": "dangerous enemies", + "572ffbaa947a6a140053cee6": "1970s", + "572ffbaa947a6a140053ceea": "experience, ideology, and weapons", + "572ffbaa947a6a140053cee9": "mujahideen Muslim Afghanistan enemies", + "572ffbaa947a6a140053cee8": "leftist/communist/nationalist insurgents/opposition", + "572ffbaab2c2fd14005686cd": "experience, ideology, and weapons", + "572ffc99947a6a140053cef6": "Anwar Sadat", + "572ffc99947a6a140053cef7": "making peace", + "572ffc99947a6a140053cef8": "making peace with Israel", + "572ffc99947a6a140053cef9": "1975", + "572ffc99947a6a140053cefa": "assassinated", + "572ffd9e04bcaa1900d76fc7": "strict, conservative Saudi-based Wahhabism", + "572ffd9e04bcaa1900d76fc8": "hate them for their religion", + "572ffd9e04bcaa1900d76fc9": "all the horrible wars", + "572ffd9e04bcaa1900d76fca": "infidels", + "572ffd9e04bcaa1900d76fcb": "Saudi-interpretation", + "572ffe6fb2c2fd14005686ef": "Islamist", + "572ffe6fb2c2fd14005686f2": "incompetent, inefficient, or neglectful", + "572ffe6fb2c2fd14005686f0": "housing", + "572ffe6fb2c2fd14005686f3": "rhetoric", + "572ffe6fb2c2fd14005686f1": "to avoid prohibitively costly dowry demands, legal assistance, sports facilities, and women's groups", + "572ffee1947a6a140053cf14": "law and philosophy", + "572ffee1947a6a140053cf15": "All India Muslim League", + "572ffee1947a6a140053cf17": "Indian National Congress", + "572ffee1947a6a140053cf16": "1908", + "572ffee1947a6a140053cf18": "The Reconstruction of Religious Thought in Islam", + "572fffb1b2c2fd14005686f9": "secularism and secular nationalism", + "572fffb1b2c2fd14005686fa": "crowd", + "572fffb1b2c2fd14005686fb": "shedding of nationalist differences", + "572fffb1b2c2fd14005686fc": "1930", + "572fffb1b2c2fd14005686fd": "Pakistan movement", + "5730005db2c2fd1400568703": "Sayyid Abul Ala Maududi", + "5730005db2c2fd1400568704": "journalism", + "5730005db2c2fd1400568705": "1941", + "5730005db2c2fd1400568706": "political organising", + "5730005db2c2fd1400568707": "in a modern context", + "57300137b2c2fd1400568717": "Sayyid Abul Ala Maududi", + "57300137b2c2fd1400568718": "journalism", + "57300137b2c2fd140056871a": "political organising", + "57300137b2c2fd140056871b": "in a modern context", + "57300200b2c2fd1400568729": "Sharia", + "57300200b2c2fd140056872a": "an Islamic state", + "57300200b2c2fd140056872b": "unity of God", + "57300200b2c2fd140056872c": "Islamic revolution, by \"revolution\" he meant not the violence or populist policies of the Iranian Revolution", + "57300200b2c2fd140056872d": "da'wah", + "5730035e04bcaa1900d77001": "1928", + "5730035e04bcaa1900d77002": "Ismailiyah, Egypt", + "5730035e04bcaa1900d77003": "Hassan al Banna", + "5730035e04bcaa1900d77004": "the Qur'an", + "5730035e04bcaa1900d77005": "imperialist", + "5730040f947a6a140053cf4c": "violence", + "5730040f947a6a140053cf4d": "1949", + "5730040f947a6a140053cf4e": "Mahmud Fami Naqrashi", + "5730040f947a6a140053cf4f": "1948", + "5730040f947a6a140053cf50": "Gamal Abdul Nasser", + "573004bf947a6a140053cf56": "one of the most influential movements", + "573004bf947a6a140053cf59": "75%", + "573004bf947a6a140053cf57": "semi-legal", + "573004bf947a6a140053cf58": "field candidates", + "573004bf947a6a140053cf5a": "Mohamed Morsi", + "573005b9947a6a140053cf6a": "quick and decisive", + "573005b9947a6a140053cf6b": "a pivotal event", + "573005b9947a6a140053cf6c": "economic", + "573005b9947a6a140053cf6d": "A steep and steady decline", + "573005b9947a6a140053cf6e": "different democratic and anti-democratic Islamist movements", + "5730088e947a6a140053cfad": "ideological", + "5730088e947a6a140053cfac": "Ali Shariati", + "5730088e947a6a140053cfae": "somewhere between beliefs of Sunni Islamic thinkers", + "5730088e947a6a140053cfaf": "Prophet Mohammad", + "5730088e947a6a140053cfb0": "conspiracy against Islam", + "57300e2604bcaa1900d770b7": "The Islamic Republic", + "57300e2604bcaa1900d770b9": "Shia terrorist groups", + "57300e2604bcaa1900d770b8": "economic", + "57300e2604bcaa1900d770ba": "2006 Israel-Lebanon conflict", + "57300e2604bcaa1900d770bb": "President Mahmoud Ahmadinejad", + "57300ec0947a6a140053d004": "the Soviet Union", + "57300ec0947a6a140053d005": "Islamic rebellion", + "57300ec0947a6a140053d006": "send aid", + "57300ec0947a6a140053d007": "marginal", + "57300ec0947a6a140053d008": "16,000 to 35,000", + "57300f8504bcaa1900d770d1": "put an end to Saddam Hussein's occupation of Kuwait", + "57300f8504bcaa1900d770d2": "Saddam Hussein", + "57300f8504bcaa1900d770d3": "Islamist groups", + "57300f8504bcaa1900d770d4": "Saudi monarchy", + "57300f8504bcaa1900d770d5": "the west", + "573010fab2c2fd14005687d7": "conservative Muslims", + "573010fab2c2fd14005687d9": "domestic Islamists who attacked it", + "573010fab2c2fd14005687d8": "the kingdom", + "573010fab2c2fd14005687da": "Algeria", + "573010fab2c2fd14005687db": "Osama bin Laden", + "573011de04bcaa1900d770f9": "Qutb", + "573011de04bcaa1900d770fa": "1966", + "573011de04bcaa1900d770fb": "the Brotherhood", + "573011de04bcaa1900d770fc": "Fringe or splinter movements", + "573011de04bcaa1900d770fd": "1970s", + "5730126ba23a5019007fcd09": "Egyptian Islamic Jihad organization", + "5730126ba23a5019007fcd0a": "1981", + "5730126ba23a5019007fcd0b": "\"apostate\" leaders of Muslim states", + "5730126ba23a5019007fcd0c": "apostate", + "5730126ba23a5019007fcd0d": "Muhammad Abd al-Salaam Farag", + "5730131c947a6a140053d052": "violence", + "5730131c947a6a140053d053": "counter-terrorism police", + "5730131c947a6a140053d055": "2003", + "5730131c947a6a140053d054": "unsuccessful", + "5730131c947a6a140053d056": "political figures", + "5730208fa23a5019007fcded": "quiescent", + "5730208fa23a5019007fcdee": "HAMAS", + "5730208fa23a5019007fcdef": "destruction of Israel and the establishment of an Islamic state in Palestine", + "5730208fa23a5019007fcdf1": "alcohol", + "5730208fa23a5019007fcdf0": "Palestine", + "573020f7b2c2fd14005688f7": "Hamas", + "573020f7b2c2fd14005688f8": "542", + "573020f7b2c2fd14005688f9": "the majority of the seats", + "573020f7b2c2fd14005688fa": "2007", + "573020f7b2c2fd14005688fb": "driving Israel out of the Gaza Strip", + "57302700a23a5019007fce89": "Islamist", + "57302700a23a5019007fce8a": "Hassan al-Turabi", + "57302700a23a5019007fce8b": "National Islamic Front", + "57302700a23a5019007fce8c": "with money from foreign Islamist banking systems", + "57302700a23a5019007fce8d": "university and military academy", + "573027d6a23a5019007fce9d": "1985", + "573027d6a23a5019007fce9e": "with the help of the military", + "573027d6a23a5019007fce9f": "sharia law, torture and mass imprisonment of the opposition", + "573027d6a23a5019007fcea0": "Osama bin Laden", + "573027d6a23a5019007fcea1": "American attack on Iraq", + "5730285a04bcaa1900d77270": "alleviate the high rate of unemployment", + "5730285a04bcaa1900d7726f": "1989", + "5730285a04bcaa1900d7726e": "Algeria", + "5730285a04bcaa1900d7726d": "Front Islamique de Salut", + "5730285a04bcaa1900d77271": "a military coup d'\u00e9tat", + "573028fa04bcaa1900d77287": "justice and prosperity", + "573028fa04bcaa1900d77288": "vicious and destructive", + "573028fa04bcaa1900d7728a": "1992", + "573028fa04bcaa1900d77289": "poorest countries on earth", + "573028fa04bcaa1900d7728b": "80%", + "57302a3aa23a5019007fcecf": "The Taliban were spawned by the thousands of madrasahs the Deobandi movement", + "57302a3aa23a5019007fced0": "Pakistan", + "57302a3aa23a5019007fced1": "Islamic fundamentalist or neofundamentalist", + "57302a3aa23a5019007fced2": "tribal village customs", + "57302a3aa23a5019007fced3": "Wahhabism", + "57302ad804bcaa1900d772af": "July 1977", + "57302ad804bcaa1900d772b0": "alcohol and nightclubs", + "57302ad804bcaa1900d772b1": "Islamism", + "57302ad804bcaa1900d772b2": "his means of seizing power", + "57302ad804bcaa1900d772b3": "1988", + "57302bd0b2c2fd14005689db": "Wahhabi/Salafi jihadist extremist militant", + "57302bd0b2c2fd14005689dc": "Sunni Arabs", + "57302bd0b2c2fd14005689de": "ten million", + "57302bd0b2c2fd14005689df": "international recognition", + "57302bd0b2c2fd14005689dd": "a caliphate", + "57302cd004bcaa1900d772d7": "2004", + "57302cd004bcaa1900d772d8": "March 2003", + "57302cd004bcaa1900d772da": "failure to consult and \"notorious intransigence", + "57302cd004bcaa1900d772d9": "March 2011", + "57302cd004bcaa1900d772db": "a terrorist organisation", + "57302e45947a6a140053d22e": "different view", + "57302e45947a6a140053d22f": "7th century", + "57302e45947a6a140053d230": "1924", + "57302e45947a6a140053d231": "the true Islamic system", + "57302e45947a6a140053d232": "disbelieving (Kafir)", + "57302efe04bcaa1900d772f5": "armed", + "57302efe04bcaa1900d772f6": "through \"ideological struggle", + "57302efe04bcaa1900d772f7": "elites", + "57302efe04bcaa1900d772f8": "Egypt", + "57302efe04bcaa1900d772f9": "terrorist groups", + "57302faa04bcaa1900d77311": "900,000", + "57302faa04bcaa1900d77312": "strong Islamist", + "57302faa04bcaa1900d77313": "2007", + "57302faa04bcaa1900d77314": "Londonistan", + "57302faa04bcaa1900d77315": "incitement to terrorism", + "57303048947a6a140053d254": "2001", + "57303048947a6a140053d255": "State Department", + "57303048947a6a140053d256": "Christian Whiton", + "57303048947a6a140053d257": "Defense Secretary", + "57303048947a6a140053d258": "undermining the communist ideology", + "573060b48ab72b1400f9c4c6": "Latin", + "573060b48ab72b1400f9c4c7": "military force", + "573060b48ab72b1400f9c4c9": "Japanese", + "573060b48ab72b1400f9c4ca": "technologies and ideas", + "573062662461fd1900a9cdf7": "influence", + "573062662461fd1900a9cdf8": "Formal", + "573062662461fd1900a9cdfa": "\"othering", + "573062662461fd1900a9cdfb": "direct", + "57306797396df919000960ee": "uneven trade agreements forcefully", + "57306797396df919000960ef": "full-fledged colonial rule", + "57306797396df919000960f0": "aggressiveness", + "57306797396df919000960f2": "ownership of private industries", + "57306797396df919000960f1": "Informal rule", + "573081c2069b531400832133": "a nation has conquered and expanded", + "573081c2069b531400832134": "world systems theory", + "573081c2069b531400832135": "Lenin", + "573081c2069b531400832136": "empires", + "573081c2069b531400832137": "sea and trade routes", + "573083dc2461fd1900a9ce6d": "colonialism", + "573083dc2461fd1900a9ce6e": "a political focus", + "573083dc2461fd1900a9ce6f": "ideological", + "573083dc2461fd1900a9ce70": "Ottoman", + "573083dc2461fd1900a9ce71": "a person or group of people", + "573085ea8ab72b1400f9c54c": "Imperialism and colonialism", + "573085ea8ab72b1400f9c54d": "taking physical control of another", + "573085ea8ab72b1400f9c54e": "conquering the other state's lands", + "573085ea8ab72b1400f9c550": "the exploitation of the valuable assets and supplies of the nation that was conquered and the conquering nation then gaining the benefits from the spoils of the war", + "573085ea8ab72b1400f9c54f": "spoils of the war", + "5730876a396df9190009617a": "defense and justification of empire-building", + "5730876a396df9190009617c": "imperialism", + "5730876a396df9190009617b": "races of highest 'social efficiency'", + "5730876a396df9190009617d": "Social Darwinism", + "5730876a396df9190009617e": "whiteness", + "573088da069b53140083216b": "Germany", + "573088da069b53140083216c": "Britain", + "573088da069b53140083216d": "Political", + "573088da069b53140083216e": "expansion was necessary for a state\u2019s survival", + "573088da069b53140083216f": "fund travelers who would come back with tales of their discoveries", + "57308cf88ab72b1400f9c576": "environmental determinism", + "57308cf88ab72b1400f9c577": "temperate zone", + "57308cf88ab72b1400f9c578": "Orientalism", + "57308cf88ab72b1400f9c579": "uncivilized people", + "57308cf88ab72b1400f9c57a": "the superior and the norm", + "57308ddc396df919000961a5": "Terra nullius", + "57308ddc396df919000961a7": "eighteenth century", + "57308ddc396df919000961a4": "British Empire", + "57308ddc396df919000961a6": "Aboriginal", + "57308ddc396df919000961a8": "empty land", + "57308f6b8ab72b1400f9c580": "imaginative geography", + "57308f6b8ab72b1400f9c581": "a negative vision of itself", + "57308f6b8ab72b1400f9c582": "irrational and backward", + "57308f6b8ab72b1400f9c583": "place-based identities", + "57308f6b8ab72b1400f9c584": "inferior", + "5730909d8ab72b1400f9c58a": "analysis of the role of nineteenth-century maps", + "5730909d8ab72b1400f9c58b": "blank space", + "5730909d8ab72b1400f9c58c": "unknown or unexplored territory", + "5730909d8ab72b1400f9c58d": "nineteenth-century cartographic techniques", + "5730909d8ab72b1400f9c58e": "French", + "573092088ab72b1400f9c595": "pre-Columbian era", + "573092088ab72b1400f9c594": "Genghis Khan", + "573092088ab72b1400f9c597": "dozens", + "573092088ab72b1400f9c598": "Oyo Empire", + "573092088ab72b1400f9c596": "Sub-Saharan Africa", + "573093598ab72b1400f9c5ae": "Cultural imperialism", + "573093598ab72b1400f9c5af": "soft power", + "573093598ab72b1400f9c5b0": "Dallas", + "573093598ab72b1400f9c5b1": "Roman", + "573093598ab72b1400f9c5b2": "bans on foreign popular culture, control of the internet and unauthorised satellite dishes", + "57309446396df919000961b8": "around 1700", + "57309446396df919000961b9": "colonizing, influencing, and annexing other parts of the world", + "57309446396df919000961ba": "thousands", + "57309446396df919000961bb": "1700", + "57309446396df919000961bc": "Open Door Policy", + "57309564069b5314008321a5": "1919", + "57309564069b5314008321a6": "1999", + "57309564069b5314008321a7": "historians", + "57309564069b5314008321a8": "the world's economy", + "57309564069b5314008321a9": "imperial powers", + "573098f38ab72b1400f9c5d2": "economic growth", + "573098f38ab72b1400f9c5d4": "mid-18th century", + "573098f38ab72b1400f9c5d3": "economic growth by collecting resources from colonies", + "573098f38ab72b1400f9c5d5": "the political weakness of the Mughal state", + "573099ee8ab72b1400f9c5dc": "communication", + "573099ee8ab72b1400f9c5dd": "deadly explosives", + "573099ee8ab72b1400f9c5de": "machine gun", + "573099ee8ab72b1400f9c5df": "arrows, swords, and leather shields", + "573099ee8ab72b1400f9c5e0": "Europe", + "57309bfb8ab72b1400f9c5e6": "British", + "57309bfb8ab72b1400f9c5e7": "late 1870s", + "57309bfb8ab72b1400f9c5e8": "philanthropy", + "57309bfb8ab72b1400f9c5e9": "constantly expand investment, material resources and manpower in such a way that necessitated colonial expansion", + "57309ef18ab72b1400f9c600": "aristocracy", + "57309ef18ab72b1400f9c602": "1950s", + "57309ef18ab72b1400f9c601": "1883\u20131950", + "57309ef18ab72b1400f9c603": "domestic social reforms could cure the international disease of imperialism by removing its economic foundation", + "57309ef18ab72b1400f9c604": "domestic social reforms could cure the international disease of imperialism by removing its economic foundation", + "5730a0778ab72b1400f9c60a": "environmental determinism", + "5730a0778ab72b1400f9c60b": "the environment in which they lived", + "5730a0778ab72b1400f9c60c": "less civilized", + "5730a0778ab72b1400f9c60d": "Africa", + "5730a0778ab72b1400f9c60e": "orientalism and tropicality", + "5730a314069b5314008321eb": "geographic scholars", + "5730a314069b5314008321ec": "Northern Europe and the Mid-Atlantic", + "5730a314069b5314008321ed": "guidance and intervention", + "5730a314069b5314008321ee": "orientalism", + "5730a314069b5314008321ef": "colonizing empires", + "5730a40f396df91900096234": "sixteenth century", + "5730a40f396df91900096235": "1599", + "5730a40f396df91900096236": "Queen Elizabeth", + "5730a40f396df91900096237": "bankruptcy", + "5730a40f396df91900096238": "Portuguese", + "5730a4d02461fd1900a9cf29": "1830", + "5730a4d02461fd1900a9cf2a": "after 1850", + "5730a4d02461fd1900a9cf2d": "Catholicism", + "5730a4d02461fd1900a9cf2b": "North and West Africa", + "5730a4d02461fd1900a9cf2c": "1850", + "5730a951069b531400832213": "civilize the inferior", + "5730a951069b531400832214": "Full citizenship rights", + "5730a951069b531400832215": "small numbers of settlers", + "5730a951069b531400832216": "Christianity and French culture", + "5730a951069b531400832217": "Algeria", + "5730aa52069b53140083221d": "overseas colonies", + "5730aa52069b53140083221e": "anti-colonial movements", + "5730aa52069b53140083221f": "Vietnam", + "5730aa52069b531400832220": "Vietnam", + "5730aa52069b531400832221": "1960", + "5730ab63396df91900096260": "Scandinavia and northern Europe", + "5730ab63396df91900096263": "Muslim Iberia", + "5730ab63396df91900096261": "middle period of classical antiquity", + "5730ab63396df91900096262": "late antiquity", + "5730ab63396df91900096264": "central Europe", + "5730ac782461fd1900a9cf73": "late 19th century", + "5730ac782461fd1900a9cf74": "1862\u201390", + "5730ac782461fd1900a9cf75": "after the Franco-German War", + "5730ac782461fd1900a9cf77": "defeat of Napoleon", + "5730ac782461fd1900a9cf76": "Europe", + "5730aef38ab72b1400f9c682": "South Pacific", + "5730aef38ab72b1400f9c683": "German prestige", + "5730aef38ab72b1400f9c685": "1884", + "5730aef38ab72b1400f9c684": "German New Guinea", + "5730aef38ab72b1400f9c686": "Hamburg merchants and traders", + "5730b1022461fd1900a9cfa4": "Japan took part of Sakhalin Island from Russia", + "5730b1022461fd1900a9cfa3": "1894", + "5730b1022461fd1900a9cfa6": "Thailand", + "5730b1022461fd1900a9cfa5": "Manchuria", + "5730b255396df919000962b0": "The Soviet Union and the People\u2019s Republic of China", + "5730b255396df919000962b1": "1932", + "5730b255396df919000962b2": "Lenin", + "5730b255396df919000962b3": "Eastern Europe", + "5730b255396df919000962b4": "Bolshevik leaders", + "5730b4282461fd1900a9cfc5": "the revolution could only succeed in Russia as part of a world revolution", + "5730b4282461fd1900a9cfc6": "Lenin", + "5730b4282461fd1900a9cfc9": "Mao Zedong", + "5730b4282461fd1900a9cfc8": "Nikita Khrushchev", + "5730b4282461fd1900a9cfc7": "socialism in one country'", + "5730b541396df919000962c2": "mercantilism", + "5730b541396df919000962c3": "1776", + "5730b541396df919000962c5": "free trade", + "5730b541396df919000962c4": "1820", + "5730b541396df919000962c6": "1815", + "5730b6592461fd1900a9cfcf": "British Empire", + "5730b6592461fd1900a9cfd0": "pseudo-sciences", + "5730b6592461fd1900a9cfd2": "The British Empire", + "5730b6592461fd1900a9cfd1": "Middle East", + "5730b7ce069b5314008322c3": "oppose the US annexation of the Philippines and Cuba", + "5730b7ce069b5314008322c4": "interventionism in Central America", + "5730b7ce069b5314008322c6": "a war erupted in the Philippines", + "5730b7ce069b5314008322c5": "Philippines", + "5730b7ce069b5314008322c7": "racket", + "5730b8ca8ab72b1400f9c704": "Isiah Bowman", + "5730b8ca8ab72b1400f9c705": "1917", + "5730b8ca8ab72b1400f9c706": "President Wilson and the American delegation from the Paris Peace Conference", + "5730b8ca8ab72b1400f9c707": "allow for U.S authorship of a 'new world' which was to be characterized by geographical order", + "5730b8ca8ab72b1400f9c708": "Wilson's geographer", + "5730bb522461fd1900a9d011": "internal strife", + "5730bb522461fd1900a9d012": "internal colonialism", + "5730bb522461fd1900a9d013": "12 to 15 million", + "5730bb522461fd1900a9d015": "the contemporary Orient", + "5730bc308ab72b1400f9c73c": "1299 to 1923", + "5730bc308ab72b1400f9c73d": "Suleiman the Magnificent", + "5730bc308ab72b1400f9c73e": "32", + "5730bc308ab72b1400f9c73f": "the Caucasus", + "5730bc308ab72b1400f9c740": "16th and 17th centuries", + "5730bd00069b5314008322d7": "Istanbul", + "5730bd00069b5314008322d9": "Germany", + "5730bd00069b5314008322db": "World War I", + "5730bd00069b5314008322da": "Turkey", + "5730982f396df919000961e2": "United Methodist Church", + "5730982f396df919000961e3": "a mainline Protestant Methodist denomination", + "5730982f396df919000961e4": "1968", + "5730982f396df919000961e5": "union of the Methodist Church (USA", + "5730982f396df919000961e6": "Wesleyan", + "573098c12461fd1900a9cee5": "United Methodist Church", + "573098c12461fd1900a9cee6": "80 million", + "573098c12461fd1900a9cee7": "mainline Protestant denomination", + "573098c12461fd1900a9cee8": "3.6%", + "57309921396df919000961f6": "mid-18th century", + "57309921396df919000961f7": "Church of England", + "57309921396df919000961f8": "methodical and exceptionally detailed in their Bible study, opinions and disciplined lifestyle", + "573099f42461fd1900a9cef7": "1735", + "573099f42461fd1900a9cef8": "the colony of Georgia", + "573099f42461fd1900a9cef9": "the American Indians", + "573099f42461fd1900a9cefa": "salvation by God's grace", + "57309a6c2461fd1900a9ceff": "the American Revolution", + "57309a6c2461fd1900a9cf00": "1784", + "57309a6c2461fd1900a9cf01": "Thomas Coke", + "57309a6c2461fd1900a9cf02": "Lovely Lane Methodist Church", + "57309a6c2461fd1900a9cf03": "Lovely Lane Methodist Church", + "57309adb396df919000961fc": "St. George's United Methodist Church", + "57309adb396df919000961fd": "St. George's United Methodist Church", + "57309adb396df919000961fe": "1767", + "57309adb396df919000961ff": "a sail loft on Dock Street", + "57309adb396df91900096200": "1784", + "57309cd6069b5314008321c3": "Richard Allen and Absalom Jones", + "57309cd6069b5314008321c4": "St. George's Church", + "57309cd6069b5314008321c5": "1784", + "57309d31396df91900096210": "1830", + "57309d31396df91900096211": "over the issue of laity having a voice and vote in the administration of the church", + "57309d31396df91900096212": "1844", + "57309d31396df91900096213": "tensions over slavery and the power of bishops in the denomination", + "5730a97a396df9190009625a": "April 23, 1968", + "5730a97a396df9190009625b": "Dallas, Texas", + "5730a97a396df9190009625c": "Bishop Lloyd Christ Wicke", + "5730a9fa2461fd1900a9cf6d": "holy catholic", + "5730a9fa2461fd1900a9cf6e": "The Book of Discipline", + "5730a9fa2461fd1900a9cf6f": "all who are truly believers in every age belong to the holy Church invisible", + "5730aaa88ab72b1400f9c64e": "As a result of the American Revolution", + "5730aaa88ab72b1400f9c650": "Dr. Thomas Coke", + "5730aaa88ab72b1400f9c64f": "Thomas Vasey and Richard Whatcoat", + "5730ab288ab72b1400f9c655": "1968", + "5730ab288ab72b1400f9c654": "John Wesley and Charles Wesley", + "5730ab288ab72b1400f9c656": "Albert C. Outler", + "5730ab288ab72b1400f9c657": "Albert C. Outler", + "5730ac6b8ab72b1400f9c670": "Prevenient grace", + "5730ac6b8ab72b1400f9c672": "Prevenient grace", + "5730ac6b8ab72b1400f9c671": "the grace that \"goes before\" us", + "5730ac6b8ab72b1400f9c673": "sin", + "5730aeba069b531400832241": "Justifying Grace or Accepting Grace", + "5730aeba069b531400832242": "justifying grace", + "5730aeba069b531400832243": "conversion", + "5730aeba069b531400832244": "conversion", + "5730aeba069b531400832245": "the New Birth", + "5730afed069b53140083225f": "grace of God which sustains the believers in the journey toward Christian Perfection", + "5730afed069b531400832260": "Sanctifying Grace", + "5730afed069b531400832261": "a genuine love of God with heart, soul, mind, and strength, and a genuine love of our neighbors as ourselves", + "5730afed069b531400832262": "Sanctifying Grace", + "5730b07c8ab72b1400f9c696": "Wesleyan theology", + "5730b07c8ab72b1400f9c697": "prima scriptura", + "5730b07c8ab72b1400f9c698": "UMC", + "5730b07c8ab72b1400f9c699": "The Book of Discipline", + "5730b10b8ab72b1400f9c69f": "2008", + "5730b10b8ab72b1400f9c69e": "pro-choice", + "5730b10b8ab72b1400f9c6a0": "Religious Coalition for Reproductive Choice", + "5730b1e28ab72b1400f9c6ae": "The General Board of Church and Society, and the United Methodist Women", + "5730b1e28ab72b1400f9c6af": "all women", + "5730b1e28ab72b1400f9c6b0": "the mother", + "5730b2312461fd1900a9cfad": "Taskforce of United Methodists on Abortion and Sexuality", + "5730b2312461fd1900a9cfae": "2012", + "5730b2312461fd1900a9cfaf": "Rev. Paul T. Stallsworth", + "5730b2ac2461fd1900a9cfb3": "temperance movement", + "5730b2ac2461fd1900a9cfb6": "2011 and 2012", + "5730b2ac2461fd1900a9cfb4": "The Use of Money,\"", + "5730b2ac2461fd1900a9cfb5": "unfermented grape juice", + "5730b54c069b53140083228d": "capital punishment", + "5730b54c069b53140083228e": "John 8:7", + "5730b54c069b53140083228f": "Matthew 5:38-39", + "5730b54c069b531400832290": "The General Conference of the United Methodist Church", + "5730b5cc396df919000962d2": "same-sex", + "5730b5cc396df919000962d3": "1999", + "5730b5cc396df919000962d4": "2016", + "5730b6bd2461fd1900a9cfd7": "the Connectional Table", + "5730b6bd2461fd1900a9cfd8": "LGBT", + "5730b6bd2461fd1900a9cfd9": "same-gender marriages with resolutions", + "5730b776069b5314008322bd": "1987", + "5730b776069b5314008322be": "2005", + "5730b776069b5314008322bf": "The Baltimore-Washington Conference of the UMC", + "5730b9852461fd1900a9cff9": "conscription", + "5730b9852461fd1900a9cffa": "military action", + "5730b9852461fd1900a9cffb": "all war, or any particular war", + "5730b9dc8ab72b1400f9c70e": "Christ's message and teachings", + "5730b9dc8ab72b1400f9c70f": "national foreign policy", + "5730b9dc8ab72b1400f9c710": "general and complete disarmament", + "5730bdfe396df9190009630e": "Sexual Ethics Task Force", + "5730bdfe396df9190009630f": "violence, degradation, exploitation, and coercion", + "5730bdfe396df91900096310": "girls and women", + "5730bf03069b5314008322eb": "IVF", + "5730bf03069b5314008322ed": "stem cells retrieved from umbilical cords and adult stem cells", + "5730bf03069b5314008322ec": "research", + "5730c059069b531400832305": "the Sunday Service of the Methodists in North America", + "5730c059069b531400832306": "When the Methodists in America were separated from the Church of England", + "5730c059069b531400832307": "Book of Common Prayer", + "5730c52fb54a4f140068cc46": "Africa", + "5730c52fb54a4f140068cc47": "Book of Common Prayer", + "5730c52fb54a4f140068cc48": "anointing with oil", + "5730c6d3b54a4f140068cc4c": "Methodist institutions", + "5730c6d3b54a4f140068cc4d": "William Booth", + "5730c6d3b54a4f140068cc4e": "John Wesley", + "5730c737b54a4f140068cc52": "United Methodist Church", + "5730c737b54a4f140068cc54": "the General Conference", + "5730c737b54a4f140068cc55": "Book of Discipline", + "5730c737b54a4f140068cc53": "General Conference", + "5730c737b54a4f140068cc56": "every four years", + "5730c810aca1c71400fe5aa7": "five", + "5730c810aca1c71400fe5aa8": "seven", + "5730c810aca1c71400fe5aa9": "to elect and appoint bishops", + "5730c810aca1c71400fe5aaa": "bishops", + "5730c810aca1c71400fe5aab": "Episcopal Areas", + "5730c8a1f6cb411900e2449c": "Mission Council", + "5730c8a1f6cb411900e2449d": "church bishops", + "5730c8a1f6cb411900e2449e": "36", + "5730c8a1f6cb411900e2449f": "George W. Bush Presidential Library", + "5730c8a1f6cb411900e244a0": "Southern Methodist University", + "5730ca6eaca1c71400fe5ac2": "nine", + "5730ca6eaca1c71400fe5ac1": "The Judicial Council", + "5730ca6eaca1c71400fe5ac3": "eight-year", + "5730ca6eaca1c71400fe5ac4": "twice", + "5730ca6eaca1c71400fe5ac5": "various locations throughout the world", + "5730cb0fb7151e1900c0154a": "The Annual Conference", + "5730cb0fb7151e1900c0154b": "the geographical area it covers as well as the frequency of meeting", + "5730cb0fb7151e1900c0154c": "Annual Conference", + "5730cb8df6cb411900e244c2": "The Book of Discipline", + "5730cb8df6cb411900e244c3": "at least three", + "5730cb8df6cb411900e244c4": "at least three", + "5730cb8df6cb411900e244c5": "The church conference", + "5730cb8df6cb411900e244c6": "The church conference", + "5730cc2cb54a4f140068cc66": "one hundred", + "5730cc2cb54a4f140068cc67": "three hundred sixty", + "5730cc2cb54a4f140068cc68": "International Association of Methodist-related Schools, Colleges, and Universities", + "5730d26fb54a4f140068cc94": "John Wesley", + "5730d26fb54a4f140068cc95": "pastors", + "5730d26fb54a4f140068cc96": "Annual Conference Order of Elders", + "5730d26fb54a4f140068cc97": "Annual Conference Order of Deacons", + "5730d3adaca1c71400fe5af5": "Annual Conference Cabinet", + "5730d3adaca1c71400fe5af6": "annually", + "5730d3adaca1c71400fe5af7": "the bishop has read the appointments at the session of the Annual Conference", + "5730d473b7151e1900c0155a": "Elders", + "5730d473b7151e1900c0155b": "a bishop", + "5730d473b7151e1900c0155c": "2\u20133", + "5730d473b7151e1900c0155d": "District Superintendents", + "5730d523aca1c71400fe5b03": "2\u20133", + "5730d523aca1c71400fe5b04": "Deacons", + "5730d523aca1c71400fe5b05": "Deacons", + "5730d523aca1c71400fe5b06": "sacramental authority", + "5730d597f6cb411900e244d6": "1996", + "5730d597f6cb411900e244d7": "The provisional elder/deacon", + "5730d597f6cb411900e244d8": "the ordination order of transitional deacon", + "5730d6fcb7151e1900c01562": "Licensed Local Pastor", + "5730d6fcb7151e1900c01563": "The licensed local pastor", + "5730d6fcb7151e1900c01564": "five", + "5730d6fcb7151e1900c01565": "Associate", + "5730d77ef6cb411900e244dc": "Baptized Members", + "5730d77ef6cb411900e244dd": "through confirmation and sometimes the profession of faith", + "5730d77ef6cb411900e244de": "through transfer from another Christian denomination", + "5730de74f6cb411900e244fc": "Baptism", + "5730de74f6cb411900e244fd": "confirmation and membership preparation classes", + "5730de74f6cb411900e244fe": "The Book of Discipline of the United Methodist Church", + "5730de74f6cb411900e244ff": "Church and the Methodist-Christian theological tradition", + "5730e936aca1c71400fe5b61": "lay servants", + "5730e936aca1c71400fe5b62": "they must be recommended by their pastor and Church Council or Charge Conference, and complete the basic course for lay servant", + "5730e936aca1c71400fe5b63": "annually", + "5730e936aca1c71400fe5b64": "two", + "5730e9f4aca1c71400fe5b73": "The United Methodist Church", + "5730e9f4aca1c71400fe5b74": "observer status", + "5730e9f4aca1c71400fe5b75": "blurring of theological and confessional differences in the interests of unity", + "5730ea71b54a4f140068cce4": "2000", + "5730ea71b54a4f140068cce5": "May 2012", + "5730ea71b54a4f140068cce6": "1985", + "5730eb5b497a881900248a3f": "11 million", + "5730eb5b497a881900248a40": "42,000", + "5730eb5b497a881900248a41": "8 million", + "5730eb5b497a881900248a42": "34,000", + "5730eb5b497a881900248a43": "Texas", + "5730ebe0a5e9cc1400cdbae5": "11.4 million", + "5730ebe0a5e9cc1400cdbae6": "11.4 million, with about 7.9 million", + "5730ebe0a5e9cc1400cdbae7": "3.5 million", + "5730ec85e6313a140071caba": "Wesleyan Holiness Consortium", + "5730ec85e6313a140071cabb": "World Methodist Council", + "5730ec85e6313a140071cabc": "July 18, 2006", + "5733cf61d058e614000b62e9": "1754\u20131763", + "5733cf61d058e614000b62ea": "British America and New France", + "5733cf61d058e614000b62eb": "60,000", + "5733cf61d058e614000b62ec": "2 million", + "5733cff84776f419006612b4": "along the frontiers between New France and the British colonies", + "5733cff84776f419006612b5": "a dispute over control of the confluence of the Allegheny and Monongahela rivers", + "5733cff84776f419006612b6": "May 1754", + "5733d13e4776f419006612c4": "1755", + "5733d13e4776f419006612c5": "a disaster", + "5733d13e4776f419006612c6": "poor management, internal divisions, and effective Canadian scouts, French regular forces, and Indian warrior allies", + "5733d13e4776f419006612c7": "Fort Beaus\u00e9jour", + "5733d13e4776f419006612c8": "four-way attack", + "5733d249d058e614000b6331": "William Pitt", + "5733d249d058e614000b6332": "increased British military resources", + "5733d249d058e614000b6333": "European theatre of the war", + "5733d249d058e614000b6334": "Sainte Foy in Quebec", + "5733d2dbd058e614000b6339": "French Louisiana", + "5733d2dbd058e614000b633a": "Havana, Cuba", + "5733d2dbd058e614000b633b": "one of the most significant developments in a century of Anglo-French conflict", + "5733d3cb4776f419006612ea": "1740s", + "5733d3cb4776f419006612eb": "the second war", + "5733d3cb4776f419006612ec": "a much larger conflict between France and Great Britain", + "5733d3cb4776f419006612ed": "the Fourth Intercolonial War and the Great War for the Empire", + "5733d4c8d058e614000b6353": "1756 to the signing of the peace treaty in 1763", + "5733d4c8d058e614000b6354": "six years", + "5733d4c8d058e614000b6355": "1760", + "5733d4c8d058e614000b6356": "Battle of Jumonville Glen", + "5733d5704776f4190066130e": "75,000", + "5733d5704776f4190066130f": "St. Lawrence River valley", + "5733d5704776f41900661310": "St. Lawrence and Mississippi watersheds", + "5733d68ed058e614000b637f": "20 to 1", + "5733d68ed058e614000b6380": "Nova Scotia and Newfoundland in the north, to Georgia in the south", + "5733d68ed058e614000b6381": "along the coast", + "5733d7cbd058e614000b63ab": "native tribes", + "5733d7cbd058e614000b63ac": "Mi'kmaq and the Abenaki", + "5733d7cbd058e614000b63ad": "Upstate New York and the Ohio Country", + "5733d7cbd058e614000b63ae": "Iroquois rule", + "5733da01d058e614000b63f9": "Catawba, Muskogee-speaking Creek and Choctaw, and the Iroquoian-speaking Cherokee tribes", + "5733da01d058e614000b63fa": "western portions of the Great Lakes region", + "5733da01d058e614000b63fb": "Iroquois Six Nations", + "5733dab4d058e614000b6409": "no French regular army troops", + "5733dab4d058e614000b640a": "few", + "5733dab4d058e614000b640b": "mustered local militia companies, generally ill trained and available only for short periods, to deal with native threats", + "5733db8dd058e614000b6428": "3,000 miles (4,800 km)", + "5733db8dd058e614000b6429": "about 200 Troupes de la marine and 30 Indians", + "5733db8dd058e614000b642a": "Whenever he encountered British merchants or fur-traders", + "5733dc95d058e614000b644a": "informed C\u00e9loron that they owned the Ohio Country", + "5733dc95d058e614000b644b": "Pickawillany", + "5733dc95d058e614000b644c": "ignored the warning", + "5733dc95d058e614000b644d": "ignored the warning", + "5733dd4f4776f419006613aa": "very badly disposed towards the French", + "5733dd4f4776f419006613ab": "brisk trade in European colonial captives from either side.", + "5733dd4f4776f419006613ac": "forceful", + "5733e5a14776f4190066145b": "1749", + "5733e5a14776f4190066145c": "Ohio Company of Virginia", + "5733e5a14776f4190066145d": "Christopher Gist", + "5733e5a14776f4190066145e": "Treaty of Logstown", + "5733e5a14776f4190066145f": "at the mouth of the Monongahela River", + "5733e771d058e614000b6545": "King George's War", + "5733e771d058e614000b6546": "Treaty of Aix-la-Chapelle", + "5733e771d058e614000b6547": "conflicting territorial claims between British and French colonies in North America", + "5733e771d058e614000b6548": "The issues of conflicting territorial claims between British and French colonies in North America were turned over to a commission to resolve", + "5733e8ae4776f419006614a6": "Marquis de la Jonqui\u00e8re", + "5733e8ae4776f419006614a7": "300 men", + "5733e8ae4776f419006614a8": "to punish the Miami people of Pickawillany", + "5733e8ae4776f419006614a9": "capturing three traders", + "5733ea04d058e614000b6594": "Paul Marin de la Malgue", + "5733ea04d058e614000b6595": "Fort Presque Isle", + "5733ea04d058e614000b6596": "Fort Le Boeuf", + "5733ea04d058e614000b6597": "to protect the King's land in the Ohio Valley from the British", + "5733ea04d058e614000b6598": "Tanaghrisson", + "5733eb34d058e614000b65cc": "Superintendent for Indian Affairs", + "5733eb34d058e614000b65cd": "Warraghiggey", + "5733eb34d058e614000b65ce": "Warraghiggey", + "5733eb34d058e614000b65cf": "Mohawk Chief Hendrick", + "5733ef47d058e614000b662b": "Ohio Company", + "5733ef47d058e614000b662c": "Major George Washington", + "5733ef47d058e614000b662d": "Jacob Van Braam", + "5733ef47d058e614000b662e": "December 12", + "5733f062d058e614000b6633": "Jacques Legardeur de Saint-Pierre", + "5733f062d058e614000b6634": "the letter from Dinwiddie", + "5733f062d058e614000b6635": "\"As to the Summons you send me to retire, I do not think myself obliged to obey it.\"", + "5733f062d058e614000b6636": "France's claim to the region was superior to that of the British", + "5733f1784776f41900661575": "500", + "5733f1784776f41900661576": "1754", + "5733f1784776f41900661577": "Fort Duquesne", + "5733f309d058e614000b6648": "surprised the Canadians", + "5733f309d058e614000b6649": "They killed many of the Canadians", + "5733f309d058e614000b664a": "to gain the support of the British and regain authority over his own people", + "5733f410d058e614000b6663": "to dislodge the French", + "5733f410d058e614000b6664": "well before Braddock's departure for North America", + "5733f410d058e614000b6665": "dispatched six regiments", + "5733f410d058e614000b6666": "blockade French ports", + "5733f5264776f419006615a3": "Albany Congress", + "5733f5264776f419006615a4": "to formalize a unified front in trade and negotiations with various Indians", + "5733f5264776f419006615a5": "The plan that the delegates agreed to was never ratified by the colonial legislatures nor approved of by the crown", + "5733f5264776f419006615a6": "to formalize a unified front in trade and negotiations with various Indians", + "5733f5f24776f419006615c1": "Braddock", + "5733f5f24776f419006615c2": "The expedition was a disaster", + "5733f5f24776f419006615c3": "1,000", + "5733f5f24776f419006615c4": "Washington and Thomas Gage", + "5733f7b9d058e614000b66a9": "Shirley and Johnson", + "5733f7b9d058e614000b66aa": "logistical difficulties", + "5733f7b9d058e614000b66ab": "Fort Niagara", + "5733f7b9d058e614000b66ac": "garrisons", + "5733f8dc4776f419006615f7": "Marquis de Vaudreuil", + "5733f8dc4776f419006615f8": "sent Dieskau to Fort St. Fr\u00e9d\u00e9ric to meet that threat", + "5733f8dc4776f419006615f9": "Fort Edward and Fort William Henry", + "5733f8dc4776f419006615fa": "Fort William Henry", + "5733f8dc4776f419006615fb": "Ticonderoga Point", + "5733f9fa4776f4190066161f": "Colonel Monckton", + "5733f9fa4776f41900661620": "ordered the deportation of the French-speaking Acadian population from the area", + "5733f9fa4776f41900661621": "at Petitcodiac in 1755 and at Bloody Creek near Annapolis Royal in 1757", + "5733faaf4776f4190066162f": "William Shirley", + "5733faaf4776f41900661630": "Albany", + "5733faaf4776f41900661631": "Fort Frontenac", + "5733faaf4776f41900661632": "through the wilderness of the Maine district", + "5733fb7bd058e614000b66ff": "Major General James Abercrombie", + "5733fb7bd058e614000b6700": "Major General Louis-Joseph de Montcalm", + "5733fb7bd058e614000b6701": "May 18, 1756", + "5733fc6ed058e614000b670f": "Oneida Carry", + "5733fc6ed058e614000b6710": "an attack against the forts Shirley had erected at the Oneida Carry", + "5733fc6ed058e614000b6711": "45,000 pounds", + "5733fc6ed058e614000b6712": "any British hopes for campaigns on Lake Ontario", + "5733fd66d058e614000b6735": "Abercrombie", + "5733fd66d058e614000b6736": "Ticonderoga", + "5733fd66d058e614000b6737": "Oswego", + "5733fd66d058e614000b6738": "the disposition of prisoners' personal effects", + "5733fe73d058e614000b673d": "an attack on New France's capital, Quebec", + "5733fe73d058e614000b673e": "to distract Montcalm", + "5733fe73d058e614000b673f": "William Pitt", + "5733fe73d058e614000b6740": "returned to New York", + "5733ffa7d058e614000b674f": "French irregular forces", + "5733ffa7d058e614000b6750": "Lake George", + "5733ffa7d058e614000b6751": "attacked the British column", + "57340111d058e614000b677d": "poor harvest", + "57340111d058e614000b677e": "poor harvest", + "57340111d058e614000b677f": "St. Lawrence", + "5734025d4776f419006616c3": "The British failures in North America", + "5734025d4776f419006616c4": "Loudoun", + "5734025d4776f419006616c5": "three major offensive actions involving large numbers of regular troops", + "5734025d4776f419006616c6": "Two", + "573403394776f419006616dd": "3,600", + "573403394776f419006616de": "3,600 Frenchmen famously and decisively defeated Abercrombie's force of 18,000", + "573403394776f419006616df": "Abercrombie saved something from the disaster when he sent John Bradstreet on an expedition that successfully destroyed Fort Frontenac", + "573403394776f419006616e0": "Abercrombie saved something", + "57340549d058e614000b67dd": "an invasion of Britain", + "57340549d058e614000b67de": "The invasion failed both militarily and politically", + "57340549d058e614000b67df": "Lagos and Quiberon Bay", + "573406d1d058e614000b6801": "James Wolfe", + "573406d1d058e614000b6802": "successfully cut off the French frontier forts further to the west and south", + "573406d1d058e614000b6803": "Battle of Sainte-Foy", + "573406d1d058e614000b6804": "the British were able to prevent the arrival of French relief ships in the naval Battle of the Restigouche", + "573407d7d058e614000b6813": "Governor Vaudreuil", + "573407d7d058e614000b6814": "medical treatment", + "573407d7d058e614000b6815": "General Amherst", + "573408ef4776f41900661757": "10 February 1763", + "573408ef4776f41900661758": "15 February 1763", + "573408ef4776f41900661759": "France chose to cede the former", + "573408ef4776f4190066175a": "They viewed the economic value of the Caribbean islands' sugar cane to be greater and easier to defend than the furs from the continent", + "57340a094776f4190066177d": "80,000", + "57340a094776f4190066177e": "1755", + "57340a094776f4190066177f": "North American provinces", + "57340a094776f41900661780": "New Orleans", + "57340b1bd058e614000b6869": "King George III", + "57340b1bd058e614000b686a": "outlined the division and administration of the newly conquered territory", + "57340b1bd058e614000b686b": "west of the Appalachian Mountains", + "57340d124776f419006617c3": "Cuba", + "57340d124776f419006617c0": "legal and illegal settlement", + "57340d124776f419006617c1": "1769", + "57340d124776f419006617c2": "Choctaw and the Creek", + "57340d124776f419006617bf": "disappearance of a strong ally and counterweight to British expansion, leading to their ultimate dispossession", + "573735e8c3c5551400e51e71": "force", + "573735e8c3c5551400e51e72": "A fundamental error", + "573735e8c3c5551400e51e73": "Sir Isaac Newton", + "573735e8c3c5551400e51e74": "nearly three hundred years", + "573735e8c3c5551400e51e75": "Sir Isaac Newton", + "57373a9fc3c5551400e51e7b": "a Standard Model", + "57373a9fc3c5551400e51e7c": "gauge bosons", + "57373a9fc3c5551400e51e7d": "strong, electromagnetic, weak, and gravitational", + "57373a9fc3c5551400e51e7e": "electromagnetic, weak, and gravitational", + "57373a9fc3c5551400e51e7f": "a more fundamental electroweak interaction", + "57373d0cc3c5551400e51e85": "Aristotle", + "57373d0cc3c5551400e51e86": "Aristotelian cosmology", + "57373d0cc3c5551400e51e87": "four", + "57373d0cc3c5551400e51e88": "on the ground", + "57373d0cc3c5551400e51e89": "unnatural", + "57373f80c3c5551400e51e8f": "17th century", + "57373f80c3c5551400e51e90": "Galileo Galilei", + "57373f80c3c5551400e51e91": "an innate force of impetus", + "57373f80c3c5551400e51e92": "Galileo", + "57373f80c3c5551400e51e93": "friction", + "5737432bc3c5551400e51e99": "Newton", + "5737432bc3c5551400e51e9a": "a lack of net force", + "5737432bc3c5551400e51e9b": "Newton", + "5737432bc3c5551400e51e9c": "Newton's First Law", + "5737432bc3c5551400e51e9d": "in all frames related by a Galilean transformation", + "5737477bc3c5551400e51ea3": "the laws of physics", + "5737477bc3c5551400e51ea4": "curving parabolic path", + "5737477bc3c5551400e51ea5": "the outside world that is moving with a constant speed in the opposite direction", + "5737477bc3c5551400e51ea6": "Inertia", + "573749741c4567190057445d": "inertia", + "573749741c4567190057445e": "rotational inertia", + "573749741c4567190057445f": "Albert Einstein", + "573749741c45671900574460": "weightlessness", + "573749741c45671900574461": "equivalence", + "573750f51c45671900574467": "inverse", + "573750f61c45671900574468": "kinematic", + "573750f61c45671900574469": "General relativity", + "573750f61c4567190057446a": "microscales", + "573750f61c4567190057446b": "fixed", + "5737534ec3c5551400e51eab": "Newton's Third Law", + "5737534ec3c5551400e51eac": "The third law", + "5737534ec3c5551400e51ead": "unidirectional force", + "5737534ec3c5551400e51eae": "equal in magnitude and opposite in direction", + "573755afc3c5551400e51eb3": "the center of mass", + "573755afc3c5551400e51eb4": "closed", + "573755afc3c5551400e51eb5": "the mass of the system", + "573766251c45671900574471": "an intuitive understanding", + "573766251c45671900574472": "precise operational definitions", + "573766251c45671900574473": "Newtonian mechanics", + "573766251c45671900574474": "Through experimentation", + "57376828c3c5551400e51eb9": "vector quantities", + "57376828c3c5551400e51eba": "scalar quantities", + "57376828c3c5551400e51ebb": "Associating forces with vectors", + "57376828c3c5551400e51ebc": "ambiguous", + "57376828c3c5551400e51ebd": "impossible", + "57376a1bc3c5551400e51ec3": "static equilibrium", + "57376a1bc3c5551400e51ec4": "magnitude and direction", + "57376a1bc3c5551400e51ec5": "net force", + "57376a1bc3c5551400e51ec6": "their respective lines of application", + "57376a1bc3c5551400e51ec7": "parallelogram rule of vector addition", + "57376c50c3c5551400e51ecd": "independent components", + "57376c50c3c5551400e51ece": "two", + "57376c50c3c5551400e51ecf": "the original force", + "57376c50c3c5551400e51ed0": "orthogonal components", + "57376c50c3c5551400e51ed1": "three-dimensional", + "57376df3c3c5551400e51ed7": "static friction", + "57376df3c3c5551400e51ed8": "static friction", + "57376df3c3c5551400e51ed9": "applied force", + "57376df3c3c5551400e51eda": "applied force", + "57377083c3c5551400e51edf": "force of gravity", + "57377083c3c5551400e51ee0": "spring reaction force", + "57377083c3c5551400e51ee1": "the object's weight", + "57377083c3c5551400e51ee2": "force of gravity", + "57377083c3c5551400e51ee3": "Isaac Newton", + "573776eec3c5551400e51ee9": "Galileo", + "573776eec3c5551400e51eea": "rest", + "573776eec3c5551400e51eeb": "Aristotle", + "573776eec3c5551400e51eec": "behind the foot of the mast of a moving ship", + "573776eec3c5551400e51eed": "behind the foot of the mast of a moving ship", + "57377862c3c5551400e51ef3": "A simple case of dynamic equilibrium", + "57377862c3c5551400e51ef4": "kinetic friction force", + "57377862c3c5551400e51ef5": "kinetic friction", + "57377862c3c5551400e51ef6": "Aristotle", + "57377aac1c45671900574479": "Schr\u00f6dinger equation", + "57377aac1c4567190057447a": "Newtonian equations", + "57377aac1c4567190057447b": "classical position variables", + "57377aac1c4567190057447c": "quantized", + "57377aac1c4567190057447d": "force", + "57377c98c3c5551400e51efb": "spin", + "57377c98c3c5551400e51efc": "Pauli principle", + "57377c98c3c5551400e51efd": "value of the spin", + "57377c98c3c5551400e51efe": "strictly positive", + "57377c98c3c5551400e51eff": "strictly positive", + "57377ec7c3c5551400e51f05": "a mathematical by-product", + "57377ec7c3c5551400e51f06": "force", + "57377ec7c3c5551400e51f07": "conservation of momentum", + "57377ec7c3c5551400e51f08": "Feynman diagrams", + "57377ec7c3c5551400e51f09": "straight line", + "5737804dc3c5551400e51f0f": "four", + "5737804dc3c5551400e51f10": "strong and weak forces", + "5737804dc3c5551400e51f11": "The electromagnetic force", + "5737804dc3c5551400e51f12": "masses", + "5737804dc3c5551400e51f13": "Pauli exclusion principle", + "5737821cc3c5551400e51f19": "Isaac Newton", + "5737821cc3c5551400e51f1a": "20th", + "5737821cc3c5551400e51f1b": "unification models", + "5737821cc3c5551400e51f1c": "self-consistent unification models", + "573784fa1c45671900574483": "Isaac Newton", + "573784fa1c45671900574484": "Isaac Newton. Before Newton, the tendency for objects to fall towards the Earth was not understood to be related to the motions of celestial objects. Galileo", + "573784fa1c45671900574485": "9.81 meters per second squared", + "573784fa1c45671900574486": "from sea level", + "573784fa1c45671900574487": "directly proportional to the object's mass", + "573786b51c4567190057448d": "at larger distances", + "573786b51c4567190057448e": "the same force of gravity", + "573786b51c4567190057448f": "the mass of the attracting body", + "573786b51c45671900574490": "radius", + "57378862c3c5551400e51f21": "a dimensional constant", + "57378862c3c5551400e51f22": "Henry Cavendish", + "57378862c3c5551400e51f23": "1798", + "57378862c3c5551400e51f24": "Newton", + "5737898f1c45671900574495": "Mercury", + "5737898f1c45671900574496": "Vulcan", + "5737898f1c45671900574497": "theory of general relativity", + "5737898f1c45671900574498": "Albert Einstein", + "5737898f1c45671900574499": "Albert Einstein", + "57378b141c4567190057449f": "general relativity", + "57378b141c456719005744a0": "straight line path", + "57378b141c456719005744a1": "gravitational force", + "57378b141c456719005744a2": "global", + "57378c9b1c456719005744a8": "electric current", + "57378c9b1c456719005744a9": "unified electromagnetic force", + "57378c9b1c456719005744a7": "Lorentz's Law", + "57378c9b1c456719005744aa": "the electric field", + "57378e311c456719005744af": "James Clerk Maxwell", + "57378e311c456719005744b0": "1864", + "57378e311c456719005744b1": "20", + "57378e311c456719005744b2": "4", + "57378e311c456719005744b3": "James Clerk Maxwell", + "573792ee1c456719005744b9": "electromagnetic theory", + "573792ee1c456719005744ba": "quantum mechanics", + "573792ee1c456719005744bb": "quantum electrodynamics", + "573792ee1c456719005744bc": "photons", + "573792ee1c456719005744bd": "quantum electrodynamics", + "5737958ac3c5551400e51f29": "Pauli exclusion principle", + "5737958ac3c5551400e51f2a": "Pauli exclusion principle", + "5737958ac3c5551400e51f2b": "energy", + "5737958ac3c5551400e51f2c": "as a structural force", + "5737958b1c456719005744c3": "Pauli exclusion principle", + "5737958b1c456719005744c4": "Pauli exclusion principle", + "5737958b1c456719005744c5": "energy", + "5737958b1c456719005744c6": "as a structural force", + "573796edc3c5551400e51f33": "elementary particles", + "573796edc3c5551400e51f34": "a residual of the force", + "573796edc3c5551400e51f35": "nuclear force", + "573796edc3c5551400e51f36": "gluons", + "573796edc3c5551400e51f37": "color confinement", + "57379829c3c5551400e51f3d": "The weak force", + "57379829c3c5551400e51f3e": "The weak force", + "57379829c3c5551400e51f3f": "neutrons in atomic nuclei", + "57379829c3c5551400e51f40": "1013", + "57379829c3c5551400e51f41": "1015 kelvins", + "57379a4b1c456719005744cd": "The normal force", + "57379a4b1c456719005744ce": "Pauli repulsion", + "57379a4b1c456719005744cf": "fermionic nature of electrons", + "57379a4b1c456719005744d0": "The normal force", + "57379ed81c456719005744d5": "ideal strings", + "57379ed81c456719005744d6": "ideal pulleys", + "57379ed81c456719005744d7": "instantaneously in action-reaction pairs", + "57379ed81c456719005744d8": "conservation of mechanical energy", + "57379ed81c456719005744d9": "connecting the same string multiple times to the same object through the use of a set-up that uses movable pulleys", + "5737a0acc3c5551400e51f47": "idealized point particles", + "5737a0acc3c5551400e51f48": "forces affect idealized point particles", + "5737a0acc3c5551400e51f49": "extended fluids", + "5737a0acc3c5551400e51f4a": "other parts of an object", + "5737a0acc3c5551400e51f4b": "extended structure and forces that act on one part of an object might affect other parts of an object", + "5737a25ac3c5551400e51f51": "The stress tensor", + "5737a25ac3c5551400e51f52": "stress-tensor", + "5737a25ac3c5551400e51f53": "pressure terms", + "5737a25ac3c5551400e51f54": "formalism", + "5737a4511c456719005744df": "angle", + "5737a4511c456719005744e0": "an unbalanced torque", + "5737a4511c456719005744e1": "Newton's Second Law of Motion", + "5737a5931c456719005744e7": "center of the curving path", + "5737a5931c456719005744e8": "perpendicular", + "5737a5931c456719005744e9": "radial (centripetal) force", + "5737a5931c456719005744ea": "radial", + "5737a5931c456719005744eb": "tangential force", + "5737a7351c456719005744f1": "kinetic", + "5737a7351c456719005744f2": "potential", + "5737a7351c456719005744f3": "the net mechanical energy", + "5737a7351c456719005744f4": "the difference in potential energy", + "5737a7351c456719005744f5": "conservative", + "5737a84dc3c5551400e51f59": "forces", + "5737a84dc3c5551400e51f5a": "gradient of potentials", + "5737a84dc3c5551400e51f5b": "friction", + "5737a84dc3c5551400e51f5c": "Nonconservative forces other than friction include other contact forces", + "5737a9afc3c5551400e51f61": "statistical mechanics", + "5737a9afc3c5551400e51f62": "nonconservative forces", + "5737a9afc3c5551400e51f63": "macroscopic closed systems", + "5737a9afc3c5551400e51f64": "Second law of thermodynamics", + "5737a9afc3c5551400e51f65": "nonconservative 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "37 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"37 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "38 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"38 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" -> "39 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"39 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "40 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"39 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "41 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"39 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "44 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"39 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "61 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"40 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "47 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"41 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "42 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"42 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "43 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"43 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "49 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"44 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "45 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"45 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "46 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"46 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "55 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"47 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "48 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"48 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "50 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"49 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "50 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"50 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "51 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"51 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "52 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"52 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "53 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"53 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "54 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"54 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "55 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"55 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "56 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"56 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "57 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"57 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "58 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"58 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "59 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"59 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "60 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"60 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "61 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"61 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "62 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"62 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "63 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"62 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "67 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"63 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "64 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"64 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "65 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"65 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "66 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"66 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "67 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"67 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "69 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "70 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "73 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "90 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"69 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "76 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"70 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "71 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"71 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "72 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"72 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "78 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"73 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "74 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"74 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "75 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"75 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "84 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"76 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "77 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"77 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "79 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"78 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "79 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"79 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "80 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"80 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "81 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"81 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "82 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"82 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "83 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"83 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "84 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"84 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "85 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"85 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "86 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"86 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "87 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"87 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "88 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"88 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "89 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"89 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "90 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"90 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "91 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"91 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "92 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"91 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "96 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"92 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "93 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"93 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "94 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"94 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "95 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"95 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "96 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"96 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "97 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"97 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"97 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "99 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"97 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "102 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"97 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "119 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"98 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "105 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"99 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "100 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"100 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "101 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"101 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "107 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"102 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "103 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"103 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "104 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"104 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "113 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"105 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "106 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"106 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "108 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"107 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "108 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"108 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "109 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"109 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "110 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"110 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "111 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"111 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "112 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"112 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "113 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"113 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "114 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"114 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "115 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"115 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "116 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"116 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "117 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"117 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "118 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"118 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "119 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"119 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "120 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"120 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "121 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"120 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "125 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"121 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "122 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"122 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "123 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"123 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "124 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"124 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "125 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"125 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "127 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "128 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "131 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "148 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"127 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "134 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"128 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "129 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"129 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "130 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"130 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "136 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"131 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "132 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"132 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "133 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"133 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "142 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"134 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "135 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"135 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "137 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"136 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "137 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"137 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "138 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"138 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "139 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"139 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "140 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"140 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "141 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"141 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "142 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"142 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "143 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"143 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "144 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"144 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "145 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"145 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "146 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"146 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "147 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"147 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "148 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"150 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "151 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"151 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "152 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"152 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "153 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"153 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "154 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"154 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "156 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "157 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "160 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"156 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "163 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"157 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "158 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"158 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "159 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"159 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "165 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"160 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "161 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"161 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "162 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"162 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "171 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"163 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "164 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"164 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "166 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"165 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "166 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"166 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "167 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"167 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "168 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"168 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "169 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"169 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "170 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"170 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "171 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"171 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "172 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"172 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "173 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"173 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "174 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"174 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "175 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"175 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "176 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"176 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "177 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"179 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "180 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"180 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "181 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"181 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "182 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"182 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "183 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"183 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "184 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"184 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"184 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "186 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"184 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "189 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"184 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "206 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"185 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "192 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"186 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "187 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"187 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "188 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"188 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "194 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"189 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "190 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"190 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "191 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"191 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "200 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"192 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "193 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"193 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "195 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"194 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "195 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"195 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "196 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"196 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "197 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"197 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "198 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"198 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "199 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"199 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "200 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"200 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "201 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"201 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "202 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"202 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "203 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"203 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "204 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"204 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "205 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"205 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "206 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"208 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"209 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "210 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"210 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "211 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"211 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "212 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"212 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "213 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"213 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"213 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "215 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"213 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"213 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "235 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"214 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "221 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"215 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "216 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"216 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "217 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"217 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "223 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"218 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "219 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"219 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "220 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"220 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "229 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"221 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "222 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"222 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "224 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"223 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "224 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"224 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "225 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"225 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "226 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"226 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "227 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"227 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "228 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"228 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "229 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"229 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "230 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"230 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "231 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"231 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "232 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"232 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "233 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"233 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "234 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"234 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "235 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"237 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "238 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"238 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "239 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"239 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "240 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"240 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "241 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"241 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "242 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"242 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "243 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"242 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "244 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"242 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "247 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"242 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "264 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"243 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "250 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"244 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "245 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"245 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "246 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"246 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "252 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"247 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "248 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"248 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "249 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"249 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "258 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"250 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "251 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"251 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "253 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"252 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "253 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"253 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "254 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"254 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "255 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"255 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "256 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"256 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "257 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"257 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "258 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"258 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "259 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"259 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "260 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"260 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "261 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"261 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "262 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"262 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "263 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"263 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "264 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"266 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "267 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"267 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "268 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"268 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "269 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"269 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "270 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"270 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "271 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"271 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "274 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"274 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "275 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"275 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "281 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"276 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "277 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"277 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "278 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"278 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"281 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "282 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"282 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "283 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"283 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "284 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"284 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "285 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"285 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "286 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"286 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "287 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"287 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "288 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"288 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "289 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"289 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "290 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"290 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "291 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"291 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "292 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"292 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "293 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "301 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "302 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "305 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "322 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"301 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "308 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"302 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "303 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"303 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "304 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"304 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "310 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"305 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "306 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"306 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "307 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"307 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "316 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"308 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "309 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"309 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "311 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"310 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "311 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"311 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "312 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"312 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "313 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"313 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "314 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"314 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "315 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"315 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "316 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"316 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "317 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"317 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "318 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"318 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "319 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"319 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "320 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"320 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "321 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"321 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "322 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"322 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "323 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"323 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "324 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"323 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "328 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"324 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "325 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"325 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "326 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"326 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "327 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"327 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "328 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"328 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" -> "329 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"329 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "330 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"329 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "331 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"329 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "334 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"329 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "351 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"330 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "337 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"331 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "332 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"332 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "333 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"333 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "339 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"334 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "335 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"335 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "336 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"336 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "345 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"337 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "338 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"338 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "340 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"339 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "340 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"340 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "341 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"341 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "342 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"342 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "343 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"343 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "344 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"344 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "345 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"345 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "346 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"346 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "347 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"347 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "348 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"348 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "349 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"349 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "350 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"350 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "351 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"351 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "352 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"352 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "353 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"352 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "357 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"353 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "354 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"354 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "355 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"355 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "356 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"356 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "357 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"357 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/__add___0" -> "358 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"358 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "359 BertForQuestionAnswering/NNCFLinear[qa_outputs]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"359 BertForQuestionAnswering/NNCFLinear[qa_outputs]/linear_0" -> "360 BertForQuestionAnswering/split_0" [label="(1, 384, 2) \n0 -> 0", style=solid]; +"360 BertForQuestionAnswering/split_0" -> "361 BertForQuestionAnswering/squeeze_0" [label="(1, 384, 1) \n0 -> 0", style=solid]; +"360 BertForQuestionAnswering/split_0" -> "363 BertForQuestionAnswering/squeeze_1" [label="(1, 384, 1) \n1 -> 0", style=solid]; +"361 BertForQuestionAnswering/squeeze_0" -> "362 BertForQuestionAnswering/contiguous_0" [label="(1, 384) \n0 -> 0", style=solid]; +"362 BertForQuestionAnswering/contiguous_0" -> "366 /nncf_model_output_1" [label="(1, 384) \n0 -> 0", style=solid]; +"363 BertForQuestionAnswering/squeeze_1" -> "364 BertForQuestionAnswering/contiguous_1" [label="(1, 384) \n0 -> 0", style=solid]; +"364 BertForQuestionAnswering/contiguous_1" -> "365 /nncf_model_output_0" [label="(1, 384) \n0 -> 0", style=solid]; +} diff --git a/eftnas-s1-bert-base-squadv1/original_graph.png b/eftnas-s1-bert-base-squadv1/original_graph.png new file mode 100644 index 0000000000000000000000000000000000000000..ee458a79bf05ca2f9c0c401e2be551323f381bf3 --- /dev/null +++ b/eftnas-s1-bert-base-squadv1/original_graph.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3c0f930cc769ebbca358394bfb35380ad091151fc092779b96be34410a63ca51 +size 8905770 diff --git a/eftnas-s1-bert-base-squadv1/pytorch_model.bin b/eftnas-s1-bert-base-squadv1/pytorch_model.bin new file mode 100644 index 0000000000000000000000000000000000000000..a8fa5c90ad9f57b76578a79276b8b7517badbed7 --- /dev/null +++ b/eftnas-s1-bert-base-squadv1/pytorch_model.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:22e7d0855a4cbbd145c46a50241c4cb5565429dee9760213d7e5833baf7f16fb +size 435643185 diff --git a/eftnas-s1-bert-base-squadv1/search_progression.csv b/eftnas-s1-bert-base-squadv1/search_progression.csv new file mode 100644 index 0000000000000000000000000000000000000000..fe1c9369366548fbd96bbf3f63d472bd3f7aac30 --- /dev/null +++ b/eftnas-s1-bert-base-squadv1/search_progression.csv @@ -0,0 +1,1000 @@ +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 768, 4: 768, 5: 384, 6: 448, 7: 768, 8: 512, 9: 384, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1284, 15: 1218, 16: 2804, 17: 2017, 18: 3072, 19: 976, 20: 794, 21: 964, 22: 3072, 23: 3072})])",MACs,25278.676992,top1_acc,-88.57264456877431 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2830, 13: 3072, 14: 2189, 15: 1218, 16: 2804, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 3072, 23: 3072})])",MACs,28272.623616,top1_acc,-89.0826425380652 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 320, 12: 1169, 13: 1170, 14: 2876, 15: 2825, 16: 1205, 17: 2760, 18: 1030, 19: 976, 20: 1559, 21: 401, 22: 785, 23: 617})])",MACs,20817.248256,top1_acc,-88.27421929632483 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 512, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 3072, 19: 1809, 20: 1559, 21: 3072, 22: 785, 23: 1030})])",MACs,25447.95648,top1_acc,-88.97105296916327 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 512, 5: 768, 6: 768, 7: 768, 8: 512, 9: 384, 10: 768, 11: 320, 12: 2096, 13: 2815, 14: 3072, 15: 3072, 16: 3072, 17: 2017, 18: 3072, 19: 3072, 20: 2441, 21: 1950, 22: 3072, 23: 3072})])",MACs,29363.798016,top1_acc,-89.07771178128809 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 3072, 14: 2876, 15: 3072, 16: 2804, 17: 1130, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 422})])",MACs,23955.70176,top1_acc,-88.57186651615298 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,24615.714816,top1_acc,-89.04880845607887 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 768, 4: 512, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2830, 13: 1170, 14: 3072, 15: 2144, 16: 3072, 17: 2017, 18: 2651, 19: 2628, 20: 2441, 21: 401, 22: 3072, 23: 422})])",MACs,26424.705024,top1_acc,-88.88505704451576 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 512, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 2830, 13: 1170, 14: 2189, 15: 3072, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 2441, 21: 3072, 22: 3072, 23: 3072})])",MACs,27758.886912,top1_acc,-88.58010554766717 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 512, 5: 512, 6: 448, 7: 768, 8: 512, 9: 768, 10: 256, 11: 320, 12: 2830, 13: 1170, 14: 3072, 15: 3072, 16: 2115, 17: 1130, 18: 1869, 19: 2628, 20: 794, 21: 1950, 22: 785, 23: 3072})])",MACs,23880.794112,top1_acc,-88.57347906990873 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 256, 11: 768, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 2804, 17: 2017, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 617})])",MACs,21313.29024,top1_acc,-88.68728536767925 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 384, 10: 768, 11: 768, 12: 1169, 13: 3072, 14: 2876, 15: 2144, 16: 2115, 17: 1130, 18: 1030, 19: 3072, 20: 3072, 21: 3072, 22: 1554, 23: 422})])",MACs,25910.378496,top1_acc,-88.68626376290112 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 3072, 22: 785, 23: 3072})])",MACs,27284.078592,top1_acc,-89.20576050926228 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 512, 6: 448, 7: 768, 8: 512, 9: 384, 10: 256, 11: 768, 12: 2830, 13: 2815, 14: 2876, 15: 2144, 16: 1205, 17: 2760, 18: 1869, 19: 1809, 20: 2441, 21: 964, 22: 3072, 23: 422})])",MACs,24305.467392,top1_acc,-88.73591281774199 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 768, 8: 512, 9: 768, 10: 768, 11: 320, 12: 1169, 13: 3072, 14: 2876, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 976, 20: 3072, 21: 1950, 22: 3072, 23: 1030})])",MACs,25410.797568,top1_acc,-88.59123529473989 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 512, 4: 512, 5: 768, 6: 448, 7: 768, 8: 512, 9: 768, 10: 768, 11: 768, 12: 2830, 13: 1170, 14: 2876, 15: 2144, 16: 1205, 17: 2017, 18: 1030, 19: 2628, 20: 3072, 21: 964, 22: 1554, 23: 617})])",MACs,25025.052672,top1_acc,-88.60478782736891 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 512, 5: 384, 6: 448, 7: 768, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 2876, 15: 1218, 16: 2804, 17: 2017, 18: 1030, 19: 976, 20: 1559, 21: 3072, 22: 1554, 23: 3072})])",MACs,22152.609792,top1_acc,-88.36709635744364 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 3072, 18: 3072, 19: 2628, 20: 2441, 21: 401, 22: 3072, 23: 617})])",MACs,22849.78176,top1_acc,-88.56246050929539 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2096, 13: 1170, 14: 2876, 15: 3072, 16: 1205, 17: 2017, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 1554, 23: 422})])",MACs,22239.31392,top1_acc,-88.71639714550975 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 2096, 13: 3072, 14: 2189, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 3072, 22: 3072, 23: 617})])",MACs,27276.41088,top1_acc,-88.98224189615576 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 2099, 14: 3072, 15: 2144, 16: 2115, 17: 1130, 18: 1869, 19: 3072, 20: 2441, 21: 3072, 22: 785, 23: 422})])",MACs,23988.731904,top1_acc,-88.87653133167814 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 2830, 13: 2815, 14: 2189, 15: 2144, 16: 2115, 17: 2017, 18: 3072, 19: 1809, 20: 1559, 21: 1950, 22: 3072, 23: 422})])",MACs,24958.40256,top1_acc,-88.58325046777628 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 1030, 19: 1809, 20: 2441, 21: 3072, 22: 1554, 23: 1030})])",MACs,26609.319936,top1_acc,-89.06107009391293 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 976, 20: 1559, 21: 1950, 22: 785, 23: 617})])",MACs,22131.965952,top1_acc,-88.78831329199382 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 768, 7: 768, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2815, 14: 1284, 15: 2144, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 2441, 21: 3072, 22: 3072, 23: 422})])",MACs,24524.88192,top1_acc,-88.89979047547355 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 384, 10: 192, 11: 768, 12: 3072, 13: 1170, 14: 2876, 15: 2825, 16: 2115, 17: 2017, 18: 3072, 19: 1809, 20: 794, 21: 1950, 22: 3072, 23: 617})])",MACs,26111.50848,top1_acc,-88.94442736444485 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 448, 4: 512, 5: 384, 6: 768, 7: 768, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 3072, 16: 1205, 17: 3072, 18: 3072, 19: 1809, 20: 2441, 21: 964, 22: 1554, 23: 617})])",MACs,21605.25312,top1_acc,-88.35818927851983 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 512, 4: 640, 5: 384, 6: 448, 7: 768, 8: 512, 9: 768, 10: 256, 11: 320, 12: 3072, 13: 3072, 14: 3072, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 3072, 20: 794, 21: 401, 22: 1554, 23: 617})])",MACs,23023.190016,top1_acc,-88.69163600895247 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 768, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1284, 15: 2825, 16: 2115, 17: 2760, 18: 2651, 19: 976, 20: 1559, 21: 1950, 22: 404, 23: 617})])",MACs,23738.056704,top1_acc,-88.62384813783301 +"OrderedDict([(, {0: 768, 1: 768, 2: 512, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 2189, 15: 2144, 16: 3072, 17: 2017, 18: 1030, 19: 2628, 20: 3072, 21: 401, 22: 3072, 23: 3072})])",MACs,26675.970048,top1_acc,-88.78189607509887 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2815, 14: 3072, 15: 2825, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 422})])",MACs,27386.118144,top1_acc,-89.246105874051 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 384, 6: 448, 7: 768, 8: 512, 9: 384, 10: 192, 11: 768, 12: 2830, 13: 2815, 14: 1284, 15: 2825, 16: 3072, 17: 3072, 18: 2651, 19: 976, 20: 794, 21: 1950, 22: 1554, 23: 617})])",MACs,24324.931584,top1_acc,-88.79910295411715 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 768, 12: 3072, 13: 3072, 14: 1284, 15: 3072, 16: 1205, 17: 3072, 18: 2651, 19: 976, 20: 2441, 21: 964, 22: 785, 23: 3072})])",MACs,25142.427648,top1_acc,-88.52803623790612 +"OrderedDict([(, {0: 768, 1: 768, 2: 512, 3: 768, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 384, 10: 256, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 1809, 20: 2441, 21: 1950, 22: 404, 23: 3072})])",MACs,25051.004928,top1_acc,-88.57334372750387 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 3072, 14: 3072, 15: 2825, 16: 3072, 17: 3072, 18: 1869, 19: 976, 20: 2441, 21: 401, 22: 1554, 23: 1030})])",MACs,26825.785344,top1_acc,-89.01997856699211 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 2876, 15: 1218, 16: 3072, 17: 2017, 18: 2651, 19: 1809, 20: 3072, 21: 964, 22: 785, 23: 1030})])",MACs,22749.51168,top1_acc,-88.7390312338568 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 768, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2830, 13: 3072, 14: 1284, 15: 2825, 16: 2115, 17: 3072, 18: 2651, 19: 1809, 20: 1559, 21: 3072, 22: 3072, 23: 617})])",MACs,25656.754176,top1_acc,-88.79264815037041 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 2628, 20: 1559, 21: 964, 22: 785, 23: 1030})])",MACs,21396.455424,top1_acc,-88.29372175179238 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 384, 6: 768, 7: 768, 8: 512, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 2815, 14: 2189, 15: 2144, 16: 2804, 17: 2760, 18: 1030, 19: 976, 20: 1559, 21: 1950, 22: 3072, 23: 3072})])",MACs,26379.288576,top1_acc,-88.67379320085533 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2099, 14: 2876, 15: 3072, 16: 1205, 17: 2017, 18: 2651, 19: 2628, 20: 3072, 21: 401, 22: 785, 23: 422})])",MACs,25563.561984,top1_acc,-88.84018731902927 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 768, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 2876, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 1809, 20: 3072, 21: 964, 22: 785, 23: 1030})])",MACs,24131.469312,top1_acc,-89.05081680494318 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 768, 6: 448, 7: 768, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 3072, 14: 3072, 15: 3072, 16: 2804, 17: 1130, 18: 2651, 19: 2628, 20: 1559, 21: 1950, 22: 785, 23: 422})])",MACs,25607.798784,top1_acc,-88.69044533032834 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 3072, 14: 1284, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 2441, 21: 401, 22: 3072, 23: 3072})])",MACs,28032.565248,top1_acc,-88.83585450156292 +"OrderedDict([(, {0: 768, 1: 768, 2: 512, 3: 448, 4: 640, 5: 384, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2144, 16: 2804, 17: 2017, 18: 1030, 19: 2628, 20: 3072, 21: 401, 22: 3072, 23: 3072})])",MACs,27133.083648,top1_acc,-88.85276887192865 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 384, 10: 768, 11: 320, 12: 2096, 13: 1170, 14: 3072, 15: 3072, 16: 3072, 17: 2017, 18: 1030, 19: 3072, 20: 2441, 21: 1950, 22: 3072, 23: 3072})])",MACs,27755.347968,top1_acc,-88.76477255270174 +"OrderedDict([(, {0: 768, 1: 768, 2: 512, 3: 448, 4: 640, 5: 512, 6: 768, 7: 768, 8: 512, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2099, 14: 2876, 15: 3072, 16: 1205, 17: 2017, 18: 2651, 19: 1809, 20: 2441, 21: 964, 22: 785, 23: 422})])",MACs,25606.619136,top1_acc,-88.850488719145 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 2628, 20: 3072, 21: 1950, 22: 785, 23: 617})])",MACs,23764.00896,top1_acc,-88.68354079777983 +"OrderedDict([(, {0: 768, 1: 768, 2: 512, 3: 768, 4: 768, 5: 384, 6: 448, 7: 768, 8: 512, 9: 384, 10: 192, 11: 768, 12: 2830, 13: 3072, 14: 1284, 15: 2825, 16: 2115, 17: 3072, 18: 2651, 19: 976, 20: 794, 21: 1950, 22: 1554, 23: 617})])",MACs,24383.913984,top1_acc,-88.71564425303812 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2815, 14: 3072, 15: 3072, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 422})])",MACs,28098.035712,top1_acc,-89.26840726370226 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 448, 4: 512, 5: 384, 6: 448, 7: 768, 8: 512, 9: 384, 10: 256, 11: 320, 12: 3072, 13: 1170, 14: 2876, 15: 1218, 16: 2804, 17: 2017, 18: 1030, 19: 2628, 20: 1559, 21: 3072, 22: 785, 23: 3072})])",MACs,24267.718656,top1_acc,-88.53066316324366 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 512, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2815, 14: 3072, 15: 2825, 16: 2804, 17: 2760, 18: 3072, 19: 1809, 20: 1559, 21: 3072, 22: 3072, 23: 1030})])",MACs,28634.185728,top1_acc,-89.10009160991486 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2830, 13: 3072, 14: 1284, 15: 3072, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 1559, 21: 1950, 22: 785, 23: 617})])",MACs,23713.284096,top1_acc,-88.75377278953785 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 1869, 19: 976, 20: 2441, 21: 1950, 22: 785, 23: 3072})])",MACs,24665.849856,top1_acc,-88.85579459055627 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 768, 4: 512, 5: 768, 6: 768, 7: 768, 8: 512, 9: 384, 10: 768, 11: 320, 12: 2096, 13: 2815, 14: 3072, 15: 3072, 16: 3072, 17: 2017, 18: 3072, 19: 2628, 20: 2441, 21: 1950, 22: 3072, 23: 422})])",MACs,28010.74176,top1_acc,-89.02601795961455 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2099, 14: 2876, 15: 2825, 16: 2115, 17: 3072, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 785, 23: 422})])",MACs,27202.68288,top1_acc,-89.23329317996664 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 320, 12: 1169, 13: 3072, 14: 2876, 15: 1218, 16: 2115, 17: 2017, 18: 2651, 19: 1809, 20: 3072, 21: 1950, 22: 3072, 23: 1030})])",MACs,24331.419648,top1_acc,-88.41987708345364 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 512, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 2096, 13: 1170, 14: 2876, 15: 2144, 16: 1205, 17: 2017, 18: 1030, 19: 2628, 20: 3072, 21: 964, 22: 1554, 23: 617})])",MACs,24120.262656,top1_acc,-88.55408339392122 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1284, 15: 2825, 16: 2115, 17: 2017, 18: 2651, 19: 976, 20: 1559, 21: 1950, 22: 404, 23: 617})])",MACs,22356.099072,top1_acc,-88.65029127408013 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 2830, 13: 1170, 14: 2876, 15: 3072, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 964, 22: 785, 23: 3072})])",MACs,22228.697088,top1_acc,-88.56012642045998 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 768, 9: 384, 10: 768, 11: 768, 12: 1169, 13: 1170, 14: 2189, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 3072, 23: 617})])",MACs,23089.840128,top1_acc,-88.85383836042921 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2815, 14: 2189, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 422})])",MACs,26929.004544,top1_acc,-89.0964704978324 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 768, 4: 512, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 256, 11: 768, 12: 1169, 13: 2815, 14: 3072, 15: 1218, 16: 2804, 17: 2017, 18: 3072, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 617})])",MACs,22921.740288,top1_acc,-88.82256251818362 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 768, 12: 2830, 13: 2815, 14: 2876, 15: 2144, 16: 1205, 17: 2760, 18: 1869, 19: 2628, 20: 3072, 21: 401, 22: 3072, 23: 422})])",MACs,24262.41024,top1_acc,-88.69034320545197 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 976, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,22983.671808,top1_acc,-88.84141189502586 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 512, 4: 640, 5: 384, 6: 448, 7: 768, 8: 512, 9: 768, 10: 256, 11: 320, 12: 3072, 13: 2815, 14: 3072, 15: 1218, 16: 3072, 17: 2017, 18: 1869, 19: 3072, 20: 794, 21: 401, 22: 1554, 23: 617})])",MACs,22964.207616,top1_acc,-88.68170992715763 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 3072, 14: 2876, 15: 2825, 16: 2804, 17: 1130, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 422})])",MACs,23243.784192,top1_acc,-88.56947570316086 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 976, 20: 1559, 21: 964, 22: 1554, 23: 1030})])",MACs,19753.20576,top1_acc,-88.03202125779471 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 2099, 14: 2189, 15: 2144, 16: 1205, 17: 2760, 18: 1030, 19: 976, 20: 1559, 21: 1950, 22: 785, 23: 3072})])",MACs,23193.059328,top1_acc,-88.48204831687082 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 768, 4: 640, 5: 512, 6: 448, 7: 768, 8: 512, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1170, 14: 3072, 15: 2825, 16: 2115, 17: 1130, 18: 1869, 19: 976, 20: 794, 21: 1950, 22: 404, 23: 3072})])",MACs,23905.56672,top1_acc,-88.34182662617134 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2830, 13: 3072, 14: 2189, 15: 1218, 16: 1205, 17: 2017, 18: 1869, 19: 2628, 20: 1559, 21: 401, 22: 3072, 23: 617})])",MACs,25738.739712,top1_acc,-89.04652639354788 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2830, 13: 1170, 14: 3072, 15: 2144, 16: 3072, 17: 2017, 18: 2651, 19: 3072, 20: 2441, 21: 401, 22: 3072, 23: 3072})])",MACs,27777.76128,top1_acc,-88.6976898074125 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 2144, 16: 1205, 17: 2017, 18: 2651, 19: 2628, 20: 2441, 21: 401, 22: 3072, 23: 617})])",MACs,21611.15136,top1_acc,-88.30562491057086 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 448, 4: 768, 5: 768, 6: 448, 7: 768, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 2876, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 976, 20: 3072, 21: 964, 22: 785, 23: 1030})])",MACs,23828.8896,top1_acc,-88.82487054893764 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 448, 4: 512, 5: 768, 6: 448, 7: 768, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2830, 13: 1170, 14: 2876, 15: 3072, 16: 1205, 17: 2017, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 1554, 23: 422})])",MACs,23144.103936,top1_acc,-88.80338672535578 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 3072, 14: 2876, 15: 3072, 16: 2804, 17: 1130, 18: 2651, 19: 2628, 20: 1559, 21: 964, 22: 785, 23: 422})])",MACs,23920.902144,top1_acc,-88.69540110655501 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 512, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 1809, 20: 1559, 21: 3072, 22: 785, 23: 1030})])",MACs,26834.04288,top1_acc,-89.1238672196353 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,24650.514432,top1_acc,-89.02795304002774 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 3072, 14: 2189, 15: 1218, 16: 1205, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 3072, 22: 3072, 23: 617})])",MACs,25890.32448,top1_acc,-88.7438931398996 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 768, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1284, 15: 3072, 16: 2804, 17: 2760, 18: 2651, 19: 976, 20: 1559, 21: 1950, 22: 404, 23: 617})])",MACs,24290.131968,top1_acc,-88.73430703950977 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 3072, 14: 2876, 15: 2825, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 422})])",MACs,23403.626496,top1_acc,-88.68321276409482 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 3072, 23: 617})])",MACs,26189.365248,top1_acc,-89.11066716194549 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 768, 5: 384, 6: 448, 7: 768, 8: 512, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 2815, 14: 1284, 15: 2825, 16: 3072, 17: 2017, 18: 2651, 19: 976, 20: 1559, 21: 1950, 22: 1554, 23: 617})])",MACs,23174.18496,top1_acc,-88.62606368994999 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 448, 7: 768, 8: 768, 9: 384, 10: 256, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 2804, 17: 3072, 18: 1030, 19: 1809, 20: 2441, 21: 3072, 22: 1554, 23: 1030})])",MACs,25640.828928,top1_acc,-89.03962501895629 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 512, 5: 768, 6: 768, 7: 768, 8: 512, 9: 768, 10: 768, 11: 320, 12: 2096, 13: 2815, 14: 2189, 15: 3072, 16: 3072, 17: 2017, 18: 3072, 19: 3072, 20: 2441, 21: 1950, 22: 3072, 23: 3072})])",MACs,29409.214464,top1_acc,-89.1187985870761 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 2876, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 1809, 20: 3072, 21: 964, 22: 785, 23: 1030})])",MACs,23093.379072,top1_acc,-88.91123816371112 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 2628, 20: 1559, 21: 964, 22: 3072, 23: 1030})])",MACs,21622.94784,top1_acc,-88.20831243294633 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2815, 14: 2189, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 3072, 22: 785, 23: 1030})])",MACs,29534.257152,top1_acc,-89.29344079144903 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1284, 15: 2825, 16: 2115, 17: 2017, 18: 2651, 19: 976, 20: 1559, 21: 1950, 22: 785, 23: 3072})])",MACs,24500.699136,top1_acc,-88.7343719285345 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 448, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 2876, 15: 1218, 16: 3072, 17: 3072, 18: 3072, 19: 976, 20: 3072, 21: 964, 22: 785, 23: 1030})])",MACs,25299.320832,top1_acc,-88.89332246319115 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 1130, 18: 1869, 19: 3072, 20: 2441, 21: 3072, 22: 785, 23: 1030})])",MACs,24749.01504,top1_acc,-88.97326424930802 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 2115, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 785, 23: 422})])",MACs,25815.416832,top1_acc,-89.06753125446419 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 2144, 16: 2115, 17: 3072, 18: 3072, 19: 2628, 20: 2441, 21: 401, 22: 3072, 23: 617})])",MACs,23395.958784,top1_acc,-88.58194108273295 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 976, 20: 1559, 21: 964, 22: 1554, 23: 1030})])",MACs,19375.7184,top1_acc,-88.03903523417102 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2815, 14: 2189, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 617})])",MACs,28424.798208,top1_acc,-89.15150626948025 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 3072, 13: 3072, 14: 1284, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 976, 20: 1559, 21: 1950, 22: 3072, 23: 617})])",MACs,24616.30464,top1_acc,-88.66860840973062 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 1169, 13: 3072, 14: 2876, 15: 2825, 16: 1205, 17: 2760, 18: 1869, 19: 976, 20: 1559, 21: 401, 22: 3072, 23: 617})])",MACs,25009.717248,top1_acc,-88.76031371958076 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 512, 9: 384, 10: 768, 11: 320, 12: 2096, 13: 2815, 14: 1284, 15: 3072, 16: 3072, 17: 2760, 18: 1869, 19: 1809, 20: 2441, 21: 3072, 22: 3072, 23: 3072})])",MACs,28426.56768,top1_acc,-89.145148229923 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 768, 9: 384, 10: 768, 11: 768, 12: 1169, 13: 1170, 14: 2189, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 404, 23: 617})])",MACs,21516.189696,top1_acc,-88.72988972101616 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 512, 5: 384, 6: 448, 7: 768, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2830, 13: 1170, 14: 2876, 15: 1218, 16: 2804, 17: 3072, 18: 1030, 19: 976, 20: 794, 21: 3072, 22: 1554, 23: 3072})])",MACs,23303.356416,top1_acc,-88.50873324085171 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 768, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 3072, 15: 3072, 16: 3072, 17: 2017, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 617})])",MACs,22281.781248,top1_acc,-88.8194233002941 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 384, 10: 768, 11: 768, 12: 2830, 13: 3072, 14: 3072, 15: 1218, 16: 2804, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 3072, 23: 3072})])",MACs,28227.207168,top1_acc,-89.07528623713037 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 512, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2017, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,24306.64704,top1_acc,-88.91339285738253 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 3072, 13: 1170, 14: 1284, 15: 2144, 16: 1205, 17: 2017, 18: 2651, 19: 2628, 20: 2441, 21: 401, 22: 785, 23: 617})])",MACs,21384.658944,top1_acc,-88.42374714257474 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 422})])",MACs,22842.703872,top1_acc,-88.94275016464616 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 3072, 22: 404, 23: 617})])",MACs,25139.478528,top1_acc,-89.13284132319038 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 2441, 21: 401, 22: 3072, 23: 617})])",MACs,21379.350528,top1_acc,-88.48265051447989 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 512, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 3072, 15: 2144, 16: 1205, 17: 2760, 18: 3072, 19: 1809, 20: 1559, 21: 3072, 22: 785, 23: 422})])",MACs,24687.673344,top1_acc,-88.95583981152008 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 2876, 15: 2825, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 3072, 21: 3072, 22: 785, 23: 3072})])",MACs,28671.34464,top1_acc,-89.13567744913092 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 2651, 19: 2628, 20: 2441, 21: 401, 22: 3072, 23: 617})])",MACs,21064.974336,top1_acc,-88.23077694732218 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 448, 4: 512, 5: 384, 6: 768, 7: 768, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 3072, 16: 1205, 17: 3072, 18: 3072, 19: 1809, 20: 2441, 21: 964, 22: 1554, 23: 617})])",MACs,21982.74048,top1_acc,-88.5187239081718 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 422})])",MACs,23119.921152,top1_acc,-88.85730051224624 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 512, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2815, 14: 3072, 15: 2825, 16: 2804, 17: 2017, 18: 2651, 19: 1809, 20: 1559, 21: 3072, 22: 404, 23: 1030})])",MACs,26373.98016,top1_acc,-88.99690862515608 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 2830, 13: 1170, 14: 2189, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 2628, 20: 1559, 21: 401, 22: 785, 23: 617})])",MACs,21546.27072,top1_acc,-88.57811185748665 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 768, 7: 768, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2815, 14: 3072, 15: 2144, 16: 2115, 17: 2017, 18: 3072, 19: 3072, 20: 2441, 21: 1950, 22: 3072, 23: 422})])",MACs,25462.112256,top1_acc,-88.74340562259952 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 640, 5: 512, 6: 768, 7: 768, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 3072, 16: 1205, 17: 3072, 18: 3072, 19: 1809, 20: 2441, 21: 964, 22: 1554, 23: 617})])",MACs,22906.994688,top1_acc,-88.80646739521335 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 2876, 15: 1218, 16: 1205, 17: 2760, 18: 1869, 19: 976, 20: 3072, 21: 1950, 22: 785, 23: 617})])",MACs,24264.179712,top1_acc,-88.8010059983308 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 768, 7: 768, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2815, 14: 1284, 15: 2144, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 2441, 21: 3072, 22: 3072, 23: 422})])",MACs,23223.140352,top1_acc,-88.53431167672106 +"OrderedDict([(, {0: 768, 1: 768, 2: 512, 3: 768, 4: 512, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 1130, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 1030})])",MACs,21999.255552,top1_acc,-88.7624360764536 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 512, 4: 640, 5: 512, 6: 768, 7: 768, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2815, 14: 1284, 15: 2144, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 1559, 21: 3072, 22: 3072, 23: 422})])",MACs,25231.491072,top1_acc,-88.95615936491869 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 448, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2815, 14: 3072, 15: 2825, 16: 2804, 17: 2760, 18: 3072, 19: 1809, 20: 2441, 21: 3072, 22: 3072, 23: 1030})])",MACs,27927.576576,top1_acc,-89.06073111164196 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 976, 20: 1559, 21: 964, 22: 1554, 23: 1030})])",MACs,21519.72864,top1_acc,-88.33286062636387 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 448, 4: 640, 5: 384, 6: 768, 7: 768, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 3072, 16: 1205, 17: 3072, 18: 3072, 19: 1809, 20: 2441, 21: 964, 22: 1554, 23: 617})])",MACs,22171.48416,top1_acc,-88.63518249724416 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 1554, 23: 422})])",MACs,23862.509568,top1_acc,-89.00634605173444 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25936.920576,top1_acc,-89.28286543001755 +"OrderedDict([(, {0: 768, 1: 768, 2: 512, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 3072, 13: 1170, 14: 2876, 15: 2825, 16: 1205, 17: 2017, 18: 2651, 19: 2628, 20: 2441, 21: 401, 22: 785, 23: 617})])",MACs,22819.700736,top1_acc,-88.54841243233835 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 2189, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 976, 20: 1559, 21: 1950, 22: 785, 23: 617})])",MACs,26441.80992,top1_acc,-88.87847258367972 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 768, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 3072, 17: 2017, 18: 2651, 19: 2628, 20: 2441, 21: 401, 22: 785, 23: 1030})])",MACs,22645.702656,top1_acc,-88.5947110902485 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 976, 20: 1559, 21: 964, 22: 3072, 23: 1030})])",MACs,19911.278592,top1_acc,-87.92119332635868 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27778.351104,top1_acc,-89.46927301395344 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2099, 14: 2876, 15: 2825, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 785, 23: 422})])",MACs,28175.302656,top1_acc,-89.24475413776989 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 1170, 14: 2876, 15: 3072, 16: 3072, 17: 2017, 18: 1869, 19: 2628, 20: 3072, 21: 964, 22: 1554, 23: 617})])",MACs,27971.813376,top1_acc,-89.07771653455484 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 2189, 15: 2825, 16: 2115, 17: 2017, 18: 2651, 19: 976, 20: 1559, 21: 1950, 22: 785, 23: 617})])",MACs,24152.702976,top1_acc,-88.81499845089647 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 448, 4: 640, 5: 384, 6: 768, 7: 768, 8: 768, 9: 384, 10: 192, 11: 320, 12: 3072, 13: 1170, 14: 2876, 15: 3072, 16: 1205, 17: 3072, 18: 3072, 19: 1809, 20: 2441, 21: 964, 22: 1554, 23: 617})])",MACs,24232.91904,top1_acc,-88.89225727384073 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 512, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 1809, 20: 1559, 21: 3072, 22: 785, 23: 1030})])",MACs,27738.832896,top1_acc,-89.07159381026136 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 2628, 20: 2441, 21: 401, 22: 3072, 23: 617})])",MACs,20919.287808,top1_acc,-88.30904679533334 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 768, 11: 768, 12: 3072, 13: 2815, 14: 2189, 15: 2825, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 422})])",MACs,25703.940096,top1_acc,-88.93451409877666 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 976, 20: 1559, 21: 964, 22: 1554, 23: 1030})])",MACs,21540.37248,top1_acc,-88.56343322403916 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2815, 14: 2189, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 1030})])",MACs,27535.93344,top1_acc,-89.1996490843606 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,24898.830336,top1_acc,-89.1755644086907 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 768, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 617})])",MACs,19169.28,top1_acc,-88.04254705086062 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 422})])",MACs,22931.177472,top1_acc,-88.81889743822026 +"OrderedDict([(, {0: 768, 1: 768, 2: 512, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2096, 13: 1170, 14: 2876, 15: 3072, 16: 1205, 17: 2017, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 785, 23: 422})])",MACs,21219.508224,top1_acc,-88.58877902149293 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 3072, 22: 404, 23: 617})])",MACs,23818.272768,top1_acc,-88.96382413471387 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 2144, 16: 1205, 17: 2760, 18: 1030, 19: 976, 20: 1559, 21: 401, 22: 785, 23: 617})])",MACs,19382.206464,top1_acc,-88.27169690606229 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 384, 10: 192, 11: 768, 12: 3072, 13: 2815, 14: 1284, 15: 2825, 16: 2115, 17: 2017, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,24339.08736,top1_acc,-88.88757433576913 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 2876, 15: 1218, 16: 1205, 17: 2760, 18: 2651, 19: 1809, 20: 3072, 21: 964, 22: 3072, 23: 617})])",MACs,22550.740992,top1_acc,-88.6614581780922 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 768, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 2628, 20: 2441, 21: 401, 22: 1554, 23: 617})])",MACs,21221.277696,top1_acc,-88.4723679157084 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2815, 14: 2189, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 3072, 22: 785, 23: 1030})])",MACs,26406.42048,top1_acc,-89.06760015215644 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 2115, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 3072, 22: 785, 23: 3072})])",MACs,26311.458816,top1_acc,-89.01393670390227 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2096, 13: 2815, 14: 2189, 15: 2825, 16: 1205, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 785, 23: 422})])",MACs,22692.298752,top1_acc,-88.94028818939152 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 2628, 20: 1559, 21: 401, 22: 404, 23: 617})])",MACs,19749.666816,top1_acc,-88.40496312428841 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 512, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 2115, 17: 3072, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 785, 23: 422})])",MACs,24952.50432,top1_acc,-88.94676334407045 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 512, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2017, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,23401.857024,top1_acc,-88.92672573716226 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 976, 20: 1559, 21: 964, 22: 1554, 23: 1030})])",MACs,19898.892288,top1_acc,-87.93170115650577 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 2441, 21: 401, 22: 3072, 23: 617})])",MACs,22604.414976,top1_acc,-88.6154190207364 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 1170, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 422})])",MACs,20678.049792,top1_acc,-88.33099330822043 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 3072, 22: 404, 23: 422})])",MACs,25118.244864,top1_acc,-89.0684788499793 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 320, 12: 1169, 13: 1170, 14: 2876, 15: 2825, 16: 1205, 17: 2760, 18: 1030, 19: 976, 20: 1559, 21: 401, 22: 785, 23: 617})])",MACs,20534.132736,top1_acc,-88.19008495086747 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 384, 10: 256, 11: 768, 12: 2096, 13: 1170, 14: 1284, 15: 2144, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 1559, 21: 3072, 22: 785, 23: 422})])",MACs,23195.418624,top1_acc,-88.86745525427003 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2815, 14: 3072, 15: 1218, 16: 2804, 17: 2017, 18: 1030, 19: 1809, 20: 2441, 21: 964, 22: 3072, 23: 617})])",MACs,22642.753536,top1_acc,-88.46283326030232 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 2825, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27479.90016,top1_acc,-89.32132967717246 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22714.712064,top1_acc,-89.02029747469655 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 3072, 22: 404, 23: 422})])",MACs,22727.098368,top1_acc,-88.97596482660259 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 2876, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 1809, 20: 3072, 21: 964, 22: 785, 23: 1030})])",MACs,23659.610112,top1_acc,-88.94902080384192 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 1170, 14: 3072, 15: 2825, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 1030})])",MACs,20075.249664,top1_acc,-88.218735915853 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 2825, 16: 2804, 17: 1130, 18: 1030, 19: 2628, 20: 1559, 21: 964, 22: 785, 23: 617})])",MACs,20788.936704,top1_acc,-88.35014933854531 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 617})])",MACs,26822.2464,top1_acc,-89.23428458686702 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 2189, 15: 1218, 16: 1205, 17: 2017, 18: 3072, 19: 2628, 20: 1559, 21: 401, 22: 404, 23: 617})])",MACs,22413.312,top1_acc,-88.77107252084137 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 384, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 422})])",MACs,23031.447552,top1_acc,-88.95489771797772 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 2144, 16: 1205, 17: 2760, 18: 1030, 19: 2628, 20: 3072, 21: 401, 22: 785, 23: 617})])",MACs,22098.345984,top1_acc,-88.70307550671853 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 2804, 17: 2017, 18: 1030, 19: 976, 20: 1559, 21: 964, 22: 785, 23: 617})])",MACs,21765.685248,top1_acc,-88.47480804439098 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 1170, 14: 2876, 15: 1218, 16: 2115, 17: 3072, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 785, 23: 617})])",MACs,24740.16768,top1_acc,-89.11957125977483 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 768, 11: 768, 12: 2830, 13: 1170, 14: 2189, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 3072, 23: 617})])",MACs,24635.768832,top1_acc,-89.06220467797208 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 768, 11: 768, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 3072, 22: 785, 23: 617})])",MACs,26496.663552,top1_acc,-89.17204702606881 +"OrderedDict([(, {0: 768, 1: 768, 2: 512, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 617})])",MACs,25878.528,top1_acc,-89.17476564344034 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 3072, 17: 1130, 18: 1030, 19: 976, 20: 1559, 21: 964, 22: 1554, 23: 1030})])",MACs,22722.379776,top1_acc,-88.5085266277203 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 768, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 2876, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 1809, 20: 3072, 21: 3072, 22: 785, 23: 1030})])",MACs,26322.665472,top1_acc,-88.9958251215683 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 617})])",MACs,22850.961408,top1_acc,-88.74459388405853 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27589.607424,top1_acc,-89.36509240179869 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2096, 13: 1170, 14: 2189, 15: 2825, 16: 3072, 17: 2760, 18: 1030, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 422})])",MACs,24521.342976,top1_acc,-88.92818900998365 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 384, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 2815, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 422})])",MACs,24521.9328,top1_acc,-88.98983505605398 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 2628, 20: 1559, 21: 3072, 22: 404, 23: 617})])",MACs,20853.22752,top1_acc,-88.53194818960242 +"OrderedDict([(, {0: 768, 1: 768, 2: 512, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 3072, 13: 1170, 14: 2876, 15: 3072, 16: 1205, 17: 2017, 18: 1869, 19: 2628, 20: 3072, 21: 401, 22: 785, 23: 422})])",MACs,23610.65472,top1_acc,-88.7026956653278 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 768, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 2876, 15: 1218, 16: 3072, 17: 2017, 18: 2651, 19: 1809, 20: 3072, 21: 964, 22: 785, 23: 1030})])",MACs,23221.37088,top1_acc,-88.81599041096595 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 976, 20: 1559, 21: 964, 22: 1554, 23: 422})])",MACs,19978.518528,top1_acc,-87.99959724851692 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 640, 5: 384, 6: 768, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2099, 14: 2876, 15: 1218, 16: 2115, 17: 3072, 18: 3072, 19: 1809, 20: 3072, 21: 401, 22: 785, 23: 422})])",MACs,25583.026176,top1_acc,-89.19415324931042 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2815, 14: 3072, 15: 3072, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 422})])",MACs,27212.709888,top1_acc,-89.03969726169086 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 1170, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 1030, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 617})])",MACs,24031.789056,top1_acc,-88.8638574480537 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27589.607424,top1_acc,-89.36288900025647 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2815, 14: 2189, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 976, 20: 1559, 21: 3072, 22: 785, 23: 1030})])",MACs,26818.117632,top1_acc,-88.95558808618152 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 2144, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 1559, 21: 401, 22: 785, 23: 617})])",MACs,18929.811456,top1_acc,-88.3316084806082 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 768, 11: 768, 12: 1169, 13: 2099, 14: 2189, 15: 2825, 16: 2115, 17: 2017, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,23978.704896,top1_acc,-88.95194500755295 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 384, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 2628, 20: 1559, 21: 401, 22: 404, 23: 617})])",MACs,18203.738112,top1_acc,-88.07853175664185 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 768, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,17812.094976,top1_acc,-87.96425789941911 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2096, 13: 1170, 14: 2876, 15: 3072, 16: 1205, 17: 2017, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20239.81056,top1_acc,-88.47550413239591 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 1030})])",MACs,18652.594176,top1_acc,-88.2361070844556 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21627.076608,top1_acc,-88.99156584684754 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 2876, 15: 2825, 16: 1205, 17: 2760, 18: 2651, 19: 976, 20: 1559, 21: 401, 22: 785, 23: 422})])",MACs,20525.8752,top1_acc,-88.48306822344969 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26125.664256,top1_acc,-89.28182159221679 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 2815, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 3072, 19: 1809, 20: 1559, 21: 3072, 22: 785, 23: 1030})])",MACs,25690.963968,top1_acc,-88.85583918736536 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 1554, 23: 422})])",MACs,24239.996928,top1_acc,-89.07462288318236 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 2830, 13: 1170, 14: 2189, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 2628, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,21653.618688,top1_acc,-88.50860957587066 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 2144, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 1559, 21: 401, 22: 785, 23: 617})])",MACs,23417.192448,top1_acc,-88.81446073901583 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 3072, 16: 1205, 17: 2017, 18: 1869, 19: 2628, 20: 1559, 21: 401, 22: 785, 23: 617})])",MACs,21054.947328,top1_acc,-88.54843071972887 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 384, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 1170, 14: 3072, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,23204.265984,top1_acc,-88.81000839095158 +"OrderedDict([(, {0: 768, 1: 768, 2: 512, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,24179.245056,top1_acc,-89.03122011533486 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 448, 7: 768, 8: 512, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 1170, 14: 3072, 15: 2144, 16: 1205, 17: 2760, 18: 1030, 19: 976, 20: 3072, 21: 401, 22: 785, 23: 617})])",MACs,23772.85632,top1_acc,-88.49434547937453 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 512, 4: 512, 5: 768, 6: 448, 7: 768, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 2876, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 1809, 20: 3072, 21: 964, 22: 785, 23: 1030})])",MACs,24445.25568,top1_acc,-89.05821535146181 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2099, 14: 2876, 15: 1218, 16: 2115, 17: 3072, 18: 3072, 19: 1809, 20: 3072, 21: 401, 22: 785, 23: 422})])",MACs,25771.769856,top1_acc,-89.06310311882241 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 2189, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 404, 23: 617})])",MACs,20666.843136,top1_acc,-88.75990204575675 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23046.782976,top1_acc,-89.04276529198559 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 768, 4: 640, 5: 384, 6: 768, 7: 448, 8: 768, 9: 768, 10: 256, 11: 768, 12: 3072, 13: 1170, 14: 2876, 15: 1218, 16: 2804, 17: 3072, 18: 1030, 19: 1809, 20: 3072, 21: 964, 22: 785, 23: 617})])",MACs,24117.90336,top1_acc,-88.90429478556376 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 768, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 2628, 20: 2441, 21: 401, 22: 1554, 23: 617})])",MACs,21627.666432,top1_acc,-88.45195120606634 +"OrderedDict([(, {0: 768, 1: 768, 2: 512, 3: 768, 4: 512, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 1559, 21: 3072, 22: 785, 23: 1030})])",MACs,24687.08352,top1_acc,-89.08513106777062 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 512, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 320, 12: 1169, 13: 1170, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 1030, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,22103.064576,top1_acc,-88.45719356221645 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 768, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 2144, 16: 3072, 17: 2760, 18: 2651, 19: 1809, 20: 3072, 21: 964, 22: 785, 23: 1030})])",MACs,23190.700032,top1_acc,-88.80606974942746 +"OrderedDict([(, {0: 768, 1: 768, 2: 512, 3: 768, 4: 512, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 1130, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 1030})])",MACs,21621.768192,top1_acc,-88.76031031184357 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 785, 23: 617})])",MACs,27482.259456,top1_acc,-89.36681068145607 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,23290.970112,top1_acc,-88.67240911230358 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 2096, 13: 1170, 14: 2876, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18368.299008,top1_acc,-88.08967371704031 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 768, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,19506.659328,top1_acc,-88.46798771276349 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 1559, 21: 401, 22: 785, 23: 1030})])",MACs,17188.061184,top1_acc,-88.17987172800102 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,21735.0144,top1_acc,-88.79764366459011 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 768, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27166.113792,top1_acc,-89.215756829788 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21438.332928,top1_acc,-88.82004445577063 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 384, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 2628, 20: 1559, 21: 401, 22: 404, 23: 617})])",MACs,19053.084672,top1_acc,-88.11712096427651 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21295.005696,top1_acc,-88.97185242926862 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 1809, 20: 1559, 21: 401, 22: 785, 23: 422})])",MACs,20634.402816,top1_acc,-88.3422857217571 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 768, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,17405.70624,top1_acc,-88.052796259121 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,20039.2704,top1_acc,-88.58576349605049 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 1284, 15: 2144, 16: 3072, 17: 2760, 18: 3072, 19: 976, 20: 1559, 21: 964, 22: 785, 23: 617})])",MACs,25057.492992,top1_acc,-89.07815710498934 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 512, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,24710.086656,top1_acc,-89.12217478413012 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 2876, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 1559, 21: 401, 22: 785, 23: 617})])",MACs,19870.580736,top1_acc,-88.4438437718578 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 2876, 15: 3072, 16: 2804, 17: 3072, 18: 1869, 19: 2628, 20: 794, 21: 3072, 22: 785, 23: 422})])",MACs,25718.685696,top1_acc,-88.9156495210419 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21194.145792,top1_acc,-88.96222083060648 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,27823.767552,top1_acc,-89.27798968987264 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 768, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 2825, 16: 1205, 17: 2017, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20640.301056,top1_acc,-88.54976933608323 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 3072, 22: 404, 23: 422})])",MACs,23160.029184,top1_acc,-88.9732486840068 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 448, 4: 640, 5: 384, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 2099, 14: 2876, 15: 1218, 16: 2115, 17: 3072, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 785, 23: 422})])",MACs,25537.609728,top1_acc,-89.156952773821 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 640, 5: 384, 6: 768, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2099, 14: 2876, 15: 2825, 16: 2115, 17: 3072, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 785, 23: 422})])",MACs,26862.944256,top1_acc,-89.17044008090299 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22804.955136,top1_acc,-89.12190315835852 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 1554, 23: 617})])",MACs,24986.124288,top1_acc,-89.15736615576293 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 768, 4: 768, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 1169, 13: 2099, 14: 3072, 15: 2144, 16: 3072, 17: 2760, 18: 1030, 19: 2628, 20: 1559, 21: 964, 22: 785, 23: 617})])",MACs,24902.36928,top1_acc,-89.01897509460531 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 3072, 22: 404, 23: 617})])",MACs,25233.850368,top1_acc,-89.13076911601584 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 768, 11: 768, 12: 2096, 13: 2815, 14: 2189, 15: 2825, 16: 1205, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 785, 23: 422})])",MACs,24013.504512,top1_acc,-89.02448239480113 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,28017.229824,top1_acc,-89.33930300274314 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 1559, 21: 3072, 22: 785, 23: 1030})])",MACs,21574.582272,top1_acc,-88.68154721037867 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25028.001792,top1_acc,-89.22040853021726 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 512, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2017, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,26158.6944,top1_acc,-89.10877540321097 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 2189, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22443.982848,top1_acc,-89.0595688152179 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27117.748224,top1_acc,-89.45805777092639 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 2651, 19: 1809, 20: 1559, 21: 401, 22: 1554, 23: 1030})])",MACs,21926.7072,top1_acc,-88.7509607510115 +"OrderedDict([(, {0: 768, 1: 768, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 768, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 2825, 16: 1205, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20909.2608,top1_acc,-88.41486922723871 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 768, 4: 640, 5: 384, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,24383.913984,top1_acc,-88.90687997745198 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2830, 13: 2815, 14: 2189, 15: 2825, 16: 1205, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,22990.159872,top1_acc,-88.90216329236775 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 768, 11: 768, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 1205, 17: 3072, 18: 1030, 19: 2628, 20: 1559, 21: 3072, 22: 404, 23: 617})])",MACs,24575.606784,top1_acc,-88.79920240941203 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 384, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26035.421184,top1_acc,-89.17931965407935 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 2189, 15: 1218, 16: 1205, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 404, 23: 422})])",MACs,19543.228416,top1_acc,-88.56796465507819 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 1170, 14: 1284, 15: 2825, 16: 1205, 17: 2760, 18: 3072, 19: 976, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,22258.188288,top1_acc,-88.75777387250243 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,19944.89856,top1_acc,-88.63597513707988 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 2628, 20: 1559, 21: 401, 22: 404, 23: 617})])",MACs,17731.878912,top1_acc,-87.95094781004927 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25509.298176,top1_acc,-89.27453381219581 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18340.57728,top1_acc,-88.46422693425312 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,21136.932864,top1_acc,-88.6460934257591 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 1170, 14: 2876, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,19799.212032,top1_acc,-88.37104748304331 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 404, 23: 617})])",MACs,19661.193216,top1_acc,-88.54085696023776 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 2099, 14: 3072, 15: 2825, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,28140.50304,top1_acc,-89.31845008853038 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 422})])",MACs,19123.863552,top1_acc,-88.53403217300595 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 2144, 16: 1205, 17: 2017, 18: 1030, 19: 976, 20: 1559, 21: 401, 22: 785, 23: 617})])",MACs,19113.24672,top1_acc,-88.2302859050742 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,18958.712832,top1_acc,-88.33392613188404 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 785, 23: 617})])",MACs,22416.850944,top1_acc,-89.06875007366868 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2804, 17: 2017, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18767.609856,top1_acc,-88.39818047977279 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 617})])",MACs,26256.01536,top1_acc,-89.15370501717746 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 768, 4: 640, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 2830, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 2628, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,19906.56,top1_acc,-88.33364618241228 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 2144, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26671.84128,top1_acc,-89.26468870942286 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2815, 14: 2189, 15: 2825, 16: 1205, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,22785.490944,top1_acc,-88.89502434846959 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 512, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25559.433216,top1_acc,-89.11172341334397 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 1809, 20: 1559, 21: 401, 22: 404, 23: 617})])",MACs,17248.813056,top1_acc,-87.99543940337377 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 1559, 21: 401, 22: 785, 23: 617})])",MACs,18383.634432,top1_acc,-88.32406082859934 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 785, 23: 422})])",MACs,19946.078208,top1_acc,-88.5657341160523 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 768, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,23820.04224,top1_acc,-88.86650853785147 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 2804, 17: 3072, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 1554, 23: 617})])",MACs,25915.097088,top1_acc,-89.22330251102342 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 617})])",MACs,27814.330368,top1_acc,-89.33053380404957 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 964, 22: 404, 23: 617})])",MACs,22180.33152,top1_acc,-88.99909909657175 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 1559, 21: 401, 22: 785, 23: 1030})])",MACs,23724.490752,top1_acc,-89.14760073178158 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 785, 23: 617})])",MACs,26013.007872,top1_acc,-89.17046200115814 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,19195.82208,top1_acc,-88.09163397367246 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 768, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 785, 23: 617})])",MACs,20016.857088,top1_acc,-88.45903996863389 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 1554, 23: 422})])",MACs,24334.368768,top1_acc,-89.06863423703379 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 617})])",MACs,27814.330368,top1_acc,-89.34780932949097 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21149.908992,top1_acc,-89.05168791905575 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2096, 13: 1170, 14: 2189, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 404, 23: 617})])",MACs,21402.353664,top1_acc,-89.08516589168119 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 404, 23: 617})])",MACs,19124.453376,top1_acc,-88.47992718943185 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,26195.263488,top1_acc,-89.17981948734237 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,17124.950016,top1_acc,-88.38280489180448 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 2189, 15: 1218, 16: 1205, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,20768.882688,top1_acc,-88.83790836028959 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 1559, 21: 401, 22: 404, 23: 617})])",MACs,17687.052288,top1_acc,-88.27317144611735 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 384, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 2189, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,24423.432192,top1_acc,-89.01323571002328 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16268.525568,top1_acc,-88.2105860016782 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,21414.150144,top1_acc,-88.79806611589477 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,25532.891136,top1_acc,-89.24514858783492 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2804, 17: 3072, 18: 1030, 19: 2628, 20: 1559, 21: 401, 22: 404, 23: 617})])",MACs,19560.923136,top1_acc,-88.541374744656 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25842.548736,top1_acc,-89.29338719972554 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,27446.280192,top1_acc,-89.38208395215815 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 2189, 15: 2825, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 785, 23: 617})])",MACs,23710.9248,top1_acc,-89.1526780690639 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,19209.388032,top1_acc,-88.48858716664185 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 2189, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 1809, 20: 1559, 21: 401, 22: 404, 23: 422})])",MACs,17667.588096,top1_acc,-87.97286494367687 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22735.355904,top1_acc,-89.03461063225718 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 1130, 18: 2651, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,22364.946432,top1_acc,-88.82797713748602 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 617})])",MACs,26776.240128,top1_acc,-89.1941760835796 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 768, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 1170, 14: 2876, 15: 1218, 16: 2115, 17: 2017, 18: 1030, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,21852.9792,top1_acc,-88.60931048470785 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 768, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 1559, 21: 401, 22: 785, 23: 1030})])",MACs,17848.664064,top1_acc,-88.19301612089448 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 768, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 1030, 19: 2628, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,21792.227328,top1_acc,-88.71733268194902 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 1205, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,21484.929024,top1_acc,-88.70007543831794 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22333.095936,top1_acc,-88.93072546053003 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,16021.979136,top1_acc,-88.09995271406063 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 1559, 21: 401, 22: 785, 23: 617})])",MACs,17723.031552,top1_acc,-88.13917765239097 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 512, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,22348.43136,top1_acc,-88.709340517623 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 1205, 17: 3072, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21340.422144,top1_acc,-88.84154512951693 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18194.300928,top1_acc,-88.58629541487953 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 1559, 21: 401, 22: 785, 23: 617})])",MACs,18458.54208,top1_acc,-88.51655879650991 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22238.724096,top1_acc,-88.98885065767547 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 785, 23: 617})])",MACs,21948.530688,top1_acc,-88.74395291804848 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 785, 23: 617})])",MACs,16547.51232,top1_acc,-88.06520297043832 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 1559, 21: 401, 22: 785, 23: 1030})])",MACs,24101.978112,top1_acc,-89.19775969443829 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,20028.063744,top1_acc,-88.74535437304799 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 3072, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27449.229312,top1_acc,-89.26295204940187 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,26785.677312,top1_acc,-89.46962053671481 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 1205, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18588.893184,top1_acc,-88.51048836069712 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27400.863744,top1_acc,-89.36083488009734 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,20133.64224,top1_acc,-88.64711697408981 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 1170, 14: 3072, 15: 2825, 16: 3072, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 404, 23: 617})])",MACs,25189.613568,top1_acc,-88.99317169167068 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20079.378432,top1_acc,-88.86910897089034 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 2189, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 404, 23: 617})])",MACs,21950.30016,top1_acc,-89.10291114926581 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 2189, 15: 2825, 16: 2115, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 785, 23: 617})])",MACs,24107.876352,top1_acc,-89.07246470837545 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,25378.947072,top1_acc,-89.24617889808263 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 422})])",MACs,23916.773376,top1_acc,-88.73505430488225 +"OrderedDict([(, {0: 576, 1: 768, 2: 448, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 256, 11: 768, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 2804, 17: 2017, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 1030})])",MACs,21556.887552,top1_acc,-88.67647181665282 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 512, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 785, 23: 1030})])",MACs,21146.370048,top1_acc,-88.78941924666077 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21716.140032,top1_acc,-89.21058537185422 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 2189, 15: 2825, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,22899.326976,top1_acc,-89.0373254159037 +"OrderedDict([(, {0: 576, 1: 768, 2: 512, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 256, 11: 768, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,20787.757056,top1_acc,-88.51351507271282 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 785, 23: 617})])",MACs,27104.772096,top1_acc,-89.27170474081825 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17603.887104,top1_acc,-88.34953036965457 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26171.670528,top1_acc,-89.32006408373448 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17945.985024,top1_acc,-88.64509805628019 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20866.793472,top1_acc,-88.9915087222912 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18005.557248,top1_acc,-88.47503898268043 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 785, 23: 617})])",MACs,24472.977408,top1_acc,-89.15968527456486 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15386.148864,top1_acc,-88.06813806065767 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15720.579072,top1_acc,-88.01373623633745 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25445.597184,top1_acc,-89.227537991734 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 1130, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23204.265984,top1_acc,-88.67102105481754 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22059.4176,top1_acc,-89.2062175019821 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 1559, 21: 401, 22: 785, 23: 617})])",MACs,16944.463872,top1_acc,-88.22941770194504 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 2189, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22632.726528,top1_acc,-89.17177708657846 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 2628, 20: 1559, 21: 401, 22: 785, 23: 1030})])",MACs,23252.631552,top1_acc,-88.98208848896523 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18005.557248,top1_acc,-88.4256617163528 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 785, 23: 617})])",MACs,22888.710144,top1_acc,-89.13604759447986 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 2099, 14: 2189, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 404, 23: 617})])",MACs,20880.359424,top1_acc,-88.90328052542284 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,24201.658368,top1_acc,-89.233156467533 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,20717.568,top1_acc,-88.72373880937252 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 2189, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 2441, 21: 401, 22: 404, 23: 617})])",MACs,23881.97376,top1_acc,-89.19890926027401 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25414.926336,top1_acc,-89.27043016067977 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21107.441664,top1_acc,-88.87212350097093 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,17531.338752,top1_acc,-88.34399894896872 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17459.970048,top1_acc,-88.22630246492045 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 256, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27872.722944,top1_acc,-89.46665769170889 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 1030})])",MACs,21110.390784,top1_acc,-88.99048907215118 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,20616.708096,top1_acc,-88.69020241808414 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 384, 6: 448, 7: 768, 8: 512, 9: 384, 10: 768, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 1030})])",MACs,19472.449536,top1_acc,-88.34121309705614 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 512, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1030, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,22016.360448,top1_acc,-88.72752909817592 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 2804, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19815.13728,top1_acc,-88.49485303111234 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 256, 11: 768, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1030, 19: 1809, 20: 1559, 21: 401, 22: 404, 23: 617})])",MACs,19903.021056,top1_acc,-88.59676100929983 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21244.280832,top1_acc,-89.08657957760212 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25434.390528,top1_acc,-89.25748179900121 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 3072, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21144.010752,top1_acc,-88.88950098468194 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,24643.436544,top1_acc,-89.0694850517236 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17316.052992,top1_acc,-88.50427999935309 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19784.466432,top1_acc,-89.06034005011318 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27545.370624,top1_acc,-89.40433813838932 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,23999.93856,top1_acc,-89.14637789079143 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 785, 23: 617})])",MACs,16141.123584,top1_acc,-88.122964791656 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16454.909952,top1_acc,-88.30464908414454 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,15927.607296,top1_acc,-88.06735053804071 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 2099, 14: 2189, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 2441, 21: 401, 22: 404, 23: 617})])",MACs,20397.293568,top1_acc,-88.74835945396087 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 1205, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,23652.532224,top1_acc,-89.05948487855962 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21894.26688,top1_acc,-88.8324063639794 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25909.198848,top1_acc,-89.25663034240154 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,17373.855744,top1_acc,-88.02140897182662 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15858.008064,top1_acc,-88.179554995866 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17599.168512,top1_acc,-88.49844710757283 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20562.444288,top1_acc,-88.7976153238057 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16926.179328,top1_acc,-88.34060148469462 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23565.238272,top1_acc,-88.94806658761243 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,20899.823616,top1_acc,-88.77825470787717 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 1559, 21: 964, 22: 785, 23: 617})])",MACs,17276.534784,top1_acc,-88.2722287372326 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18623.6928,top1_acc,-88.39280229224637 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,23354.08128,top1_acc,-88.90968093228996 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,24073.076736,top1_acc,-89.07515084609483 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23190.110208,top1_acc,-89.27968355031486 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17911.185408,top1_acc,-88.51072558636406 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21874.212864,top1_acc,-89.16341370533753 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21382.299648,top1_acc,-89.01579188809693 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 785, 23: 617})])",MACs,17095.458816,top1_acc,-88.14915490875924 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 1130, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,24008.78592,top1_acc,-89.02520125093204 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,18140.626944,top1_acc,-88.53064941763603 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 256, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23366.467584,top1_acc,-89.01558869079527 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,17408.065536,top1_acc,-88.44844224763273 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25877.348352,top1_acc,-89.28263207379442 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22531.2768,top1_acc,-89.13931702547605 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 384, 6: 768, 7: 768, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,23675.53536,top1_acc,-89.17659617705901 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20783.628288,top1_acc,-89.04892590478622 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 3072, 19: 1809, 20: 1559, 21: 401, 22: 404, 23: 617})])",MACs,17345.544192,top1_acc,-88.35073279368994 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 1030, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,22119.579648,top1_acc,-88.6570701709829 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17350.852608,top1_acc,-88.6629663105333 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,24043.585536,top1_acc,-89.21834899746482 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,20705.181696,top1_acc,-88.68867302885045 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19912.45824,top1_acc,-88.79587665492326 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 2651, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,19377.487872,top1_acc,-88.48228286333101 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,24486.54336,top1_acc,-89.14915806953698 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 768, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,22649.831424,top1_acc,-88.84941149544474 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21433.024512,top1_acc,-89.12668686365866 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25087.574016,top1_acc,-89.29349452029435 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 2189, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 404, 23: 617})])",MACs,21478.44096,top1_acc,-89.06381043526424 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 768, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,23646.04416,top1_acc,-89.19050084691409 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26118.586368,top1_acc,-89.41821503081395 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 785, 23: 422})])",MACs,17793.220608,top1_acc,-88.37614451171926 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,25837.830144,top1_acc,-89.18672288096424 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17743.675392,top1_acc,-88.57257258450197 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15814.950912,top1_acc,-88.00246405437538 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26884.767744,top1_acc,-89.29004435992077 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 768, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 1559, 21: 964, 22: 404, 23: 617})])",MACs,18142.396416,top1_acc,-88.32781577299575 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21965.04576,top1_acc,-89.12158677431931 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20777.140224,top1_acc,-89.05950522099911 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 384, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,24849.874944,top1_acc,-89.30393235825761 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22048.210944,top1_acc,-89.14684831979618 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21066.743808,top1_acc,-89.04888523919855 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 2189, 15: 1218, 16: 2115, 17: 2017, 18: 3072, 19: 2628, 20: 2441, 21: 401, 22: 404, 23: 617})])",MACs,23037.345792,top1_acc,-89.08689130562415 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17199.26784,top1_acc,-88.28442608904902 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 768, 8: 512, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,24583.86432,top1_acc,-89.08108536082709 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25359.48288,top1_acc,-89.18050991499885 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 2189, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 2628, 20: 2441, 21: 401, 22: 404, 23: 617})])",MACs,21950.30016,top1_acc,-89.10291114926581 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,23041.47456,top1_acc,-89.19080054939494 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 1559, 21: 401, 22: 785, 23: 617})])",MACs,17858.691072,top1_acc,-88.53279561359462 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22804.365312,top1_acc,-88.96055912218188 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26597.523456,top1_acc,-89.28479158309956 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18196.0704,top1_acc,-88.72484706492065 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16551.641088,top1_acc,-88.35240413477048 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,18462.670848,top1_acc,-88.38040293065409 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,24500.699136,top1_acc,-89.1222553188815 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,18210.226176,top1_acc,-88.36152703898773 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,23571.726336,top1_acc,-89.22886002733861 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 1559, 21: 401, 22: 404, 23: 617})])",MACs,16141.123584,top1_acc,-88.21419200133302 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17504.796672,top1_acc,-88.50034167247291 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 384, 10: 768, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25875.57888,top1_acc,-89.28323987111823 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20340.08064,top1_acc,-88.98321360806615 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 2804, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,21140.471808,top1_acc,-88.82150196011399 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20562.444288,top1_acc,-88.7976153238057 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16768.106496,top1_acc,-88.4706234126681 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25792.413696,top1_acc,-89.24648425322253 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16436.625408,top1_acc,-88.33794440152225 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,20439.171072,top1_acc,-88.5708113801027 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,25038.0288,top1_acc,-89.2904140415498 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17308.975104,top1_acc,-88.37842015247226 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,14649.458688,top1_acc,-87.97377271576424 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22135.504896,top1_acc,-89.12455672232761 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23730.388992,top1_acc,-89.22148751600608 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17589.731328,top1_acc,-88.60820444296874 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22346.072064,top1_acc,-89.14402272058307 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16590.569472,top1_acc,-88.17154108584776 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17757.241344,top1_acc,-88.54389481314755 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,23175.954432,top1_acc,-89.1488648249327 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15259.336704,top1_acc,-88.06043770357503 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,21662.466048,top1_acc,-89.05124382043567 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26077.298688,top1_acc,-89.14297784119059 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 512, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 1130, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,23466.737664,top1_acc,-88.76295133942786 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21810.511872,top1_acc,-89.14215185255047 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22531.2768,top1_acc,-89.13931702547605 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27306.491904,top1_acc,-89.29667692218213 +"OrderedDict([(, {0: 768, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17495.359488,top1_acc,-88.50548628907373 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27967.094784,top1_acc,-89.47682450774309 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,24309.006336,top1_acc,-89.10154202789748 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15763.636224,top1_acc,-88.20331473161674 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 2804, 17: 2760, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,23358.210048,top1_acc,-89.12223977948766 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23280.35328,top1_acc,-89.30164804122083 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17470.58688,top1_acc,-88.4305478820257 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26645.889024,top1_acc,-89.31909766785144 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19916.587008,top1_acc,-88.74798385079328 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16805.265408,top1_acc,-88.29207342554966 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16549.281792,top1_acc,-88.3431235643515 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 384, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,24000.528384,top1_acc,-89.26920357843636 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,19367.460864,top1_acc,-88.54793889391458 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15480.520704,top1_acc,-88.14750541878875 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 1130, 18: 2651, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,20706.361344,top1_acc,-88.70927985476044 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21969.174528,top1_acc,-89.09629129888914 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15984.820224,top1_acc,-88.42093126665304 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 768, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,24322.572288,top1_acc,-89.36387837389674 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21407.072256,top1_acc,-88.95940773770293 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16779.313152,top1_acc,-88.33904803915796 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25810.69824,top1_acc,-89.30329546172507 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,26313.818112,top1_acc,-89.3058691051885 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 384, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 2441, 21: 964, 22: 404, 23: 617})])",MACs,25079.31648,top1_acc,-89.12835542995016 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19787.415552,top1_acc,-88.67880234718548 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20478.68928,top1_acc,-88.99792276946643 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,14838.202368,top1_acc,-88.14160475656774 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2017, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20473.970688,top1_acc,-89.07453193113723 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 2189, 15: 1218, 16: 2115, 17: 2017, 18: 3072, 19: 2628, 20: 2441, 21: 401, 22: 404, 23: 617})])",MACs,20338.311168,top1_acc,-88.89089918203042 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22551.330816,top1_acc,-89.20421459068167 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23661.969408,top1_acc,-89.36074310735258 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 1559, 21: 401, 22: 404, 23: 422})])",MACs,17604.476928,top1_acc,-88.56209529074287 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17649.303552,top1_acc,-88.53364581373808 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19773.8496,top1_acc,-88.96111900916435 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17127.309312,top1_acc,-88.32783597313573 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17256.480768,top1_acc,-88.52769789281969 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17832.148992,top1_acc,-88.41885421497196 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23734.51776,top1_acc,-89.15803169983369 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20462.764032,top1_acc,-88.99064381438967 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19569.180672,top1_acc,-88.87534489614588 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 2115, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20078.198784,top1_acc,-88.81948520606433 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22531.2768,top1_acc,-89.13931702547605 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19369.82016,top1_acc,-88.7389803447015 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,22182.690816,top1_acc,-88.97650077295665 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16910.25408,top1_acc,-88.50562092582621 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,26687.176704,top1_acc,-89.22794556331527 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 512, 5: 384, 6: 768, 7: 768, 8: 512, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,17152.08192,top1_acc,-88.18359954091555 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26454.786048,top1_acc,-89.27601971059934 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2017, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25433.800704,top1_acc,-89.12657003804361 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 1559, 21: 401, 22: 404, 23: 422})])",MACs,15648.620544,top1_acc,-88.11639216434448 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 2804, 17: 1130, 18: 2651, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,22341.353472,top1_acc,-88.8677274458875 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20961.165312,top1_acc,-89.08541616578562 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20427.374592,top1_acc,-89.02571446153992 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21173.501952,top1_acc,-89.01351961877826 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16331.046912,top1_acc,-88.3529374241645 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26270.171136,top1_acc,-89.19758003726812 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,25275.727872,top1_acc,-89.18279525779613 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19504.300032,top1_acc,-88.734758114604 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21457.79712,top1_acc,-88.90666946247813 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16256.139264,top1_acc,-88.26624213233754 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21723.21792,top1_acc,-89.0430908433695 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 448, 7: 768, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,23194.238976,top1_acc,-88.9181289046821 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23043.244032,top1_acc,-89.13835166382958 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26436.501504,top1_acc,-89.36601610069206 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18312.265728,top1_acc,-88.58685730880612 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 1170, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 1030, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22840.344576,top1_acc,-88.81850064585923 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,23790.55104,top1_acc,-88.8805828002378 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 1030, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,21643.001856,top1_acc,-88.85038763771598 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 768, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,22530.097152,top1_acc,-88.7800914544736 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 384, 6: 448, 7: 768, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18803.58912,top1_acc,-88.54567671348012 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20455.09632,top1_acc,-88.88402377392651 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18607.767552,top1_acc,-88.79724250055682 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 3072, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,18594.791424,top1_acc,-88.37661149281945 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18091.671552,top1_acc,-88.49432516702484 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,19053.674496,top1_acc,-88.63569006153526 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27212.120064,top1_acc,-89.41892926787817 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22046.441472,top1_acc,-88.96679912901004 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17703.56736,top1_acc,-88.70797570986754 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 3072, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,24566.759424,top1_acc,-89.2834541690257 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16403.00544,top1_acc,-88.22763565457434 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15330.705408,top1_acc,-88.03908802762702 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16457.269248,top1_acc,-88.27504748984765 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17945.985024,top1_acc,-88.53541045137838 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22063.546368,top1_acc,-89.05649463424996 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2017, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,23458.480128,top1_acc,-88.95306300425865 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22325.428224,top1_acc,-89.0237432864092 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20304.101376,top1_acc,-89.03796847563113 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 768, 11: 768, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,25077.547008,top1_acc,-89.35883987584117 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25283.395584,top1_acc,-89.19592634716665 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,19306.119168,top1_acc,-88.75027329071452 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20975.321088,top1_acc,-89.2304241004385 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 512, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16231.366656,top1_acc,-88.10626968812835 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,21050.228736,top1_acc,-88.87391473063533 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23055.040512,top1_acc,-89.17115831031549 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18371.248128,top1_acc,-88.65355048552568 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15763.636224,top1_acc,-88.2112510709314 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17495.359488,top1_acc,-88.56878328851519 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22444.572672,top1_acc,-89.37975337681716 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19150.995456,top1_acc,-88.72509987329823 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2017, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19493.093376,top1_acc,-88.72529067360172 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 256, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27212.120064,top1_acc,-89.45682671454199 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22551.330816,top1_acc,-89.20421459068167 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20009.7792,top1_acc,-88.78124901572014 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15215.689728,top1_acc,-88.0693970175243 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17787.912192,top1_acc,-88.52082026087533 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,18864.930816,top1_acc,-88.7102517579017 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 1205, 17: 1130, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,19982.647296,top1_acc,-88.28345647502769 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18179.555328,top1_acc,-88.62965891992968 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,22859.808768,top1_acc,-89.01091710947168 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17368.547328,top1_acc,-88.54939393728236 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2017, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20081.737728,top1_acc,-88.69475253087067 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 512, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17595.039744,top1_acc,-88.36664881925638 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 768, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,24621.023232,top1_acc,-89.30266392701714 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25598.3616,top1_acc,-89.16071219525868 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22465.806336,top1_acc,-89.16973101520398 +"OrderedDict([(, {0: 576, 1: 448, 2: 512, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,17619.812352,top1_acc,-88.51232833710604 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17759.60064,top1_acc,-88.51426976292657 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26138.05056,top1_acc,-89.30844776466009 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19436.470272,top1_acc,-88.5944176136995 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19162.791936,top1_acc,-88.91143645819048 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,14764.474368,top1_acc,-87.95915829838711 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18613.075968,top1_acc,-88.71238263990949 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25964.642304,top1_acc,-89.43236616368182 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16346.382336,top1_acc,-88.36704947196473 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16233.725952,top1_acc,-88.366201071852 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 1130, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21469.5936,top1_acc,-88.87180237732865 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20676.28032,top1_acc,-88.84044342636363 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 1130, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26816.937984,top1_acc,-89.16497467646985 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,18815.3856,top1_acc,-88.47858194068179 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,20978.270208,top1_acc,-88.9338752235276 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15141.961728,top1_acc,-88.01216175285813 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17371.496448,top1_acc,-88.48068012990164 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16415.391744,top1_acc,-88.23594961813062 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15720.579072,top1_acc,-88.01373623633745 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26590.445568,top1_acc,-89.43720406853697 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19467.14112,top1_acc,-88.84687681398164 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16350.511104,top1_acc,-88.24765046242327 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19448.856576,top1_acc,-88.73477836276744 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,17531.928576,top1_acc,-88.30103915169342 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17418.682368,top1_acc,-88.53072709874147 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 1130, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19024.183296,top1_acc,-88.64133509902274 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 768, 12: 1169, 13: 1170, 14: 3072, 15: 2825, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18559.991808,top1_acc,-88.49583194807408 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18785.304576,top1_acc,-88.72381294564899 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16342.253568,top1_acc,-88.31147286297711 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15333.064704,top1_acc,-88.17151391830868 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2830, 13: 1170, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25078.136832,top1_acc,-89.14549592306169 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15186.198528,top1_acc,-88.01740663194666 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18045.66528,top1_acc,-88.64550338978167 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20243.349504,top1_acc,-88.88188030082661 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23420.731392,top1_acc,-88.87638673919875 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,23004.315648,top1_acc,-89.13102734700811 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16719.740928,top1_acc,-88.52060001032864 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18693.292032,top1_acc,-88.7251069793614 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,17039.425536,top1_acc,-88.29713204766124 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 768, 7: 768, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,21897.216,top1_acc,-88.88661638920087 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16834.166784,top1_acc,-88.49783451229823 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21595.226112,top1_acc,-89.09651769667595 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19422.314496,top1_acc,-88.83392030132315 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20146.618368,top1_acc,-88.95754343588435 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,23680.253952,top1_acc,-89.18827661238481 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21046.099968,top1_acc,-88.92891145315136 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20503.461888,top1_acc,-89.0606000922308 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18505.138176,top1_acc,-88.72786903712282 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19695.992832,top1_acc,-88.82314673384613 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23756.341248,top1_acc,-89.36606334400835 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,21619.99872,top1_acc,-88.39386478413506 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 1130, 18: 2651, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,21196.505088,top1_acc,-88.60915675113554 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 1205, 17: 1130, 18: 1030, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,17075.4048,top1_acc,-88.16681062528414 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2017, 18: 1869, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,19179.307008,top1_acc,-88.8554520199827 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 256, 11: 768, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23661.969408,top1_acc,-89.18773330200031 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20159.004672,top1_acc,-88.89450267476872 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18729.271296,top1_acc,-88.4840890243664 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 768, 6: 768, 7: 768, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 422})])",MACs,22000.4352,top1_acc,-88.86706437787039 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18134.728704,top1_acc,-88.75278082877438 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19894.173696,top1_acc,-88.98528499045281 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21531.52512,top1_acc,-89.14325586839674 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19634.651136,top1_acc,-88.9742026908608 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,25786.515456,top1_acc,-89.4680803423226 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19195.82208,top1_acc,-88.65021256718387 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19087.884288,top1_acc,-88.74342491833329 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 768, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23010.803712,top1_acc,-89.23886140117003 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 384, 6: 448, 7: 768, 8: 512, 9: 384, 10: 192, 11: 768, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,20807.811072,top1_acc,-88.56408408194149 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 512, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 1030, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20248.65792,top1_acc,-88.70368054296404 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 768, 12: 2830, 13: 1170, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,25467.420672,top1_acc,-89.11663918600425 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21379.350528,top1_acc,-89.04219883475237 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17917.083648,top1_acc,-88.55160707580154 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 1205, 17: 1130, 18: 1030, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 422})])",MACs,20455.09632,top1_acc,-88.45023671563959 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25957.564416,top1_acc,-89.19829310528917 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 1130, 18: 1030, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20880.949248,top1_acc,-88.73111875410429 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17198.088192,top1_acc,-88.42917515148811 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20701.642752,top1_acc,-89.09217162925188 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,18263.90016,top1_acc,-88.60080205808437 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2017, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20190.855168,top1_acc,-89.03188236166702 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18107.006976,top1_acc,-88.66663391087806 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,24700.059648,top1_acc,-89.39457121372713 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16373.51424,top1_acc,-88.35496395689665 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19634.651136,top1_acc,-88.90426031976418 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18201.378816,top1_acc,-88.80129004677731 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20676.870144,top1_acc,-88.79124843548914 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26740.260864,top1_acc,-89.34246991315979 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16758.669312,top1_acc,-88.29949674983547 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2017, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22783.131648,top1_acc,-89.05270362200804 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18217.893888,top1_acc,-88.74327846087125 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18626.052096,top1_acc,-88.7901763978433 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17590.910976,top1_acc,-88.48632907982113 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 1205, 17: 1130, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,19989.725184,top1_acc,-88.51761352206344 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,25880.887296,top1_acc,-89.4916358206379 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18614.84544,top1_acc,-88.70703252336669 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17915.314176,top1_acc,-88.74402999350255 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2017, 18: 1869, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20599.013376,top1_acc,-89.03181309530726 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15259.336704,top1_acc,-88.06043770357503 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,23329.898496,top1_acc,-89.32468423452225 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21961.506816,top1_acc,-89.01140187987293 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 1030, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,20998.914048,top1_acc,-88.51290214871247 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20125.974528,top1_acc,-88.93054916979183 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18206.687232,top1_acc,-88.68532281821902 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15993.667584,top1_acc,-88.3349629087605 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 768, 8: 512, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 1170, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 1030, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,22626.828288,top1_acc,-88.85422573669017 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17822.711808,top1_acc,-88.50947022455225 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16532.76672,top1_acc,-88.46258172665249 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 422})])",MACs,24283.05408,top1_acc,-89.20652043688148 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21024.866304,top1_acc,-89.18319144006549 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15374.942208,top1_acc,-88.24888838635171 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 768, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,18568.249344,top1_acc,-88.59803040670363 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,23459.659776,top1_acc,-89.05033671249346 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22817.34144,top1_acc,-89.17759351683996 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21517.959168,top1_acc,-88.86082213542642 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23645.454336,top1_acc,-89.2185462500959 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16612.982784,top1_acc,-88.24708015468259 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,19953.156096,top1_acc,-88.56890781050885 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,19694.22336,top1_acc,-89.0112074695066 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23499.177984,top1_acc,-89.24818886057903 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20125.974528,top1_acc,-89.09309252245401 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16531.587072,top1_acc,-88.21606127376832 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26118.586368,top1_acc,-89.41821503081395 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16651.321344,top1_acc,-88.30250123025755 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,24367.988736,top1_acc,-89.32301758716962 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16369.975296,top1_acc,-88.31521258820105 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,21973.89312,top1_acc,-89.13302442231318 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16814.112768,top1_acc,-88.4441189031639 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16979.853312,top1_acc,-88.14914987713672 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18295.750656,top1_acc,-88.71529123850756 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18229.690368,top1_acc,-88.69953924540782 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,18449.104896,top1_acc,-88.7344024825266 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25320.554496,top1_acc,-89.17521046206703 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26212.958208,top1_acc,-89.44950254311212 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,17901.1584,top1_acc,-88.39207949892449 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15312.420864,top1_acc,-88.10272457029086 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 768, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 3072, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18391.302144,top1_acc,-88.45733655455561 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17067.737088,top1_acc,-88.5060280317851 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,24586.223616,top1_acc,-89.27088452325644 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,24461.180928,top1_acc,-89.27288937599667 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16719.740928,top1_acc,-88.4124189076005 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17465.868288,top1_acc,-88.51571741792907 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 768, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21818.179584,top1_acc,-89.1127757956833 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 384, 10: 768, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,22772.514816,top1_acc,-89.11175739934748 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22112.50176,top1_acc,-89.22800331503444 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19108.528128,top1_acc,-88.93237978891473 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17653.43232,top1_acc,-88.58151893374259 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 1030, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,21683.699712,top1_acc,-88.71084382067407 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17539.596288,top1_acc,-88.55757690870233 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20886.257664,top1_acc,-89.02493113275776 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,21451.309056,top1_acc,-89.00932951567765 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17654.611968,top1_acc,-88.53820117086823 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2017, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,19640.549376,top1_acc,-88.91133288050526 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23378.853888,top1_acc,-89.2327869115518 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22905.81504,top1_acc,-89.31279179142228 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22551.330816,top1_acc,-89.21655390500341 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15384.969216,top1_acc,-88.07949947474987 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18701.549568,top1_acc,-88.9400027397712 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22093.627392,top1_acc,-89.17854342528173 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16352.8704,top1_acc,-88.45552852431352 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,24260.050944,top1_acc,-89.07397405174481 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,24727.781376,top1_acc,-89.22154743564946 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 1030, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,23712.104448,top1_acc,-88.93582385583842 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 768, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22633.316352,top1_acc,-89.20287510729774 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20314.718208,top1_acc,-89.21253730668649 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22128.427008,top1_acc,-89.19624775019663 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16723.869696,top1_acc,-88.28929272368033 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21402.353664,top1_acc,-89.24558376931944 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18012.635136,top1_acc,-88.67277560369132 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21609.381888,top1_acc,-89.08430868388575 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19654.115328,top1_acc,-88.72650844672569 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18890.293248,top1_acc,-88.93672397501447 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2804, 17: 1130, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20771.241984,top1_acc,-88.85303707825535 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 768, 8: 512, 9: 768, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21440.1024,top1_acc,-88.98036297393968 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22653.370368,top1_acc,-89.09026869351375 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,25220.284416,top1_acc,-89.3723811056751 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,23751.032832,top1_acc,-89.22107152168762 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20429.733888,top1_acc,-89.16052428111963 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20921.05728,top1_acc,-88.88499608464181 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21255.487488,top1_acc,-88.86308384102888 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15310.061568,top1_acc,-88.11714102701995 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17067.737088,top1_acc,-88.5060280317851 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 768, 8: 512, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22536.585216,top1_acc,-89.23589684227954 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 2804, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21867.7248,top1_acc,-88.85877732521327 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2017, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20726.41536,top1_acc,-89.00510063655204 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17285.971968,top1_acc,-88.38835403812082 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,23105.175552,top1_acc,-89.13311664998727 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,18598.920192,top1_acc,-88.63383716820806 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21927.297024,top1_acc,-89.19145541806776 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22573.744128,top1_acc,-89.19957473273791 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,14953.218048,top1_acc,-88.10542891923794 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18318.753792,top1_acc,-88.64513055204655 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19373.359104,top1_acc,-89.11173812692141 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19015.335936,top1_acc,-88.85491708432959 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 1130, 18: 2651, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 422})])",MACs,21388.197888,top1_acc,-88.64859750122586 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,17127.309312,top1_acc,-88.46066175883578 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,23641.325568,top1_acc,-89.3670348468947 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,18469.748736,top1_acc,-88.67681320708078 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18436.718592,top1_acc,-88.82824263955982 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17284.202496,top1_acc,-88.34989761324036 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23154.130944,top1_acc,-89.17211172168805 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15132.524544,top1_acc,-87.92494064463318 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21006.58176,top1_acc,-89.18344497262537 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1030, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21967.99488,top1_acc,-88.89025157807545 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23508.025344,top1_acc,-89.40328506030262 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18625.462272,top1_acc,-88.83701108970862 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2017, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19593.363456,top1_acc,-88.85239501224218 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,19371.589632,top1_acc,-88.42330376245796 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,20055.785472,top1_acc,-88.75757425019944 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19654.705152,top1_acc,-88.87507917607954 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17354.981376,top1_acc,-88.52121124533276 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25666.19136,top1_acc,-89.35004639285032 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23960.420352,top1_acc,-89.33986476095382 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17182.752768,top1_acc,-88.47335146699747 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19540.279296,top1_acc,-88.94099989863403 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19184.615424,top1_acc,-88.99102203042422 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 1030, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,23972.806656,top1_acc,-88.93509757889635 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 422})])",MACs,22908.174336,top1_acc,-88.88471661356394 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16730.35776,top1_acc,-88.44504025832391 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18492.751872,top1_acc,-88.71500854902513 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 512, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 1130, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22130.19648,top1_acc,-88.98257596442281 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17268.277248,top1_acc,-88.59279617668939 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,23259.70944,top1_acc,-89.08227551606419 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18040.356864,top1_acc,-88.52099812685412 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16373.51424,top1_acc,-88.44521411284428 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,23722.72128,top1_acc,-89.27182721982791 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,24731.910144,top1_acc,-89.25856028700949 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16864.837632,top1_acc,-88.64632296134606 +"OrderedDict([(, {0: 768, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17539.596288,top1_acc,-88.55757690870233 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 768, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 1205, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,19757.924352,top1_acc,-88.69943017288429 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 512, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 768, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22409.773056,top1_acc,-88.97597115797173 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1030, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21477.851136,top1_acc,-89.02569015642797 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19550.306304,top1_acc,-88.83712381148057 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 384, 6: 448, 7: 768, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 2825, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17219.321856,top1_acc,-88.1937279647429 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16197.746688,top1_acc,-88.21769564051253 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19672.989696,top1_acc,-88.73912850112161 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23720.361984,top1_acc,-89.36681558247622 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17480.024064,top1_acc,-88.38860822891137 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15144.321024,top1_acc,-87.9952915936768 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22271.164416,top1_acc,-89.01234624786984 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 384, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25649.086464,top1_acc,-89.40568106397113 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18333.499392,top1_acc,-88.59236141351266 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15489.957888,top1_acc,-88.25944003555641 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 2804, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,23435.476992,top1_acc,-89.27249697427384 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 512, 6: 448, 7: 768, 8: 768, 9: 384, 10: 768, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 1130, 18: 3072, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 422})])",MACs,22592.618496,top1_acc,-88.80545308939047 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20629.0944,top1_acc,-89.11453084264666 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2830, 13: 1170, 14: 1284, 15: 2825, 16: 1205, 17: 2760, 18: 1030, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20212.678656,top1_acc,-88.53384184672409 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19267.780608,top1_acc,-88.99784840678846 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21546.27072,top1_acc,-89.0974135735609 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18815.3856,top1_acc,-88.92448650332031 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 384, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20000.93184,top1_acc,-88.90678033991429 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,19890.634752,top1_acc,-88.94582940236064 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21591.097344,top1_acc,-89.23304828754081 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16832.397312,top1_acc,-88.24891801210698 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 768, 7: 768, 8: 512, 9: 384, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19712.507904,top1_acc,-88.57754521454022 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19079.036928,top1_acc,-88.9612770978439 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26212.958208,top1_acc,-89.44950254311212 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16708.534272,top1_acc,-88.37280469831228 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27257.536512,top1_acc,-89.45153845481812 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 384, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1030, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20459.225088,top1_acc,-88.80161316214951 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,25152.454656,top1_acc,-89.19524576198147 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 1205, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,19838.140416,top1_acc,-88.72100148720888 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2017, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,20718.747648,top1_acc,-88.98233326408416 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17305.43616,top1_acc,-88.47517261478168 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,24628.10112,top1_acc,-89.24263621864249 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18890.293248,top1_acc,-88.93672397501447 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,23175.954432,top1_acc,-89.30843716506241 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2017, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15644.491776,top1_acc,-88.0757139227495 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21716.140032,top1_acc,-89.12980956182956 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17211.06432,top1_acc,-88.47157917363559 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19202.899968,top1_acc,-88.83922373697496 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17719.492608,top1_acc,-88.6112737148593 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21968.584704,top1_acc,-89.21587271441157 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 384, 6: 768, 7: 768, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 1170, 14: 3072, 15: 1218, 16: 3072, 17: 1130, 18: 3072, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,22146.711552,top1_acc,-88.70018015850859 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22422.749184,top1_acc,-89.26540321964488 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 1030, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17970.757632,top1_acc,-88.54550174252765 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20981.809152,top1_acc,-89.09603119149301 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20429.733888,top1_acc,-89.16052428111963 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,18177.196032,top1_acc,-88.60254347063348 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16386.490368,top1_acc,-88.30126288991565 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,25314.656256,top1_acc,-89.43389189707139 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 768, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 1205, 17: 2760, 18: 1030, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20584.8576,top1_acc,-88.7366452216156 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17202.806784,top1_acc,-88.46180527327684 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21027.2256,top1_acc,-88.84900918827515 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20647.378944,top1_acc,-89.05988812346625 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18586.533888,top1_acc,-88.98317473241991 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18784.124928,top1_acc,-88.75872130418485 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18881.445888,top1_acc,-88.76343966571223 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 512, 5: 384, 6: 448, 7: 448, 8: 768, 9: 768, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 2825, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,18610.126848,top1_acc,-88.34931236862937 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15867.445248,top1_acc,-88.268954577652 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,17946.574848,top1_acc,-88.65732724773994 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16834.756608,top1_acc,-88.4945430668428 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21755.068416,top1_acc,-89.01837231957491 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,20739.981312,top1_acc,-88.65821911138397 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18202.558464,top1_acc,-88.68218765953367 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20317.077504,top1_acc,-89.08279082335773 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17306.615808,top1_acc,-88.5317521149076 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17976.066048,top1_acc,-88.73361591211847 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22310.0928,top1_acc,-89.19170630420722 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16082.731008,top1_acc,-88.2549264936433 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,23989.321728,top1_acc,-89.22326584679753 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 2825, 16: 3072, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19979.108352,top1_acc,-88.66417107984887 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,24265.35936,top1_acc,-89.19661237933643 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 1030, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17772.576768,top1_acc,-88.25865560174371 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22303.014912,top1_acc,-89.36085554711813 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 1130, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19754.975232,top1_acc,-88.77772454883323 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26684.817408,top1_acc,-89.40915848709187 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16386.490368,top1_acc,-88.30126288991565 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20598.423552,top1_acc,-89.12886442577707 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,25646.727168,top1_acc,-89.36858145665404 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 256, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,27212.120064,top1_acc,-89.45682671454199 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 2804, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,23441.375232,top1_acc,-89.0650723076692 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,17454.071808,top1_acc,-88.44827314286412 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,27163.164672,top1_acc,-89.42500913149473 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15796.076544,top1_acc,-88.22145125832547 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20071.71072,top1_acc,-89.13956240570062 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21259.026432,top1_acc,-89.17571128943372 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,14858.846208,top1_acc,-87.98505326968666 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15849.160704,top1_acc,-88.1678580935225 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15448.080384,top1_acc,-88.21104738247269 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16286.810112,top1_acc,-88.31861384889945 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15961.817088,top1_acc,-88.25105311216232 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18096.979968,top1_acc,-88.67549757105012 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15386.148864,top1_acc,-88.06813806065767 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15610.871808,top1_acc,-88.04698470693238 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22067.085312,top1_acc,-89.19658765225329 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 384, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 1030, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,24809.766912,top1_acc,-89.08290387068546 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 1205, 17: 1130, 18: 3072, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,18110.54592,top1_acc,-88.27846613514103 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17527.799808,top1_acc,-88.54473391934079 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19069.599744,top1_acc,-89.01129424320581 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15878.651904,top1_acc,-88.25997824325597 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21358.706688,top1_acc,-89.14302708476951 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,23718.592512,top1_acc,-89.16771109116529 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 1205, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,21865.365504,top1_acc,-89.13759917596893 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20554.776576,top1_acc,-89.22764835128088 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21713.190912,top1_acc,-89.10998281663377 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22121.34912,top1_acc,-88.96293877484088 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19467.730944,top1_acc,-89.09047349288646 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19097.321472,top1_acc,-88.90031498075105 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,22218.67008,top1_acc,-89.2887553766039 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,15499.984896,top1_acc,-88.15626237705679 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 384, 6: 448, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15310.061568,top1_acc,-87.9737544556992 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19831.652352,top1_acc,-88.93404528419619 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 512, 5: 768, 6: 768, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,24840.43776,top1_acc,-89.20602121330367 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19569.770496,top1_acc,-88.76336682509613 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1030, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,16881.352704,top1_acc,-88.16375580628463 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,18362.400768,top1_acc,-88.40344197103393 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22422.749184,top1_acc,-89.26540321964488 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20271.661056,top1_acc,-89.15540616693896 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,19626.983424,top1_acc,-88.61520249496478 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20222.705664,top1_acc,-89.07030767205215 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16392.978432,top1_acc,-88.39409978780647 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,23882.563584,top1_acc,-88.99601083420083 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17889.951744,top1_acc,-88.67238793594434 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20741.750784,top1_acc,-89.16961420063431 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21248.4096,top1_acc,-89.24002115814947 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21957.967872,top1_acc,-89.2488951188584 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 768, 7: 448, 8: 512, 9: 768, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 1205, 17: 1130, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19174.588416,top1_acc,-88.4378216667205 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,24286.593024,top1_acc,-89.24079045912964 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,20981.809152,top1_acc,-89.2082524344035 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21371.682816,top1_acc,-89.03519079973177 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 2825, 16: 2115, 17: 2017, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17812.6848,top1_acc,-88.5465280063225 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 1030, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,21659.516928,top1_acc,-88.99708437733928 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26125.074432,top1_acc,-89.3424386209485 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,23411.884032,top1_acc,-89.26111239233504 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21139.29216,top1_acc,-89.29109342064093 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20825.505792,top1_acc,-88.94158394059062 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,22081.241088,top1_acc,-89.12378884596521 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22055.878656,top1_acc,-89.14052845657463 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,22781.952,top1_acc,-89.29329556575513 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19645.857792,top1_acc,-88.97312523264193 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21630.025728,top1_acc,-89.00144828796572 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17251.762176,top1_acc,-88.22184012692446 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16204.234752,top1_acc,-88.28733149694533 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,22347.841536,top1_acc,-89.13087078866391 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 1205, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,18629.001216,top1_acc,-88.61727414911896 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 2825, 16: 2115, 17: 2017, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17317.822464,top1_acc,-88.1932447124231 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21129.265152,top1_acc,-88.91607149467944 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,19599.261696,top1_acc,-88.7307247340656 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 512, 4: 512, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,17382.11328,top1_acc,-88.52825010882161 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,22206.283776,top1_acc,-89.08242689488996 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,23175.954432,top1_acc,-89.30843716506241 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19813.957632,top1_acc,-89.04891089747989 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 384, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,26126.843904,top1_acc,-89.17087181679831 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 2825, 16: 2115, 17: 2017, 18: 1869, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,20345.389056,top1_acc,-88.6817217665182 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17625.120768,top1_acc,-88.67614831434697 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 640, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 3072, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,20314.718208,top1_acc,-88.96707307641391 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16980.443136,top1_acc,-88.47136611456608 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21885.41952,top1_acc,-88.98841216273846 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 320, 12: 2830, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 1130, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,26057.834496,top1_acc,-89.17192541979745 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 1130, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,15144.321024,top1_acc,-87.9952915936768 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 422})])",MACs,18035.048448,top1_acc,-88.56560186042616 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2804, 17: 1130, 18: 1030, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,16140.53376,top1_acc,-88.08294525123193 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 2804, 17: 2760, 18: 2651, 19: 2628, 20: 3072, 21: 401, 22: 404, 23: 617})])",MACs,24813.89568,top1_acc,-89.3531724465978 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,19705.430016,top1_acc,-89.0458540046941 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,21075.591168,top1_acc,-89.18988391336599 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 512, 6: 448, 7: 448, 8: 768, 9: 768, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 964, 22: 404, 23: 617})])",MACs,21307.981824,top1_acc,-89.14891237381784 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,19352.715264,top1_acc,-88.90211296582737 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,23722.72128,top1_acc,-89.23045435664017 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 1170, 14: 1284, 15: 1218, 16: 1205, 17: 2760, 18: 1869, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17313.103872,top1_acc,-88.5433637499173 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 768, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 2760, 18: 1869, 19: 1809, 20: 3072, 21: 401, 22: 404, 23: 422})])",MACs,20402.01216,top1_acc,-88.89517852994445 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 512, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17067.737088,top1_acc,-88.5060280317851 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 1170, 14: 1284, 15: 1218, 16: 2115, 17: 2017, 18: 2651, 19: 1809, 20: 794, 21: 401, 22: 404, 23: 422})])",MACs,17231.70816,top1_acc,-88.49569868072055 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 384, 10: 256, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 1218, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 3072, 21: 964, 22: 404, 23: 617})])",MACs,24227.0208,top1_acc,-89.30014396573927 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 768, 5: 384, 6: 448, 7: 448, 8: 512, 9: 384, 10: 256, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 1218, 16: 2115, 17: 1130, 18: 1030, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,16804.08576,top1_acc,-88.31407774483185 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 448, 7: 448, 8: 768, 9: 768, 10: 192, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 3072, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,24065.409024,top1_acc,-89.20699414040523 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 448, 4: 640, 5: 512, 6: 448, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 2830, 13: 2099, 14: 1284, 15: 1218, 16: 3072, 17: 2760, 18: 1869, 19: 1809, 20: 3072, 21: 964, 22: 404, 23: 422})])",MACs,21637.103616,top1_acc,-89.04498265125673 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 512, 4: 768, 5: 768, 6: 768, 7: 768, 8: 512, 9: 768, 10: 768, 11: 320, 12: 2096, 13: 2099, 14: 3072, 15: 2825, 16: 2115, 17: 2760, 18: 3072, 19: 2628, 20: 794, 21: 401, 22: 404, 23: 617})])",MACs,24916.525056,top1_acc,-89.21971547404533 +"OrderedDict([(, {0: 576, 1: 448, 2: 448, 3: 448, 4: 512, 5: 768, 6: 768, 7: 448, 8: 768, 9: 384, 10: 192, 11: 320, 12: 1169, 13: 2099, 14: 1284, 15: 2825, 16: 3072, 17: 2760, 18: 2651, 19: 1809, 20: 794, 21: 964, 22: 404, 23: 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0000000000000000000000000000000000000000..0e468c07aacb7629eaa7fab34467348aa4c32d31 --- /dev/null +++ b/eftnas-s1-bert-base-squadv2/README.md @@ -0,0 +1,54 @@ +--- +license: apache-2.0 +tags: +- generated_from_trainer +datasets: +- squad_v2 +model-index: +- name: first_try_5epochs + results: [] +--- + + + +# first_try_5epochs + +This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the squad_v2 dataset. + +## Model description + +More information needed + +## Intended uses & limitations + +More information needed + +## Training and evaluation data + +More information needed + +## Training procedure + +### Training hyperparameters + +The following hyperparameters were used during training: +- learning_rate: 3e-05 +- train_batch_size: 16 +- eval_batch_size: 128 +- seed: 42 +- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 +- lr_scheduler_type: linear +- num_epochs: 8 +- mixed_precision_training: Native AMP + +### Training results + + + +### Framework versions + +- Transformers 4.29.1 +- Pytorch 1.12.1 +- Datasets 2.13.1 +- Tokenizers 0.13.3 diff --git a/eftnas-s1-bert-base-squadv2/all_results.json b/eftnas-s1-bert-base-squadv2/all_results.json new file mode 100644 index 0000000000000000000000000000000000000000..f784e18948ec6816ce4206a1a917fc8420143af4 --- /dev/null +++ b/eftnas-s1-bert-base-squadv2/all_results.json @@ -0,0 +1,25 @@ +{ + "epoch": 5.0, + "eval_HasAns_exact": 73.36369770580296, + "eval_HasAns_f1": 80.19776649258391, + "eval_HasAns_total": 5928, + "eval_NoAns_exact": 73.75946173254836, + "eval_NoAns_f1": 73.75946173254836, + "eval_NoAns_total": 5945, + "eval_best_exact": 73.56186305061905, + "eval_best_exact_thresh": 0.0, + "eval_best_f1": 76.97400486549624, + "eval_best_f1_thresh": 0.0, + "eval_exact": 73.56186305061905, + "eval_f1": 76.97400486549628, + "eval_runtime": 33.0754, + "eval_samples": 12134, + "eval_samples_per_second": 366.859, + "eval_steps_per_second": 2.872, + "eval_total": 11873, + "train_loss": 0.7438544612808089, + "train_runtime": 64410.4338, + "train_samples": 131754, + "train_samples_per_second": 10.228, + "train_steps_per_second": 0.639 +} \ No newline at end of file diff --git a/eftnas-s1-bert-base-squadv2/cache_MACs.csv b/eftnas-s1-bert-base-squadv2/cache_MACs.csv new file mode 100644 index 0000000000000000000000000000000000000000..3be8b43ed2c5c58eb3711efb4bdff655f5a33a32 --- /dev/null +++ b/eftnas-s1-bert-base-squadv2/cache_MACs.csv @@ -0,0 +1,990 @@ +"(0, 2, 0, 0, 2, 1, 1, 0, 0, 1, 1, 1, 0, 3, 1, 1, 2, 3, 3, 3, 0, 4, 4, 1)",24940.70784 +"(1, 0, 1, 1, 3, 2, 1, 0, 1, 1, 1, 1, 3, 1, 1, 2, 0, 0, 0, 2, 2, 1, 0, 4)",27755.347968 +"(1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 3, 0, 4, 4, 4, 1, 3, 0, 4)",24535.498752 +"(0, 1, 0, 0, 3, 0, 0, 1, 0, 1, 0, 0, 2, 1, 0, 2, 2, 4, 2, 2, 0, 0, 2, 1)",29316.612096 +"(1, 2, 1, 0, 2, 1, 0, 1, 0, 1, 0, 0, 4, 0, 2, 3, 3, 3, 1, 1, 2, 4, 4, 0)",25089.933312 +"(1, 0, 0, 1, 3, 0, 1, 1, 0, 1, 1, 1, 3, 3, 4, 0, 1, 2, 0, 4, 3, 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4, 3, 3, 1, 3, 4, 4, 2)",20846.149632 +"(0, 1, 1, 1, 2, 2, 1, 0, 0, 1, 0, 0, 0, 3, 1, 2, 2, 2, 4, 4, 1, 3, 4, 0)",25379.536896 +"(1, 2, 1, 1, 2, 0, 1, 0, 0, 0, 1, 1, 1, 1, 4, 2, 0, 2, 1, 2, 2, 4, 2, 3)",25467.420672 +"(1, 2, 0, 0, 2, 0, 1, 0, 1, 1, 0, 1, 4, 0, 1, 1, 1, 2, 3, 3, 4, 4, 4, 1)",23980.474368 +"(1, 2, 1, 0, 2, 0, 1, 0, 0, 1, 0, 0, 0, 3, 3, 1, 2, 2, 1, 4, 3, 4, 2, 0)",25909.788672 +"(0, 0, 0, 1, 2, 0, 1, 1, 0, 1, 0, 0, 4, 0, 4, 4, 1, 3, 3, 2, 4, 0, 4, 2)",23466.737664 +"(1, 2, 0, 0, 2, 1, 1, 0, 0, 0, 1, 0, 1, 3, 0, 0, 1, 2, 3, 4, 3, 3, 0, 0)",27272.282112 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 2, 3, 0, 3)",29320.15104 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 2, 3, 4, 3, 1, 3, 4, 4, 4)",21462.515712 +"(1, 2, 1, 0, 2, 1, 1, 0, 0, 1, 1, 1, 4, 3, 1, 2, 3, 2, 3, 3, 0, 4, 0, 1)",24517.214208 +"(1, 2, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 2, 3, 4, 2, 2, 3, 4, 4, 0, 3, 3, 3)",22583.181312 +"(0, 0, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 2, 2, 1, 1, 3, 3, 2, 4, 3)",25792.413696 +"(0, 1, 1, 1, 2, 2, 1, 1, 1, 1, 0, 0, 4, 4, 4, 3, 4, 4, 4, 4, 4, 3, 4, 2)",16889.020416 +"(1, 2, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 2, 3, 0, 1, 2, 2, 1, 0, 2, 4, 3, 0)",28389.408768 +"(0, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 4, 2, 0, 4, 3, 1, 2, 3, 0, 4)",24435.228672 +"(1, 2, 0, 0, 2, 1, 1, 1, 0, 0, 1, 0, 1, 3, 2, 2, 4, 4, 2, 4, 0, 4, 0, 0)",25650.266112 +"(1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 4, 3, 4, 4, 1, 2, 3, 2, 4, 3, 4, 1)",21923.168256 +"(0, 1, 1, 1, 3, 0, 0, 1, 0, 1, 1, 1, 1, 3, 4, 3, 2, 3, 1, 4, 2, 3, 4, 3)",21856.518144 +"(0, 1, 1, 1, 3, 1, 1, 0, 0, 1, 1, 0, 1, 4, 4, 2, 3, 4, 1, 1, 3, 4, 0, 4)",23218.42176 +"(1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 4, 3, 3, 4, 2, 1, 0, 2, 4, 3, 1)",23699.12832 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 3, 0, 1, 4, 3, 2, 2, 2, 4, 4, 3)",23976.3456 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 4, 3, 4, 4, 3, 2, 3, 2, 0, 0, 4, 2)",22117.810176 +"(1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 3, 2, 1, 4, 1, 2, 0, 1, 4, 0, 0)",29025.828864 +"(1, 0, 1, 1, 3, 0, 0, 1, 1, 1, 1, 1, 1, 3, 4, 4, 2, 4, 0, 4, 2, 2, 4, 2)",21407.66208 +"(1, 0, 1, 0, 2, 1, 1, 0, 0, 1, 0, 1, 4, 3, 4, 4, 0, 1, 2, 2, 4, 0, 4, 1)",23952.162816 +"(0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 2, 2, 3, 1, 2, 2, 2, 2, 3)",26847.608832 +"(0, 2, 0, 1, 0, 2, 1, 1, 1, 1, 0, 1, 4, 4, 4, 3, 4, 2, 4, 4, 4, 3, 4, 1)",18420.793344 +"(1, 0, 1, 1, 2, 0, 1, 0, 0, 1, 1, 1, 4, 3, 4, 4, 0, 2, 2, 2, 4, 0, 4, 3)",22172.663808 +"(1, 2, 0, 1, 2, 0, 1, 1, 1, 0, 0, 1, 1, 0, 4, 2, 1, 4, 3, 2, 2, 4, 4, 2)",23522.770944 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 0, 1, 0, 0, 3, 4, 2, 4, 1, 3, 1, 3, 4, 4, 2)",23314.563072 +"(0, 0, 0, 0, 3, 2, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 0, 4, 3, 2, 4, 4)",19924.25472 +"(1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 4, 3, 2, 4, 2, 2, 2, 0, 3, 4, 3)",21850.619904 +"(1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 3, 0, 1, 2, 2, 1, 0, 2, 4, 2, 0)",29079.502848 +"(0, 2, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 4, 4, 3, 2, 2, 2, 2, 4, 0, 3, 4, 1)",22853.910528 +"(1, 1, 0, 0, 2, 1, 0, 0, 0, 0, 1, 0, 0, 1, 4, 1, 4, 3, 1, 0, 2, 4, 0, 3)",26668.302336 +"(0, 1, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 1, 2, 0, 4, 3, 1, 2, 3, 0, 4)",24294.260736 +"(1, 2, 0, 0, 2, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 2, 3, 0, 2)",29170.335744 +"(0, 1, 0, 1, 2, 1, 1, 0, 0, 1, 0, 0, 0, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 4)",21917.85984 +"(0, 1, 1, 0, 3, 0, 0, 1, 0, 1, 1, 1, 1, 3, 4, 4, 3, 3, 1, 4, 3, 2, 4, 3)",21108.621312 +"(1, 0, 1, 1, 3, 0, 0, 1, 1, 1, 1, 1, 1, 3, 4, 4, 2, 3, 0, 4, 2, 2, 3, 2)",22088.318976 +"(1, 0, 0, 0, 2, 0, 0, 0, 0, 1, 1, 0, 2, 4, 1, 1, 2, 3, 1, 1, 0, 4, 0, 0)",29391.519744 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 0, 1, 1, 0, 4, 4, 2, 4, 2, 2, 1, 3, 3, 4, 2)",22653.370368 +"(0, 2, 0, 0, 2, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 2, 3, 4, 3, 1, 3, 4, 4, 4)",23131.127808 +"(0, 1, 1, 1, 0, 2, 1, 1, 1, 1, 0, 0, 4, 4, 1, 3, 4, 2, 4, 4, 4, 3, 4, 1)",19978.518528 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 0, 4, 3, 2, 4, 3, 0, 4)",22241.673216 +"(1, 0, 1, 1, 3, 0, 0, 1, 1, 1, 0, 1, 0, 3, 3, 1, 2, 4, 0, 0, 2, 2, 4, 2)",25117.065216 +"(0, 1, 1, 1, 2, 2, 1, 1, 1, 0, 0, 1, 1, 4, 1, 3, 1, 2, 4, 4, 2, 3, 0, 1)",24862.851072 +"(1, 2, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 2, 3, 3, 1, 2, 2, 1, 0, 1, 4, 3, 0)",27885.109248 +"(1, 1, 0, 1, 0, 2, 1, 1, 1, 0, 1, 1, 1, 4, 4, 3, 4, 4, 4, 2, 4, 3, 0, 3)",20170.801152 +"(1, 2, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 3, 2, 1, 4, 1, 2, 2, 1, 4, 0, 0)",27810.2016 +"(0, 2, 0, 1, 0, 2, 0, 1, 0, 1, 0, 0, 4, 4, 4, 3, 4, 2, 4, 4, 4, 3, 4, 1)",19553.255424 +"(1, 0, 0, 1, 2, 0, 1, 0, 1, 1, 0, 1, 4, 0, 4, 4, 1, 4, 3, 2, 4, 0, 4, 3)",21999.845376 +"(0, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 2)",15442.182144 +"(0, 0, 0, 1, 3, 2, 1, 1, 0, 1, 1, 1, 1, 4, 4, 3, 2, 4, 0, 4, 2, 3, 4, 4)",20672.151552 +"(1, 2, 0, 1, 3, 1, 0, 1, 1, 0, 0, 1, 2, 3, 4, 4, 3, 4, 4, 4, 2, 2, 4, 3)",19817.496576 +"(0, 2, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 3, 3, 2, 2, 2, 1, 0, 2, 1, 3, 3)",28854.19008 +"(1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 4, 3, 2, 1, 3, 3, 2, 0, 4, 0, 3)",23528.07936 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 4, 0, 0, 1, 1, 0, 2, 3, 0, 3)",26660.0448 +"(0, 1, 1, 1, 2, 2, 1, 1, 1, 1, 0, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 3, 4, 2)",16322.789376 +"(1, 0, 0, 1, 2, 0, 0, 1, 1, 1, 0, 0, 4, 0, 4, 4, 1, 4, 3, 1, 2, 0, 4, 2)",24043.585536 +"(1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 1, 3, 4, 4, 2, 2, 1, 4, 1, 4, 2, 0)",24865.800192 +"(0, 2, 0, 0, 0, 2, 1, 0, 0, 1, 0, 0, 2, 3, 1, 1, 2, 2, 1, 0, 2, 4, 3, 0)",28182.380544 +"(0, 2, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 2, 2, 3, 1, 0, 1, 4, 3, 0)",29083.041792 +"(1, 1, 1, 1, 3, 0, 0, 1, 0, 1, 1, 1, 1, 3, 4, 3, 2, 2, 1, 4, 2, 3, 4, 0)",23391.240192 +"(0, 0, 0, 0, 3, 1, 1, 1, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 1, 3, 2, 4, 4)",21473.722368 +"(1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 4, 3, 1, 2, 2, 1, 2, 3, 4, 0, 3)",26218.266624 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 0, 1, 4, 4, 3, 3, 4, 4, 4, 4, 4, 3, 4, 2)",16570.515456 +"(1, 1, 1, 1, 2, 1, 1, 1, 0, 1, 0, 0, 0, 3, 3, 3, 2, 2, 2, 2, 2, 4, 4, 0)",24839.847936 +"(0, 2, 0, 1, 3, 0, 1, 0, 1, 0, 1, 1, 1, 4, 0, 2, 4, 3, 2, 2, 2, 4, 4, 3)",23055.630336 +"(0, 2, 0, 1, 2, 2, 1, 0, 0, 1, 1, 1, 1, 4, 4, 4, 4, 3, 0, 4, 3, 4, 4, 2)",19296.681984 +"(1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 3, 3, 1, 2, 1, 2, 0, 1, 3, 2, 0)",27671.003136 +"(0, 1, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 1, 2, 0, 0, 3, 0, 2, 3, 0, 4)",25590.104064 +"(1, 2, 0, 1, 2, 1, 1, 0, 1, 0, 1, 0, 1, 4, 4, 2, 2, 4, 2, 4, 0, 4, 4, 3)",21955.018752 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 0, 1, 4, 4, 3, 3, 4, 4, 4, 2, 4, 3, 4, 2)",17513.054208 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 4, 1, 3, 3, 4, 4)",20051.06688 +"(0, 0, 0, 0, 2, 2, 1, 1, 0, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 3, 4, 4, 2)",17151.492096 +"(1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 3, 3, 1, 2, 1, 1, 0, 1, 3, 2, 0)",28899.606528 +"(0, 2, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 2, 3, 4, 4, 3, 4, 4, 4, 2, 3, 4, 3)",19223.543808 +"(0, 1, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 3, 2, 1, 4, 1, 2, 1, 3, 4, 0, 0)",26602.242048 +"(1, 2, 0, 1, 2, 0, 0, 0, 0, 1, 0, 0, 0, 3, 3, 0, 0, 1, 1, 0, 1, 3, 0, 0)",30542.856192 +"(1, 0, 0, 0, 3, 1, 0, 1, 0, 0, 0, 1, 2, 3, 4, 4, 3, 4, 4, 4, 2, 2, 4, 3)",20855.586816 +"(0, 2, 0, 0, 0, 2, 1, 1, 0, 1, 1, 1, 4, 3, 4, 3, 4, 2, 4, 4, 4, 3, 4, 0)",19273.678848 +"(0, 2, 0, 1, 2, 0, 0, 0, 0, 0, 1, 0, 0, 3, 0, 2, 0, 4, 2, 1, 2, 4, 4, 4)",25811.877888 +"(0, 1, 1, 1, 2, 2, 1, 0, 1, 1, 0, 1, 0, 4, 1, 2, 0, 4, 4, 1, 4, 3, 0, 4)",23394.189312 +"(0, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 3, 4, 2)",15756.558336 +"(1, 1, 0, 1, 2, 2, 1, 1, 1, 1, 0, 1, 4, 4, 4, 2, 4, 4, 4, 1, 3, 4, 4, 2)",18291.032064 +"(0, 1, 0, 1, 2, 1, 1, 0, 0, 1, 0, 0, 0, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 2)",22291.218432 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 4, 1, 1, 2, 3, 0, 3)",28056.158208 +"(0, 1, 0, 1, 0, 2, 1, 0, 0, 1, 1, 1, 1, 4, 4, 4, 4, 3, 0, 2, 3, 3, 0, 2)",22358.458368 +"(1, 1, 1, 1, 2, 1, 1, 1, 1, 0, 1, 1, 1, 4, 3, 2, 1, 2, 2, 4, 0, 3, 0, 3)",24392.761344 +"(0, 2, 0, 1, 2, 2, 1, 1, 1, 1, 0, 1, 4, 4, 4, 3, 4, 4, 3, 4, 4, 4, 4, 2)",16742.744064 +"(0, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 0, 4, 4, 2, 4, 4)",18214.944768 +"(1, 2, 1, 0, 0, 2, 1, 0, 1, 1, 1, 1, 2, 3, 4, 1, 2, 2, 2, 0, 2, 4, 3, 3)",23272.685568 +"(1, 2, 0, 1, 3, 2, 0, 1, 0, 0, 0, 0, 4, 4, 4, 3, 4, 2, 4, 4, 4, 2, 4, 1)",20147.208192 +"(1, 2, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 4, 4, 2, 4, 3, 3, 0, 1, 4, 4, 2)",23269.736448 +"(1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 4, 4, 2, 2, 2, 1, 0, 2, 4, 3, 3)",23817.682944 +"(0, 2, 0, 1, 3, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 0, 4, 3, 2, 4, 4)",18886.16448 +"(1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 4, 2, 1, 4, 1, 2, 0, 1, 4, 0, 1)",28181.200896 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 1, 4, 4, 2, 0, 2, 3, 2, 2, 3, 0, 0)",25318.785024 +"(0, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 2, 3, 4, 2)",17222.8608 +"(0, 2, 0, 1, 2, 2, 1, 0, 0, 1, 0, 0, 1, 4, 4, 4, 4, 3, 0, 4, 3, 4, 4, 2)",20429.144064 +"(0, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 3, 3, 3, 4, 3, 4, 4, 3, 4, 4)",18750.50496 +"(0, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4)",15068.823552 +"(1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 4, 3, 2, 2, 4, 2, 2, 0, 3, 0, 3)",25170.149376 +"(0, 1, 1, 1, 2, 2, 1, 1, 1, 1, 0, 1, 1, 4, 4, 2, 3, 4, 4, 4, 4, 3, 4, 2)",18473.28768 +"(1, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 3, 3, 1, 2, 2, 0, 0, 1, 4, 2, 0)",28897.247232 +"(0, 2, 0, 1, 0, 2, 0, 1, 0, 1, 1, 0, 4, 4, 4, 3, 4, 2, 4, 4, 4, 3, 4, 1)",18987.024384 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 4, 3, 4, 4, 3, 1, 3, 4, 4, 4)",18867.879936 +"(0, 2, 1, 1, 2, 2, 1, 0, 0, 1, 1, 1, 1, 4, 4, 4, 4, 3, 1, 4, 3, 4, 4, 2)",18974.63808 +"(0, 2, 1, 1, 2, 2, 1, 1, 1, 1, 0, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 3, 4, 1)",17015.242752 +"(0, 2, 0, 1, 0, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 2, 4, 4, 4, 4, 4, 2)",16847.732736 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 2, 3, 4, 3, 1, 3, 3, 4, 4)",21682.520064 +"(0, 1, 0, 1, 2, 1, 1, 1, 0, 1, 1, 0, 0, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 2)",21347.500032 +"(0, 1, 0, 1, 2, 1, 1, 0, 0, 1, 0, 0, 4, 3, 4, 1, 4, 1, 4, 4, 1, 3, 4, 2)",21773.35296 +"(1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 3, 3, 1, 2, 1, 2, 0, 1, 3, 0, 0)",28723.838976 +"(0, 1, 1, 1, 2, 2, 1, 1, 1, 1, 0, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 3, 4, 1)",17109.614592 +"(1, 1, 1, 0, 2, 2, 1, 1, 1, 1, 0, 0, 4, 4, 3, 3, 4, 4, 0, 3, 1, 3, 4, 2)",20657.405952 +"(1, 2, 0, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 1, 4, 3, 4, 4, 4, 4, 4, 4, 0, 4)",17863.409664 +"(0, 2, 0, 1, 0, 2, 1, 0, 0, 1, 1, 1, 1, 4, 4, 4, 4, 3, 0, 2, 3, 4, 0, 2)",22044.082176 +"(1, 2, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 2, 3, 0, 0)",31443.51744 +"(0, 1, 0, 1, 2, 2, 1, 0, 0, 1, 1, 1, 1, 4, 4, 4, 3, 3, 0, 4, 3, 4, 4, 2)",19873.529856 +"(0, 2, 1, 1, 2, 2, 1, 0, 0, 1, 0, 1, 3, 4, 4, 3, 4, 4, 3, 1, 3, 4, 4, 4)",19056.623616 +"(0, 1, 1, 1, 2, 2, 1, 0, 1, 1, 1, 1, 4, 3, 3, 1, 2, 4, 4, 4, 4, 4, 4, 0)",19681.837056 +"(0, 1, 0, 1, 2, 1, 1, 0, 0, 1, 1, 0, 4, 4, 4, 3, 4, 1, 1, 4, 2, 3, 4, 2)",20816.068608 +"(0, 1, 1, 1, 2, 1, 1, 1, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 4, 2, 3, 3, 4, 2)",19623.44448 +"(1, 2, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 4, 3, 2, 3, 4, 3, 0, 3, 4, 4, 4)",20661.53472 +"(0, 1, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 1, 3, 0, 4, 3, 0, 4, 3, 0, 4)",22976.59392 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 4, 1, 3, 4, 4, 4)",19831.062528 +"(0, 1, 1, 1, 2, 1, 1, 0, 1, 1, 0, 1, 4, 4, 4, 3, 4, 4, 3, 4, 2, 3, 4, 2)",18166.5792 +"(1, 1, 1, 0, 1, 2, 1, 1, 1, 0, 1, 0, 1, 4, 2, 3, 4, 4, 2, 0, 4, 4, 0, 0)",24141.49632 +"(1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 4, 3, 2, 1, 3, 3, 2, 0, 4, 2, 3)",22475.24352 +"(0, 2, 1, 1, 2, 2, 1, 1, 1, 1, 0, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 3, 4, 2)",16228.417536 +"(1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 3, 3, 1, 2, 2, 4, 0, 4, 4, 2, 0)",25239.748608 +"(0, 2, 1, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 0, 0, 0, 1, 1, 0, 2, 3, 4, 3)",26525.564928 +"(1, 1, 0, 1, 2, 1, 1, 0, 1, 0, 1, 1, 1, 4, 3, 1, 2, 1, 2, 4, 3, 3, 4, 3)",22566.66624 +"(1, 1, 0, 0, 2, 1, 1, 0, 0, 1, 1, 0, 1, 3, 2, 1, 4, 1, 2, 0, 1, 4, 0, 3)",26902.462464 +"(0, 2, 0, 1, 3, 0, 1, 0, 0, 1, 1, 1, 1, 4, 4, 1, 4, 3, 1, 1, 3, 4, 4, 4)",21828.796416 +"(0, 1, 0, 1, 2, 1, 1, 1, 1, 1, 1, 0, 4, 4, 4, 3, 4, 4, 4, 4, 4, 3, 4, 2)",16700.276736 +"(1, 2, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 4, 4, 3, 4, 2, 0, 0, 1, 4, 2, 2)",24657.59232 +"(1, 2, 1, 1, 2, 1, 0, 1, 1, 1, 1, 1, 0, 4, 4, 0, 0, 4, 3, 0, 2, 3, 0, 3)",23066.836992 +"(1, 1, 1, 1, 2, 2, 1, 0, 1, 1, 0, 1, 4, 4, 3, 3, 4, 4, 4, 1, 4, 3, 4, 4)",17940.676608 +"(0, 1, 1, 1, 2, 0, 1, 0, 0, 1, 1, 0, 0, 3, 4, 1, 2, 1, 2, 1, 1, 3, 2, 0)",27480.489984 +"(0, 1, 1, 1, 2, 2, 1, 1, 1, 1, 0, 1, 4, 4, 4, 2, 4, 0, 4, 4, 2, 3, 4, 2)",18936.29952 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 0, 1, 0, 3, 4, 1, 2, 4, 2, 0, 1, 3, 4, 1)",23958.061056 +"(1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 4, 4, 2, 2, 2, 1, 0, 2, 4, 3, 2)",24611.586048 +"(1, 2, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 4, 3, 1, 2, 1, 2, 2, 3, 3, 0, 3)",25502.810112 +"(0, 2, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 4, 4, 3, 3, 4, 1, 4, 4, 4, 3, 2, 0)",20728.184832 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 3, 3, 4, 4, 4, 2, 4, 3, 4, 3)",16719.151104 +"(1, 1, 0, 1, 2, 1, 1, 0, 0, 1, 1, 0, 0, 4, 4, 0, 0, 1, 1, 0, 2, 3, 0, 3)",26471.30112 +"(0, 2, 0, 1, 2, 2, 1, 1, 0, 1, 1, 1, 0, 4, 4, 3, 3, 4, 3, 1, 3, 4, 4, 2)",19938.410496 +"(0, 0, 0, 0, 2, 1, 1, 0, 0, 1, 1, 1, 4, 4, 4, 2, 4, 4, 4, 4, 3, 4, 2, 4)",18247.385088 +"(0, 1, 1, 1, 2, 1, 1, 1, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 0, 2, 3, 2, 4, 2)",21469.5936 +"(0, 1, 0, 1, 2, 2, 1, 1, 0, 1, 1, 1, 0, 4, 1, 3, 3, 4, 3, 1, 3, 4, 0, 4)",22455.779328 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 0, 0, 0, 4, 4, 0, 0, 1, 1, 0, 2, 3, 0, 3)",27226.27584 +"(0, 2, 0, 1, 2, 2, 1, 0, 0, 1, 0, 1, 3, 4, 4, 2, 4, 4, 3, 1, 3, 4, 4, 2)",20147.208192 +"(0, 0, 0, 0, 2, 2, 1, 1, 0, 1, 1, 1, 1, 4, 4, 1, 2, 1, 4, 2, 3, 4, 4, 2)",22152.019968 +"(0, 1, 1, 1, 2, 0, 1, 0, 0, 1, 1, 1, 0, 3, 4, 2, 3, 4, 4, 1, 3, 3, 4, 4)",20927.545344 +"(0, 1, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 1, 2, 0, 1, 1, 0, 3, 3, 4, 3)",26110.328832 +"(0, 1, 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1, 4, 4, 4, 3, 4, 4, 4, 1, 3, 4, 4, 4)",17200.447488 +"(1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 4, 4, 3, 3, 4, 4, 2, 4, 3, 3, 0, 3)",20313.53856 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 0, 0, 4, 4, 1, 2, 1, 2, 1, 1, 3, 2, 0)",26604.01152 +"(1, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 1, 3, 0, 3, 4, 4, 1, 2, 4, 0, 4)",23553.441792 +"(0, 1, 0, 1, 2, 2, 1, 0, 0, 1, 1, 1, 1, 4, 4, 4, 3, 3, 0, 4, 3, 4, 4, 1)",20660.355072 +"(0, 1, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 4, 4, 1, 3, 4, 4, 3, 1, 2, 3, 4, 4)",19773.259776 +"(1, 2, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 4, 0, 0, 4, 4, 0, 3, 3, 0, 0)",25951.076352 +"(1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 3, 4, 4, 2, 1, 4, 3, 2, 0, 4, 4, 3)",20218.576896 +"(0, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 0, 4, 4, 2, 4, 4, 3, 1, 3, 3, 4, 4)",19359.203328 +"(1, 2, 0, 1, 2, 1, 0, 0, 1, 1, 1, 1, 1, 4, 3, 1, 2, 1, 2, 2, 3, 3, 0, 3)",24653.463552 +"(0, 1, 0, 1, 2, 2, 1, 1, 1, 1, 0, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 2)",16385.900544 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 2, 4, 0, 3)",29100.146688 +"(1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 4, 4, 3, 2, 2, 1, 4, 2, 3, 3, 0, 3)",22549.561344 +"(1, 1, 0, 1, 3, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 0, 4, 3, 4, 4, 4)",17977.83552 +"(0, 2, 0, 1, 2, 2, 1, 1, 0, 1, 0, 1, 0, 4, 3, 3, 3, 4, 3, 1, 3, 3, 4, 2)",21255.487488 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 4, 1, 1, 0, 2, 3, 0, 3)",28083.290112 +"(0, 2, 1, 1, 2, 1, 1, 1, 0, 1, 1, 1, 0, 4, 1, 3, 3, 4, 4, 4, 3, 4, 4, 4)",18739.298304 +"(0, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 4, 3, 2, 1, 3, 3, 2, 0, 2, 0, 3)",24436.40832 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 2, 4, 4, 4, 2)",16195.977216 +"(1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 3, 2, 1, 0, 1, 2, 0, 1, 4, 0, 0)",30262.689792 +"(0, 1, 1, 1, 2, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 1, 4, 3, 4, 4)",18012.045312 +"(1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 2, 2, 3, 0, 3)",29142.614016 +"(0, 1, 1, 1, 2, 1, 1, 1, 0, 1, 1, 1, 3, 4, 4, 3, 4, 4, 3, 4, 2, 4, 4, 2)",17841.586176 +"(0, 1, 0, 1, 2, 2, 0, 0, 0, 1, 1, 1, 4, 4, 4, 0, 0, 4, 1, 0, 4, 3, 4, 4)",21225.406464 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 2, 3, 4, 4, 1, 3, 4, 4, 4)",21011.300352 +"(0, 1, 0, 1, 3, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 0, 4, 3, 3, 4, 4)",18480.955392 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 0, 1, 4, 4, 3, 3, 4, 4, 4, 2, 4, 3, 4, 3)",17285.382144 +"(0, 2, 1, 1, 2, 2, 1, 0, 0, 1, 0, 1, 3, 4, 4, 3, 4, 4, 3, 1, 3, 3, 4, 4)",19276.627968 +"(1, 2, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 4, 3, 1, 2, 1, 2, 2, 3, 3, 0, 3)",24842.207232 +"(0, 1, 0, 0, 3, 1, 1, 0, 1, 1, 1, 0, 1, 4, 4, 1, 3, 4, 4, 0, 1, 3, 0, 0)",25263.341568 +"(0, 2, 0, 1, 2, 2, 1, 1, 0, 1, 0, 1, 4, 4, 4, 3, 4, 4, 1, 0, 4, 4, 4, 3)",19057.803264 +"(1, 1, 0, 1, 3, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 0, 1, 3, 4, 4, 4)",19343.867904 +"(0, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 0, 4, 3, 1, 2, 3, 4, 2)",22060.007424 +"(1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 3, 2, 1, 0, 1, 1, 0, 1, 3, 0, 0)",31145.066496 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1, 1, 1, 0, 1, 4, 4, 4, 3, 4, 4, 4, 4, 3, 4, 4, 4)",15834.415104 +"(0, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 4, 3, 4, 4, 3, 1, 3, 4, 4, 4)",18584.764416 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 0, 0, 4, 4, 0, 0, 1, 2, 0, 2, 4, 0, 3)",25777.668096 +"(0, 1, 1, 1, 2, 2, 1, 1, 1, 1, 0, 1, 0, 4, 4, 2, 4, 4, 4, 2, 4, 3, 4, 2)",18941.607936 +"(0, 2, 1, 1, 2, 2, 1, 1, 1, 1, 0, 1, 4, 4, 4, 2, 4, 4, 4, 4, 4, 3, 4, 4)",16289.169408 +"(0, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 3, 4, 2)",15662.186496 +"(1, 2, 0, 1, 2, 1, 0, 1, 0, 1, 0, 0, 0, 4, 4, 0, 0, 4, 3, 0, 2, 3, 0, 3)",24765.530112 +"(0, 1, 0, 1, 2, 1, 1, 1, 1, 1, 1, 0, 4, 4, 4, 3, 3, 4, 3, 4, 3, 3, 4, 2)",18022.07232 +"(0, 1, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 3, 3, 4, 4, 2, 1, 3, 4, 4, 4)",19970.260992 +"(1, 2, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 2, 3, 0, 0)",32009.74848 +"(0, 1, 0, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 0, 4, 2, 4, 4, 4)",18982.305792 +"(0, 1, 1, 1, 2, 2, 0, 1, 1, 1, 0, 1, 4, 4, 0, 0, 4, 4, 4, 4, 4, 3, 4, 2)",18480.365568 +"(0, 2, 0, 1, 2, 2, 1, 0, 0, 1, 1, 1, 0, 4, 4, 3, 3, 1, 1, 1, 3, 4, 4, 2)",22399.156224 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 2, 4, 4, 4, 1, 4, 3, 4, 4)",20360.72448 +"(1, 2, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 4, 4, 1, 2, 1, 3, 2, 3, 3, 0, 3)",24211.685376 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 1, 3, 4, 4, 4)",16634.216448 +"(1, 1, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 3, 4, 2)",16218.390528 +"(0, 1, 1, 1, 2, 1, 1, 1, 1, 1, 0, 1, 0, 4, 4, 2, 4, 4, 3, 1, 3, 4, 4, 4)",19705.430016 +"(0, 1, 0, 1, 3, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 0, 4, 3, 4, 4, 4)",18260.95104 +"(0, 1, 1, 1, 2, 1, 0, 0, 0, 1, 1, 1, 0, 4, 4, 0, 0, 4, 1, 4, 2, 4, 4, 3)",21722.038272 +"(0, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 0, 4, 3, 1, 2, 3, 0, 2)",23676.125184 +"(0, 1, 0, 1, 2, 1, 0, 0, 0, 1, 1, 1, 0, 4, 4, 1, 3, 1, 4, 1, 3, 3, 0, 3)",23830.659072 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 0, 4, 3, 1, 2, 3, 4, 4)",21781.020672 +"(0, 2, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 4, 4, 4, 2, 4, 1, 4, 4, 4, 3, 0, 4)",20830.814208 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 0, 4, 1, 3, 4, 4, 4, 1, 4, 3, 0, 2)",20878.000128 +"(1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 3, 2, 1, 0, 1, 2, 0, 1, 4, 0, 0)",30828.920832 +"(0, 1, 1, 1, 2, 2, 1, 0, 0, 1, 1, 1, 0, 4, 4, 3, 3, 4, 4, 4, 3, 4, 4, 2)",18309.906432 +"(0, 2, 1, 1, 3, 2, 1, 0, 1, 1, 1, 1, 1, 4, 4, 1, 2, 4, 4, 4, 4, 3, 4, 4)",18403.098624 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 4, 2, 3, 4, 3, 1, 2, 4, 4, 2)",20501.692416 +"(0, 2, 1, 1, 3, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 4, 4, 3, 1, 2, 3, 4, 2)",20453.916672 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 1, 3, 3, 4, 4)",16854.2208 +"(0, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 3, 4, 4)",15288.827904 +"(1, 2, 0, 1, 2, 1, 1, 1, 0, 1, 1, 0, 3, 4, 4, 3, 4, 1, 3, 0, 2, 3, 0, 2)",22779.592704 +"(0, 1, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 1, 2, 0, 4, 3, 1, 2, 3, 4, 4)",22678.142976 +"(1, 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1, 0, 0, 4, 4, 0, 0, 4, 1, 0, 2, 3, 0, 3)",25716.3264 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 4, 3, 3, 4, 3, 4, 2, 4, 4, 2)",18701.549568 +"(0, 1, 1, 1, 2, 2, 1, 1, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 4, 2, 3, 4, 4, 4)",18935.709696 +"(1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 4, 4, 1, 2, 1, 0, 4, 3, 3, 0, 3)",23881.383936 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 2, 0, 4, 3, 1, 2, 3, 0, 4)",24577.376256 +"(1, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 3, 1, 4, 1, 3, 4, 4, 4)",20774.780928 +"(0, 1, 1, 1, 2, 1, 1, 1, 0, 1, 1, 1, 0, 4, 4, 3, 4, 4, 4, 1, 3, 4, 4, 2)",18910.347264 +"(1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 4, 4, 0, 0, 1, 1, 0, 2, 3, 0, 3)",27603.7632 +"(0, 2, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 4, 4, 1, 2, 1, 3, 2, 3, 3, 1, 3)",24360.321024 +"(1, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 1, 4, 3, 2, 2, 1, 2, 2, 3, 3, 0, 3)",24145.625088 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 3, 4)",14982.119424 +"(1, 2, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 4, 4, 1, 3, 4, 3, 2, 3, 3, 0, 3)",21868.314624 +"(0, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 4)",19841.67936 +"(0, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 2, 3, 4, 2)",17662.869504 +"(0, 2, 0, 1, 2, 2, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 0, 4, 3, 4, 2, 3, 4, 2)",20599.6032 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 0, 0, 4, 4, 4, 2, 3, 0, 4)",19447.087104 +"(1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 3, 2, 1, 0, 1, 2, 0, 0, 4, 0, 0)",30308.10624 +"(1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 4, 3, 1, 4, 1, 2, 2, 4, 3, 3, 3)",21907.243008 +"(1, 1, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 1, 4, 0, 0, 1, 1, 0, 2, 3, 0, 3)",28216.000512 +"(1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 4, 4, 1, 2, 1, 2, 2, 3, 4, 4, 3)",22286.49984 +"(0, 1, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 4, 3, 4, 2)",16962.748416 +"(0, 1, 0, 1, 2, 2, 1, 1, 0, 1, 1, 1, 0, 4, 4, 2, 0, 4, 3, 1, 3, 3, 4, 2)",21433.024512 +"(1, 1, 0, 1, 2, 1, 0, 0, 1, 1, 1, 1, 1, 4, 3, 1, 2, 1, 2, 2, 3, 3, 0, 3)",24747.835392 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 0, 1, 0, 4, 4, 4, 0, 1, 1, 0, 2, 3, 0, 3)",25442.05824 +"(0, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 2, 4, 0, 3)",29383.262208 +"(1, 2, 1, 1, 2, 2, 1, 0, 1, 1, 0, 1, 4, 4, 4, 3, 4, 4, 4, 4, 3, 4, 4, 2)",16490.889216 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 4, 2, 3, 4, 3, 1, 4, 4, 4, 4)",19207.61856 +"(0, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 1, 4, 4, 4, 4)",16529.227776 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 4, 3, 4, 1, 1, 0, 4, 4, 3, 3)",22195.07712 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 0, 1, 1, 4, 4, 4, 3, 2, 4, 4, 4, 3, 4, 0, 4)",18388.942848 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 0, 0, 0, 1, 0, 0, 2, 4, 0, 3)",27677.4912 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 3, 2, 3, 4, 3, 1, 2, 3, 0, 2)",23057.399808 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 1, 3, 4, 4, 4)",16539.844608 +"(1, 1, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 3, 4, 4, 4, 3, 4, 4, 4)",16222.519296 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 3, 4, 2)",16124.018688 +"(1, 2, 1, 1, 3, 2, 0, 1, 1, 1, 1, 0, 1, 4, 4, 0, 3, 4, 4, 4, 4, 3, 4, 4)",18153.013248 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4)",14785.708032 +"(0, 2, 1, 1, 2, 1, 1, 1, 0, 1, 1, 0, 0, 1, 4, 2, 0, 4, 3, 2, 3, 3, 0, 2)",24087.232512 +"(1, 1, 1, 1, 2, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 2, 4, 4, 2, 3, 4, 4, 2)",17899.978752 +"(0, 2, 1, 1, 2, 1, 0, 0, 0, 1, 0, 1, 0, 4, 4, 0, 0, 4, 1, 1, 2, 3, 0, 2)",25623.724032 +"(1, 1, 0, 1, 2, 1, 0, 0, 0, 1, 1, 1, 4, 4, 4, 3, 4, 1, 1, 4, 2, 3, 4, 2)",20249.837568 +"(0, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 3, 3, 4, 4)",16851.27168 +"(0, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 1, 4, 4, 4, 4, 0, 4)",17911.775232 +"(1, 1, 0, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 0, 4, 3, 4, 3, 4, 4, 2)",17604.476928 +"(1, 1, 0, 0, 2, 1, 0, 0, 0, 1, 1, 1, 0, 4, 0, 0, 3, 1, 0, 0, 2, 4, 4, 3)",25126.5024 +"(1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 4, 3, 1, 4, 1, 2, 2, 4, 3, 0, 3)",23610.064896 +"(1, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 0, 0, 4, 4, 2, 3, 1, 3, 0, 3, 3, 4, 3)",22100.70528 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 0, 0, 4, 4, 0, 0, 4, 3, 0, 3, 3, 0, 3)",22628.59776 +"(0, 1, 1, 1, 3, 1, 1, 1, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 4, 2, 4, 3, 4, 2)",19140.968448 +"(1, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 1, 4, 3, 2, 2, 4, 2, 2, 3, 3, 4, 3)",21302.673408 +"(0, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 4, 3, 4, 4, 3, 1, 3, 3, 4, 4)",18804.768768 +"(1, 1, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 4, 0, 0, 1, 1, 0, 2, 3, 0, 3)",26754.41664 +"(0, 2, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 4, 3, 1, 2, 1, 2, 2, 3, 3, 0, 3)",25133.580288 +"(0, 2, 1, 1, 2, 1, 1, 0, 0, 1, 0, 1, 0, 4, 4, 0, 0, 4, 3, 1, 3, 4, 4, 4)",21742.092288 +"(1, 1, 0, 0, 2, 1, 1, 1, 0, 0, 1, 0, 0, 4, 4, 1, 0, 1, 2, 0, 4, 4, 0, 0)",26868.842496 +"(1, 2, 0, 1, 2, 1, 1, 1, 1, 1, 1, 1, 3, 4, 4, 3, 3, 4, 3, 4, 2, 4, 0, 4)",19189.334016 +"(1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 4, 3, 0, 0, 1, 1, 0, 2, 3, 0, 3)",27002.14272 +"(1, 2, 1, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 1, 4, 0, 0, 1, 1, 0, 2, 4, 4, 3)",25719.27552 +"(0, 2, 1, 1, 2, 1, 1, 1, 0, 1, 1, 1, 0, 4, 4, 2, 4, 4, 3, 2, 3, 3, 4, 2)",19497.811968 +"(1, 2, 1, 0, 3, 1, 0, 1, 1, 1, 1, 1, 0, 4, 0, 3, 0, 4, 3, 0, 2, 3, 0, 2)",24005.8368 +"(0, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 0, 0, 4, 4, 0, 3, 4, 3, 0, 2, 4, 4, 2)",21939.093504 +"(0, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 0, 4, 4, 2, 4, 4, 0, 4, 3, 3, 4, 4)",18888.523776 +"(1, 1, 1, 0, 1, 2, 1, 1, 0, 1, 1, 0, 4, 3, 2, 1, 0, 1, 4, 0, 3, 4, 0, 4)",24089.001984 +"(0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 1, 1, 0, 4, 0, 3, 4, 4, 0, 4, 2, 4, 0, 4)",22714.12224 +"(1, 2, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 1, 4, 4, 3, 1, 3, 3, 0, 4)",20429.733888 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 2, 3, 4, 4, 1, 3, 3, 4, 4)",21231.304704 +"(1, 1, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 4, 0, 0, 1, 1, 0, 2, 3, 0, 2)",26982.088704 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 3, 4)",15076.491264 +"(1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 2, 4, 4, 3, 1, 3, 3, 4, 4)",19067.830272 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 3, 4, 4, 3, 4, 1, 1, 0, 2, 3, 0, 3)",24068.947968 +"(1, 2, 1, 1, 1, 2, 1, 0, 1, 1, 1, 1, 4, 3, 2, 3, 4, 4, 4, 4, 1, 4, 3, 4)",18375.96672 +"(0, 2, 1, 1, 2, 2, 1, 0, 0, 1, 1, 1, 4, 4, 3, 2, 4, 4, 4, 1, 4, 3, 4, 2)",18653.773824 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 1, 4, 4, 1, 2, 1, 2, 2, 3, 3, 0, 3)",24971.968512 +"(1, 2, 0, 0, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 0, 3, 4, 4, 4, 1, 3, 4, 0, 4)",19920.715776 +"(0, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 3, 4, 4, 4, 4, 4, 4, 4)",15551.299584 +"(1, 1, 0, 1, 2, 2, 1, 0, 0, 1, 1, 0, 4, 1, 4, 0, 4, 1, 0, 4, 3, 4, 4, 3)",21351.6288 +"(1, 1, 0, 1, 2, 1, 0, 0, 0, 1, 1, 1, 3, 4, 4, 2, 0, 1, 1, 1, 2, 3, 0, 3)",25222.643712 +"(0, 1, 0, 1, 3, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 3, 1, 3, 3, 4, 4)",18951.634944 +"(1, 2, 0, 1, 2, 1, 1, 0, 1, 0, 1, 1, 0, 4, 4, 3, 4, 4, 2, 1, 1, 4, 4, 0)",22713.532416 +"(1, 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1, 1, 1, 1, 4, 4, 4, 3, 3, 4, 3, 1, 4, 4, 4, 4)",17746.034688 +"(0, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 0, 4, 4, 3, 4, 4, 3, 1, 3, 3, 4, 4)",18925.092864 +"(0, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 2)",20781.268992 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 3, 2, 3, 4, 3, 1, 2, 3, 0, 3)",22829.727744 +"(1, 2, 1, 1, 2, 1, 0, 1, 0, 1, 1, 0, 0, 4, 4, 0, 0, 1, 1, 0, 2, 3, 0, 3)",25999.44192 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 0, 1, 0, 0, 4, 1, 2, 3, 4, 2, 1, 3, 3, 0, 0)",26516.717568 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 4, 1, 4, 0, 2, 4, 0, 3)",25997.672448 +"(0, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 3)",15214.51008 +"(1, 1, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 4, 3, 4, 2)",15830.286336 +"(1, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 0, 0, 4, 4, 2, 3, 1, 3, 0, 3, 3, 4, 2)",22328.377344 +"(1, 1, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 4, 0, 0)",31142.7072 +"(0, 1, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 4, 0, 0, 1, 4, 0, 3, 3, 0, 3)",25197.28128 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 3, 4, 2)",16218.390528 +"(0, 1, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 0, 4, 4, 3, 3, 4, 3, 4, 3, 3, 4, 2)",18226.151424 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 0, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4)",15351.939072 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 1, 3, 3, 4, 3)",17262.379008 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 3, 2, 0, 4, 3, 1, 2, 3, 0, 2)",24490.082304 +"(1, 2, 0, 1, 2, 1, 1, 1, 1, 1, 0, 1, 4, 4, 4, 3, 2, 4, 2, 4, 3, 4, 4, 3)",18130.010112 +"(1, 2, 1, 1, 2, 2, 1, 1, 0, 1, 1, 0, 1, 4, 4, 3, 4, 4, 2, 2, 4, 4, 0, 4)",20356.005888 +"(0, 2, 1, 1, 2, 1, 1, 1, 0, 1, 1, 1, 3, 4, 4, 3, 4, 4, 3, 2, 3, 4, 4, 4)",17783.783424 +"(1, 2, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 4, 3, 1, 2, 1, 2, 2, 3, 3, 0, 2)",25069.879296 +"(1, 2, 0, 1, 3, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 3, 4, 2)",16784.621568 +"(1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 3, 2, 1, 4, 1, 3, 0, 1, 4, 4, 4)",24191.63136 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 0, 4, 4, 4, 3, 0, 4, 0, 4, 4, 4, 3, 4)",18217.893888 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 3, 4, 4)",15750.660096 +"(0, 2, 1, 1, 2, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 3, 4, 3, 1, 3, 4, 4, 4)",18134.13888 +"(0, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 3)",20270.481408 +"(1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 3, 2, 1, 0, 1, 2, 0, 2, 4, 0, 3)",28353.429504 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 1, 0, 4, 4, 1, 3, 1, 1, 1, 2, 3, 0, 3)",25293.422592 +"(1, 1, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 2, 4, 4, 4, 2)",16101.605376 +"(1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 1, 3, 3, 4, 4)",17833.918464 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 3, 4, 4, 4)",15173.812224 +"(0, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 4, 3, 3, 4, 2)",19132.121088 +"(0, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 3, 4, 4, 2, 3, 4, 3, 1, 2, 3, 4, 2)",20344.209408 +"(1, 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1, 1, 4, 4, 4, 3, 4, 4, 3, 1, 3, 3, 4, 2)",17490.051072 +"(1, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 0, 0, 4, 4, 0, 0, 1, 1, 0, 2, 3, 0, 3)",26093.81376 +"(1, 2, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 4, 3, 1, 2, 1, 2, 2, 3, 4, 0, 2)",23906.156544 +"(0, 1, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 3, 2, 3, 4, 3, 1, 2, 3, 0, 2)",23838.326784 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 0, 1, 0, 4, 4, 2, 3, 4, 4, 1, 3, 4, 4, 4)",20397.293568 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 0, 0, 0, 1, 0, 0, 2, 3, 0, 3)",28180.611072 +"(0, 1, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 2, 3, 4, 3, 1, 3, 3, 4, 4)",21965.635584 +"(1, 2, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 4, 3, 1, 4, 1, 2, 1, 3, 3, 0, 3)",24044.17536 +"(1, 2, 0, 1, 2, 2, 1, 0, 1, 1, 1, 1, 0, 4, 4, 3, 3, 4, 3, 0, 4, 4, 4, 3)",19171.049472 +"(1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 3, 2, 0, 4, 1, 1, 0, 1, 4, 0, 0)",29430.448128 +"(1, 2, 0, 0, 2, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 4, 4, 4, 0, 2, 4, 0, 3)",24393.351168 +"(1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 3, 2, 1, 0, 1, 2, 0, 2, 4, 4, 3)",26454.196224 +"(0, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 4, 3, 3, 4, 4)",17317.23264 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 4, 2, 3, 1, 3, 0, 3, 3, 4, 3)",22666.93632 +"(1, 2, 0, 1, 2, 2, 0, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 3, 3, 4)",16145.842176 +"(0, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 3, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 4)",19060.752384 +"(1, 1, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 1, 4, 0, 0, 1, 1, 0, 2, 4, 0, 3)",27712.88064 +"(0, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 3, 2, 3, 4, 3, 1, 2, 3, 0, 3)",22546.612224 +"(0, 2, 0, 1, 2, 1, 0, 0, 1, 1, 1, 1, 4, 4, 4, 2, 2, 4, 3, 2, 3, 3, 4, 4)",19481.296896 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 1, 3, 3, 4, 4)",17116.69248 +"(0, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 0, 4, 4, 4, 2, 4, 0, 4, 4, 3, 3, 4, 4)",18030.329856 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 2, 0, 2, 4, 0, 3)",28695.527424 +"(1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 4, 4, 1, 4, 1, 2, 0, 3, 4, 0, 0)",25839.599616 +"(1, 2, 1, 0, 2, 2, 0, 1, 1, 1, 1, 0, 0, 1, 0, 3, 0, 1, 0, 0, 2, 4, 4, 3)",25808.928768 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 0, 1, 0, 4, 4, 3, 4, 4, 4, 1, 4, 4, 4, 4)",17960.1408 +"(1, 2, 0, 0, 2, 1, 1, 1, 1, 0, 1, 1, 4, 4, 4, 1, 0, 4, 4, 4, 1, 4, 4, 4)",19455.934464 +"(0, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 3, 4, 3, 2, 2, 4, 3, 1, 2, 3, 0, 2)",23230.21824 +"(0, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 1, 3, 3, 4, 3)",17545.494528 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 0, 1, 1, 1, 3, 2, 2, 3, 4, 4, 1, 1, 4, 4, 4)",23017.291776 +"(1, 1, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 4, 4, 4, 0, 4, 4, 4, 4, 4, 4, 0, 4)",18210.226176 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 4, 4, 1, 2, 3, 4, 3, 4, 3, 3, 4, 4)",19074.318336 +"(1, 1, 1, 1, 1, 2, 1, 0, 0, 1, 1, 0, 0, 3, 2, 3, 4, 1, 2, 0, 3, 4, 0, 0)",25980.567552 +"(1, 2, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 4, 3, 1, 3, 1, 2, 2, 3, 3, 0, 3)",24669.3888 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 3, 4, 4, 2)",15547.170816 +"(1, 1, 0, 0, 2, 2, 1, 1, 0, 0, 1, 0, 0, 3, 2, 3, 4, 4, 4, 0, 4, 4, 4, 4)",21062.025216 +"(1, 2, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 1, 0, 1, 2, 4, 1, 4, 0, 0)",23986.372608 +"(0, 2, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 4, 3, 1, 2, 1, 2, 2, 3, 3, 0, 2)",25636.110336 +"(1, 2, 1, 1, 2, 2, 1, 0, 0, 1, 1, 1, 4, 4, 3, 3, 3, 4, 3, 4, 3, 3, 0, 2)",19508.4288 +"(1, 1, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 4, 0, 0, 2, 4, 0, 3)",28006.612992 +"(0, 1, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 1, 4, 4, 4, 4)",17001.086976 +"(0, 1, 0, 1, 2, 2, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 0, 4, 3, 4, 2)",20713.439232 +"(1, 2, 1, 1, 2, 1, 1, 1, 0, 1, 1, 1, 0, 1, 4, 2, 3, 4, 3, 0, 3, 3, 0, 2)",22952.411136 +"(1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 3, 2, 3, 3, 1, 3, 1, 3, 4, 0, 3)",25901.531136 +"(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 3, 4, 3, 4, 4, 3, 0, 3, 3, 4, 0)",19544.408064 +"(1, 1, 0, 1, 2, 1, 0, 1, 1, 1, 1, 0, 4, 1, 4, 0, 4, 1, 4, 0, 2, 4, 0, 2)",23501.53728 +"(1, 2, 1, 1, 2, 2, 0, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 1, 4, 4, 3, 4, 4)",16596.467712 +"(1, 2, 1, 1, 2, 2, 1, 1, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 4, 2, 3, 4, 4, 2)",18931.580928 +"(1, 2, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 3, 2, 1, 4, 1, 3, 0, 1, 3, 4, 4)",24977.866752 +"(0, 1, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 4, 0, 3, 4, 4, 4)",20151.33696 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 0, 4, 4, 4, 3, 4, 4, 1, 4, 3, 3, 0, 3)",18935.119872 +"(1, 2, 0, 1, 3, 2, 1, 1, 0, 1, 1, 1, 4, 4, 4, 3, 4, 1, 2, 0, 3, 3, 4, 2)",19797.44256 +"(1, 2, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 4, 3, 1, 3, 4, 2, 2, 2, 3, 0, 2)",24202.838016 +"(0, 2, 0, 1, 3, 1, 1, 1, 1, 1, 1, 1, 3, 4, 4, 2, 4, 4, 3, 1, 2, 3, 4, 4)",19299.631104 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 2, 3, 1, 3, 1, 3, 3, 4, 4)",22909.353984 +"(0, 2, 1, 1, 2, 2, 1, 1, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 4, 4, 3, 4, 4, 4)",17898.799104 +"(1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 0, 4, 4, 3, 3, 4, 4, 2, 3, 4, 4, 3)",18081.05472 +"(0, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 1, 4, 0, 1, 0, 1, 2, 2, 2, 4, 4, 3)",25723.404288 +"(0, 2, 1, 1, 2, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 1, 0, 4, 2, 0, 2, 4, 4, 4)",20586.037248 +"(1, 2, 0, 0, 3, 2, 1, 0, 0, 0, 1, 0, 1, 4, 2, 1, 4, 1, 2, 4, 1, 4, 0, 2)",25605.439488 +"(1, 2, 1, 0, 2, 2, 1, 0, 0, 1, 1, 1, 0, 4, 0, 3, 0, 4, 0, 4, 3, 4, 4, 3)",21279.080448 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 0, 0, 4, 4, 0, 0, 1, 4, 0, 2, 4, 0, 3)",24849.28512 +"(0, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 3, 3, 4, 4)",15865.675776 +"(1, 1, 1, 0, 3, 2, 1, 1, 0, 1, 1, 1, 4, 4, 4, 3, 4, 4, 2, 4, 3, 4, 0, 0)",19798.622208 +"(1, 2, 1, 1, 2, 2, 1, 0, 1, 1, 1, 1, 0, 4, 4, 3, 3, 4, 3, 1, 4, 4, 4, 3)",18850.77504 +"(1, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 0, 0, 1, 3, 0, 2, 3, 4, 3)",23055.040512 +"(1, 2, 1, 0, 2, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 4, 3, 1, 2, 4, 0, 3)",26388.135936 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 3, 2, 3, 1, 3, 1, 3, 3, 0, 3)",23523.950592 +"(1, 2, 1, 1, 3, 2, 0, 1, 1, 1, 1, 1, 4, 4, 4, 1, 4, 1, 3, 1, 3, 3, 4, 2)",19658.83392 +"(0, 2, 1, 1, 2, 1, 0, 0, 0, 1, 1, 1, 4, 1, 4, 3, 0, 4, 3, 0, 2, 4, 0, 3)",23050.911744 +"(1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 2)",19931.922432 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 0, 0, 1, 3, 1, 3, 3, 4, 4)",24086.052864 +"(1, 2, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 4, 3, 3, 2, 4, 2, 2, 3, 3, 0, 3)",22673.424384 +"(1, 1, 0, 0, 2, 2, 1, 0, 1, 1, 1, 0, 0, 4, 0, 0, 3, 1, 0, 1, 3, 4, 4, 4)",24316.674048 +"(0, 2, 1, 1, 2, 1, 1, 1, 0, 1, 1, 1, 1, 4, 4, 2, 4, 4, 3, 2, 3, 3, 4, 4)",19116.19584 +"(1, 1, 1, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 0, 2, 3, 4, 0, 0, 2, 3, 0, 3)",25777.078272 +"(0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 3, 1, 2, 3, 4, 3, 1, 1, 3, 4, 4)",23632.478208 +"(1, 1, 0, 0, 2, 1, 1, 0, 0, 0, 1, 0, 1, 4, 2, 1, 4, 1, 2, 0, 3, 4, 0, 0)",27358.98624 +"(0, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 0, 0, 4, 4, 1, 3, 4, 3, 0, 2, 3, 4, 2)",22141.99296 +"(1, 2, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 1, 4, 4, 3, 3, 4, 2)",17560.240128 +"(1, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 0, 0, 1, 3, 0, 3, 3, 4, 3)",22522.42944 +"(1, 2, 1, 1, 3, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 4, 4, 4)",15908.143104 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 3, 2, 3, 1, 0, 1, 2, 3, 0, 2)",25179.58656 +"(0, 2, 0, 0, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 0, 0, 1, 3, 0, 2, 3, 4, 4)",24938.938368 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 0, 0, 1, 3, 1, 3, 3, 4, 2)",24459.411456 +"(1, 2, 0, 0, 2, 2, 0, 1, 1, 1, 1, 1, 4, 4, 4, 0, 0, 4, 4, 4, 4, 4, 4, 3)",17685.282816 +"(0, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 0, 2, 3, 4, 2)",21351.038976 +"(0, 2, 1, 1, 2, 2, 1, 0, 0, 1, 1, 1, 1, 4, 3, 3, 4, 4, 2, 2, 4, 4, 4, 4)",19365.101568 +"(0, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 3)",19892.994048 +"(0, 2, 0, 1, 3, 2, 1, 0, 1, 1, 1, 1, 3, 4, 4, 3, 4, 4, 3, 4, 3, 3, 4, 4)",17249.992704 +"(0, 2, 0, 0, 2, 1, 0, 0, 1, 1, 1, 1, 4, 4, 4, 1, 0, 4, 2, 0, 2, 3, 0, 3)",23511.564288 +"(1, 2, 1, 0, 2, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 2, 0, 1, 2, 1, 3, 4, 0, 3)",27051.687936 +"(1, 2, 0, 1, 2, 2, 1, 0, 1, 1, 1, 1, 1, 4, 3, 1, 2, 4, 2, 2, 3, 4, 0, 3)",22829.13792 +"(0, 1, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 3, 4, 4, 1, 2, 4, 4, 4)",20363.6736 +"(0, 2, 0, 1, 2, 1, 1, 1, 0, 1, 1, 1, 3, 4, 4, 3, 4, 4, 3, 1, 3, 3, 4, 4)",18710.396928 +"(1, 1, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 4, 3, 0, 2, 4, 0, 3)",27111.26016 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 0, 0, 0, 1, 0, 1, 3, 3, 0, 3)",27327.725568 +"(1, 2, 0, 1, 3, 2, 1, 0, 1, 1, 1, 1, 1, 4, 4, 4, 4, 4, 3, 2, 3, 4, 4, 4)",17825.660928 +"(0, 2, 1, 1, 2, 1, 1, 1, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 2, 3, 3, 4, 4)",19606.929408 +"(1, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 3, 4, 1, 0, 0, 2, 4, 0, 4)",26333.872128 +"(1, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 0, 0, 1, 3, 1, 3, 3, 4, 3)",22202.155008 +"(1, 2, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 4, 4, 4, 1, 3, 1, 4, 4, 3, 3, 0, 3)",20373.110784 +"(1, 2, 1, 1, 3, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 1, 3, 3, 4, 4)",17494.17984 +"(1, 2, 1, 1, 2, 1, 1, 1, 0, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 1, 3, 4, 4, 4)",17368.547328 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 2, 4, 1, 3, 1, 3, 4, 4, 4)",23867.22816 +"(0, 1, 0, 1, 2, 1, 1, 1, 0, 1, 1, 1, 4, 4, 1, 3, 3, 4, 3, 1, 3, 3, 4, 4)",19911.868416 +"(0, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 3, 4, 4, 2, 3, 4, 4, 3)",17122.000896 +"(1, 2, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 4, 0, 0, 0, 1, 0, 0, 2, 3, 0, 3)",28369.354752 +"(0, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 3, 4, 3, 2, 3, 4, 3, 1, 2, 3, 0, 2)",22774.284288 +"(0, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 0, 0, 4, 3, 1, 3, 3, 4, 4)",22576.103424 +"(1, 2, 1, 1, 3, 2, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 4, 4, 3, 4, 3, 3, 4, 4)",17804.427264 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 0, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4)",16027.877376 +"(0, 1, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 3, 1, 4, 1, 3, 4, 4, 4)",21341.011968 +"(1, 2, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 4, 3, 1, 3, 1, 2, 2, 3, 3, 0, 3)",24677.646336 +"(1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 3, 3, 4, 4, 2, 3, 4, 4, 3)",18072.797184 +"(1, 2, 1, 1, 2, 2, 1, 0, 0, 1, 1, 0, 4, 4, 4, 0, 4, 1, 1, 4, 3, 4, 4, 2)",19984.416768 +"(1, 2, 1, 1, 2, 2, 1, 1, 0, 1, 1, 1, 0, 4, 4, 0, 4, 1, 3, 1, 3, 3, 4, 4)",20639.121408 +"(0, 2, 1, 1, 2, 2, 1, 1, 0, 1, 1, 1, 0, 4, 4, 2, 4, 4, 3, 1, 3, 3, 4, 2)",19826.93376 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 3, 2, 3, 4, 3, 1, 2, 3, 4, 2)",21441.282048 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 0, 2, 3, 4, 2)",21634.154496 +"(1, 2, 1, 1, 2, 2, 0, 1, 1, 1, 1, 0, 4, 4, 4, 3, 4, 4, 0, 1, 3, 3, 4, 2)",19329.122304 +"(1, 2, 1, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 0, 0, 0, 1, 4, 0, 2, 3, 0, 3)",26267.81184 +"(1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 3, 0, 1, 0, 1, 2, 0, 2, 4, 0, 3)",28873.654272 +"(1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 2, 4, 4, 3, 1, 3, 3, 4, 2)",19441.188864 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 0, 4, 1, 3, 4, 4, 3, 1, 3, 3, 4, 2)",19912.45824 +"(0, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 1, 0, 4, 1, 0, 0, 1, 2, 1, 3, 3, 4, 2)",25219.694592 +"(1, 2, 1, 1, 2, 2, 0, 1, 0, 1, 1, 0, 0, 4, 4, 3, 0, 1, 4, 4, 4, 3, 0, 4)",21451.89888 +"(1, 2, 0, 1, 2, 1, 0, 1, 1, 1, 1, 1, 0, 4, 4, 3, 0, 4, 4, 0, 2, 3, 0, 3)",22222.798848 +"(0, 2, 0, 1, 3, 1, 1, 0, 1, 1, 1, 1, 4, 4, 1, 3, 0, 4, 3, 4, 3, 3, 4, 4)",19197.591552 +"(1, 2, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 3, 4, 3, 2, 3, 3, 4, 4)",17270.04672 +"(0, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 0, 4)",16684.941312 +"(1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 3, 2, 1, 0, 1, 2, 0, 2, 4, 0, 3)",28070.313984 +"(1, 2, 0, 1, 3, 1, 1, 0, 0, 1, 1, 1, 0, 4, 0, 0, 0, 1, 3, 4, 3, 3, 0, 3)",24122.621952 +"(1, 2, 0, 0, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 0, 4, 3, 4, 4, 2)",17459.970048 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 0, 0, 4, 2, 0, 0, 1, 0, 1, 3, 3, 0, 3)",26807.5008 +"(0, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 4)",20124.79488 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 4, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 4)",19260.112896 +"(1, 2, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 4, 3, 1, 2, 1, 3, 2, 3, 3, 0, 3)",24081.924096 +"(1, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 0, 4, 4, 1, 0, 2, 4, 4, 3)",19993.853952 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 0, 0, 0, 1, 0, 1, 3, 3, 4, 3)",25711.607808 +"(1, 2, 1, 1, 3, 1, 0, 1, 1, 1, 1, 0, 0, 4, 0, 3, 4, 4, 3, 0, 3, 4, 0, 2)",22307.733504 +"(1, 2, 0, 1, 3, 1, 1, 1, 0, 1, 1, 0, 4, 4, 4, 0, 4, 4, 3, 0, 2, 3, 4, 3)",19734.921216 +"(0, 2, 0, 1, 0, 2, 0, 0, 1, 1, 1, 1, 4, 4, 3, 1, 4, 1, 4, 4, 3, 4, 0, 3)",20767.70304 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 1, 3, 3, 4, 3)",17356.750848 +"(1, 2, 0, 1, 3, 2, 0, 1, 1, 1, 1, 0, 4, 4, 0, 3, 4, 4, 2, 1, 3, 4, 4, 4)",19704.840192 +"(0, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 0, 4, 3, 0, 2, 3, 4, 2)",22097.166336 +"(0, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 1, 3, 3, 0, 2)",22114.271232 +"(1, 1, 0, 0, 2, 2, 1, 0, 0, 1, 1, 1, 4, 1, 4, 0, 0, 1, 0, 4, 2, 3, 4, 3)",23049.732096 +"(1, 2, 1, 1, 2, 2, 0, 0, 1, 1, 1, 1, 0, 4, 4, 3, 0, 1, 1, 4, 3, 3, 0, 4)",22675.78368 +"(1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 3, 2, 3, 2, 2, 4, 3, 4, 4)",19627.573248 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4)",14691.336192 +"(1, 2, 1, 0, 2, 1, 1, 0, 0, 1, 1, 1, 1, 1, 4, 1, 0, 1, 3, 0, 2, 3, 0, 3)",26107.379712 +"(1, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 0, 3, 1, 3, 0, 3, 3, 4, 3)",21776.30208 +"(1, 1, 0, 1, 2, 1, 1, 1, 1, 1, 1, 1, 0, 4, 4, 2, 4, 4, 3, 0, 2, 3, 4, 4)",19928.973312 +"(0, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 1, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 2)",20489.895936 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 1, 0, 4, 3, 1, 3, 4, 2, 2, 3, 3, 0, 3)",23262.068736 +"(1, 2, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 1, 3, 3, 4, 4)",17645.174784 +"(1, 2, 1, 1, 2, 1, 0, 1, 0, 1, 1, 0, 0, 4, 4, 3, 0, 1, 1, 0, 2, 3, 0, 4)",25177.817088 +"(1, 2, 1, 0, 2, 2, 1, 0, 0, 1, 1, 1, 0, 4, 0, 0, 0, 1, 3, 1, 2, 3, 4, 2)",24632.819712 +"(1, 2, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 4, 2, 1, 2, 1, 2, 2, 2, 3, 0, 3)",27323.5968 +"(1, 1, 0, 0, 2, 1, 0, 0, 1, 1, 1, 1, 0, 1, 4, 0, 0, 1, 3, 0, 3, 3, 4, 3)",24361.500672 +"(1, 2, 0, 1, 2, 1, 1, 1, 0, 1, 1, 1, 1, 4, 0, 3, 0, 4, 3, 4, 2, 3, 0, 4)",22315.401216 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 1, 3, 4, 4, 2)",16818.83136 +"(1, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 4, 1, 3, 3, 4, 3)",19913.637888 +"(1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 3, 2, 1, 0, 1, 2, 0, 2, 3, 0, 3)",28573.433856 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 3, 3, 3, 4, 3, 1, 2, 3, 0, 2)",22623.289344 +"(0, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 4, 2, 3, 4, 4)",17094.868992 +"(1, 2, 1, 1, 2, 2, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 2)",20120.666112 +"(0, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 2, 3, 3, 4, 4)",19984.416768 +"(0, 1, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 2, 4, 0, 3)",29516.562432 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 3, 0, 0, 0, 1, 3, 1, 3, 4, 4, 3)",24529.010688 +"(0, 2, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 4, 4, 2, 3, 1, 3, 2, 3, 3, 4, 4)",21014.249472 +"(0, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 0, 4, 4, 3, 3, 4, 3, 1, 3, 3, 4, 4)",19313.197056 +"(1, 2, 0, 1, 2, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 0, 4, 4, 4, 4, 4, 4, 4, 3)",16267.935744 +"(1, 2, 0, 1, 3, 1, 0, 1, 1, 1, 1, 0, 4, 4, 4, 3, 4, 4, 0, 0, 3, 3, 0, 3)",21037.842432 +"(1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 3, 3, 1, 0, 1, 2, 0, 3, 4, 0, 3)",25872.039936 +"(1, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 0, 0, 4, 0, 0, 0, 1, 0, 1, 2, 4, 0, 3)",27074.101248 +"(1, 2, 1, 0, 3, 2, 0, 0, 1, 1, 1, 0, 4, 1, 4, 1, 4, 1, 2, 0, 3, 4, 4, 3)",22130.786304 +"(1, 2, 1, 1, 2, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 3, 4, 4)",16222.519296 +"(0, 2, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 4, 3, 1, 2, 1, 2, 2, 3, 4, 0, 4)",24759.631872 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 4, 0, 0, 1, 1, 0, 2, 4, 0, 3)",26440.040448 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 1, 3, 3, 4, 2)",17924.161536 +"(1, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 3, 3, 4, 4, 0, 4, 4, 4, 2)",19041.878016 +"(0, 2, 1, 1, 3, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 1, 3, 3, 4, 4)",17871.6672 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 4, 4, 4)",15530.655744 +"(1, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 3)",19987.365888 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 1, 2, 1, 1, 0, 1, 2, 0, 2, 3, 0, 2)",28903.145472 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 2, 3, 0, 3)",29311.893504 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 4, 4, 2)",15998.386176 +"(1, 1, 0, 0, 3, 2, 1, 0, 1, 1, 1, 0, 0, 3, 2, 1, 4, 4, 2, 0, 2, 4, 0, 3)",24671.158272 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 1, 4, 4, 1, 0, 1, 2, 0, 2, 4, 0, 3)",26035.421184 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 3, 3, 4, 4)",15299.444736 +"(1, 2, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 4, 4, 4, 3, 0, 1, 4, 4, 4, 4, 4, 4)",18373.607424 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 1, 4, 3, 3, 4)",17019.37152 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 3, 4, 4, 4)",15079.440384 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 2, 4, 4, 3, 4, 3, 3, 4, 4)",17607.426048 +"(0, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 1, 0, 4, 4, 0, 3, 4, 3, 0, 2, 3, 0, 2)",23775.215616 +"(1, 1, 1, 1, 3, 2, 1, 0, 1, 1, 1, 1, 4, 3, 4, 3, 4, 4, 3, 4, 2, 4, 4, 4)",17034.11712 +"(1, 2, 1, 1, 2, 2, 1, 1, 0, 1, 1, 1, 1, 4, 4, 3, 4, 4, 4, 4, 3, 4, 4, 3)",16836.52608 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 2, 0, 2, 4, 0, 3)",28703.78496 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 1, 3, 3, 4, 2)",17038.835712 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 3, 0, 0, 4, 3, 1, 2, 3, 0, 2)",24731.910144 +"(1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 3, 0, 0, 0, 1, 0, 0, 2, 3, 0, 3)",29528.948736 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 1, 0, 1, 3, 1, 3, 3, 4, 3)",23931.518976 +"(1, 1, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 1, 4, 4, 2, 4, 4, 3, 1, 3, 3, 4, 4)",19445.317632 +"(1, 2, 1, 1, 2, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 0, 4, 1, 1, 0, 2, 4, 4, 2)",21070.872576 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 1, 3, 3, 4, 4)",17211.06432 +"(1, 2, 0, 1, 2, 2, 0, 1, 0, 1, 1, 1, 4, 4, 4, 1, 4, 4, 2, 0, 4, 4, 4, 3)",18771.1488 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 3, 2, 3, 4, 4, 1, 3, 3, 4, 3)",18352.963584 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 2, 0, 2, 3, 0, 2)",29143.20384 +"(0, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 3, 4, 3, 1, 3, 4, 4, 2)",18224.381952 +"(1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 1, 3, 4, 4, 2)",17007.57504 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 0, 3, 4, 3, 2, 0, 1, 1, 1, 2, 4, 0, 3)",25722.22464 +"(1, 2, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 4, 2, 1, 0, 1, 2, 0, 3, 3, 0, 3)",27447.45984 +"(1, 2, 0, 1, 2, 1, 0, 0, 1, 1, 1, 0, 4, 4, 4, 1, 0, 1, 2, 0, 2, 4, 0, 4)",24372.707328 +"(0, 2, 1, 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1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 4, 4, 2)",16281.501696 +"(1, 2, 1, 1, 3, 2, 1, 1, 0, 1, 1, 1, 4, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 4)",18316.394496 +"(1, 1, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 3, 4, 4, 4, 1, 3, 3, 4, 3)",18713.935872 +"(1, 2, 1, 1, 3, 1, 1, 0, 0, 1, 1, 1, 0, 4, 0, 3, 4, 4, 3, 1, 3, 3, 4, 4)",20312.358912 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 0, 0, 4, 4, 4, 3, 3, 4, 3)",17349.67296 +"(0, 2, 0, 0, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 0, 4, 2, 1, 2, 4, 0, 2)",24499.519488 +"(0, 1, 1, 1, 2, 2, 1, 0, 0, 1, 1, 1, 0, 4, 1, 3, 3, 4, 3, 1, 3, 3, 4, 4)",21154.03776 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 1, 0, 1, 3, 1, 2, 3, 4, 3)",24464.130048 +"(1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4)",14880.079872 +"(1, 2, 0, 1, 1, 2, 1, 1, 1, 1, 1, 1, 3, 4, 4, 1, 4, 4, 3, 1, 3, 4, 0, 3)",20344.799232 +"(0, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 1, 0, 4, 1, 0, 0, 1, 3, 0, 2, 3, 4, 2)",25312.29696 +"(1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 3, 4, 4, 3, 4, 4, 3, 4, 3, 3, 4, 4)",16495.017984 +"(1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 4, 2, 1, 0, 1, 2, 0, 3, 3, 0, 3)",27541.83168 +"(0, 2, 0, 1, 2, 2, 1, 0, 1, 1, 1, 1, 0, 4, 4, 0, 0, 4, 3, 1, 3, 4, 4, 2)",21454.848 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 0, 0, 1, 3, 1, 3, 3, 4, 3)",23948.623872 +"(0, 2, 0, 1, 3, 1, 1, 0, 0, 1, 1, 1, 4, 4, 1, 2, 3, 4, 3, 1, 3, 3, 4, 2)",20908.081152 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 1, 4, 3, 1, 0, 1, 2, 0, 2, 3, 0, 2)",27297.05472 +"(1, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 3, 4, 1, 3, 1, 3, 3, 4, 4)",20151.926784 +"(1, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 0, 0, 4, 2, 1, 3, 1, 3, 0, 3, 3, 4, 3)",23003.725824 +"(1, 2, 0, 1, 3, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 1, 3, 3, 4, 4)",18305.777664 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 1, 4, 4, 1, 0, 1, 2, 0, 3, 4, 0, 3)",25502.810112 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 2, 4, 4, 3, 1, 3, 3, 4, 4)",18973.458432 +"(1, 1, 1, 0, 3, 1, 1, 0, 0, 0, 1, 0, 1, 3, 2, 2, 0, 1, 2, 0, 2, 4, 4, 3)",26032.472064 +"(1, 2, 0, 0, 2, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 2, 1, 3, 3, 0, 4)",27916.959744 +"(1, 2, 1, 1, 3, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 2, 3, 1, 3, 1, 3, 4, 4, 3)",19563.282432 +"(1, 2, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 3, 2, 1, 0, 1, 2, 0, 2, 3, 0, 3)",28479.062016 +"(1, 2, 1, 1, 3, 1, 1, 0, 0, 1, 1, 1, 4, 4, 1, 3, 4, 1, 3, 4, 3, 3, 4, 2)",19286.065152 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 1, 0, 1, 3, 1, 3, 3, 4, 4)",24068.947968 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 0, 4, 4, 2, 4, 4, 3, 1, 3, 3, 4, 4)",18981.715968 +"(1, 2, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 2, 1, 2, 2, 3, 3, 0, 3)",26688.356352 +"(1, 2, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 4, 2, 1, 0, 1, 2, 0, 3, 3, 0, 3)",27730.57536 +"(1, 2, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 3, 4, 3)",15990.718464 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 1, 4, 3, 1, 0, 1, 2, 0, 2, 4, 0, 2)",26793.934848 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 3, 4, 3, 4, 4, 2, 4, 4, 4, 4, 4)",16307.453952 +"(1, 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1, 1, 1, 4, 4, 4, 3, 3, 4, 3, 4, 3, 4, 0, 2)",18380.095488 +"(1, 1, 0, 1, 2, 2, 0, 1, 1, 1, 1, 1, 1, 4, 4, 0, 4, 4, 3, 1, 3, 3, 4, 4)",19781.517312 +"(1, 2, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 3, 2, 1, 0, 1, 2, 0, 2, 3, 0, 3)",27912.830976 +"(1, 2, 0, 1, 3, 2, 1, 1, 1, 1, 1, 1, 3, 4, 3, 3, 3, 4, 3, 4, 2, 3, 0, 4)",19751.436288 +"(1, 2, 0, 1, 3, 1, 0, 0, 0, 1, 1, 0, 4, 4, 4, 3, 0, 4, 4, 4, 2, 3, 4, 4)",18948.096 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 1, 3, 3, 4, 3)",17696.489472 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 1, 4, 4, 4, 2, 0, 4, 3, 0, 2, 4, 4, 3)",20690.436096 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 3, 1, 0, 4, 3, 1, 2, 3, 4, 3)",22587.899904 +"(0, 2, 1, 1, 2, 1, 0, 1, 0, 1, 1, 1, 3, 4, 1, 3, 4, 4, 3, 0, 3, 3, 4, 2)",20301.152256 +"(1, 1, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 1, 4, 0, 3, 0, 1, 2, 0, 2, 3, 0, 2)",27400.27392 +"(1, 1, 1, 0, 3, 2, 1, 1, 1, 1, 1, 1, 0, 3, 4, 3, 4, 4, 4, 0, 2, 3, 0, 4)",20970.012672 +"(1, 2, 0, 1, 2, 2, 1, 0, 1, 1, 1, 1, 0, 4, 4, 3, 0, 4, 3, 1, 3, 3, 4, 4)",20342.439936 +"(1, 2, 1, 0, 2, 1, 0, 0, 0, 1, 1, 0, 1, 4, 3, 3, 0, 4, 2, 0, 3, 3, 4, 2)",22979.54304 +"(1, 2, 1, 1, 2, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 2, 3, 4, 4, 4, 4, 4, 4, 4)",16079.781888 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 3, 1, 0, 1, 3, 1, 3, 3, 4, 3)",23282.122752 +"(1, 2, 1, 0, 1, 2, 1, 1, 1, 1, 1, 1, 4, 4, 2, 3, 4, 4, 4, 4, 2, 4, 4, 4)",17045.323776 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 4, 2, 4, 4, 3, 1, 2, 3, 4, 3)",20200.292352 +"(0, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 2, 0, 1, 3, 0, 2, 3, 4, 2)",24504.23808 +"(0, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 0, 0, 4, 4, 2, 3, 4, 4, 1, 3, 4, 4, 4)",20397.293568 +"(1, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 1, 3, 4, 4, 3)",18325.83168 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 1, 4, 1, 2, 0, 3, 4, 0, 3)",22386.76992 +"(1, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 3, 4, 4, 2, 3, 1, 3, 1, 3, 4, 4, 3)",20307.64032 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 0, 1, 4, 4, 1, 4, 1, 2, 1, 3, 3, 0, 2)",23269.146624 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 1, 2, 3, 1, 3, 1, 2, 3, 0, 3)",24422.842368 +"(1, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 0, 0, 1, 3, 4, 2, 3, 4, 4)",21506.162688 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 1, 4, 1, 4, 4, 4, 4, 3, 3, 4, 4)",17136.746496 +"(1, 2, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 4, 4, 2, 1, 0, 1, 2, 4, 4, 4, 4, 3)",22294.757376 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 4, 2, 3, 4, 4, 1, 2, 4, 0, 3)",21627.666432 +"(1, 2, 1, 1, 3, 1, 1, 1, 0, 1, 1, 1, 4, 4, 1, 1, 4, 1, 3, 1, 3, 3, 4, 3)",20705.77152 +"(0, 1, 0, 1, 2, 2, 1, 0, 0, 1, 1, 1, 0, 4, 1, 1, 3, 1, 3, 1, 2, 3, 0, 4)",25471.54944 +"(1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 3, 4, 4, 3, 4, 1, 3, 1, 3, 3, 4, 3)",19233.570816 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 4, 4, 4, 3)",15288.23808 +"(1, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 3, 4, 4, 2, 3, 1, 3, 1, 3, 3, 4, 2)",20755.316736 +"(1, 2, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 3, 3, 4, 4)",15393.816576 +"(1, 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1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 1, 3, 4, 4, 3)",18042.71616 +"(0, 2, 0, 1, 3, 1, 1, 0, 0, 1, 1, 1, 1, 4, 4, 3, 4, 4, 3, 0, 2, 4, 4, 2)",20394.934272 +"(1, 2, 1, 1, 3, 2, 1, 0, 0, 1, 1, 1, 4, 3, 4, 3, 0, 4, 4, 4, 2, 3, 4, 4)",18220.253184 +"(1, 2, 1, 0, 2, 1, 1, 1, 1, 1, 1, 0, 4, 4, 4, 3, 4, 4, 3, 4, 3, 4, 4, 4)",16568.745984 +"(1, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 3, 2, 3, 1, 3, 1, 3, 3, 4, 3)",22028.156928 +"(1, 2, 0, 1, 3, 1, 0, 0, 1, 1, 1, 1, 4, 4, 4, 1, 4, 4, 3, 4, 3, 3, 4, 3)",17593.270272 +"(1, 2, 1, 1, 3, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 1, 4, 3, 4, 4)",17106.075648 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 2, 0, 2, 3, 4, 4)",26870.611968 +"(1, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 1, 3, 4, 4, 4)",17897.029632 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 4, 3, 4, 4)",15456.927744 +"(1, 2, 0, 1, 3, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 3, 3, 3, 4, 4)",16557.539328 +"(1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 0, 4, 4, 1, 0, 1, 4, 4, 4, 4, 4, 3)",19382.206464 +"(1, 2, 0, 0, 2, 1, 1, 0, 0, 1, 1, 0, 0, 3, 2, 1, 0, 1, 2, 1, 2, 3, 4, 3)",26070.810624 +"(0, 1, 0, 0, 2, 1, 1, 0, 0, 1, 1, 1, 0, 3, 2, 1, 0, 1, 2, 0, 2, 3, 4, 3)",25919.225856 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 3, 2, 3, 4, 4, 1, 2, 4, 0, 3)",21875.392512 +"(1, 2, 1, 1, 3, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 4, 1, 3, 3, 4, 4)",17477.074944 +"(1, 2, 0, 1, 3, 2, 1, 0, 0, 1, 1, 1, 4, 4, 1, 3, 4, 4, 3, 1, 3, 3, 4, 4)",19240.648704 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 0, 1, 1, 3, 4, 1, 2, 3, 1, 3, 0, 2, 3, 0, 3)",25120.60416 +"(1, 2, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 4, 1, 0, 0, 1, 3, 0, 2, 3, 0, 2)",27966.50496 +"(1, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 3, 4, 4, 2, 3, 1, 3, 0, 3, 3, 4, 2)",20792.475648 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 4, 3, 4, 4, 2)",16338.1248 +"(1, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 1, 4, 3, 1, 4, 4, 2, 1, 2, 3, 0, 4)",23015.522304 +"(1, 2, 1, 1, 2, 2, 1, 0, 1, 1, 1, 1, 0, 4, 4, 0, 0, 1, 3, 1, 3, 3, 4, 3)",22107.783168 +"(1, 2, 0, 1, 2, 2, 1, 1, 0, 1, 1, 0, 0, 3, 2, 1, 0, 4, 2, 4, 2, 3, 4, 3)",22722.9696 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 4, 4, 1, 3, 4, 1, 3, 4, 4, 4, 0, 3)",20443.889664 +"(1, 2, 0, 1, 3, 1, 1, 0, 1, 1, 1, 0, 4, 4, 4, 1, 4, 4, 2, 0, 4, 4, 4, 4)",19002.949632 +"(1, 2, 1, 1, 3, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 1, 3, 3, 4, 2)",17867.538432 +"(1, 2, 0, 0, 3, 1, 0, 0, 0, 1, 1, 0, 4, 4, 4, 2, 0, 1, 3, 0, 3, 3, 4, 2)",22587.31008 +"(1, 2, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 1, 3, 4, 4, 3)",17570.85696 +"(1, 2, 1, 0, 3, 1, 1, 0, 1, 0, 1, 1, 4, 4, 4, 3, 4, 1, 3, 0, 3, 4, 4, 4)",19576.25856 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 3, 4, 4, 2, 3, 4, 3, 1, 2, 3, 4, 3)",19267.190784 +"(1, 2, 1, 0, 2, 2, 0, 1, 0, 1, 1, 1, 1, 1, 0, 3, 0, 1, 4, 4, 2, 3, 0, 2)",24831.5904 +"(1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 3, 2, 1, 0, 1, 2, 0, 2, 3, 0, 3)",28290.318336 +"(1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 0, 0, 3, 2, 3, 0, 4, 3, 0, 4, 3, 4, 3)",21597.585408 +"(1, 2, 0, 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1, 1, 0, 3, 1, 0, 0, 1, 3, 0, 2, 3, 0, 3)",27199.73376 +"(1, 2, 1, 1, 2, 2, 1, 0, 1, 1, 1, 1, 3, 4, 4, 3, 4, 4, 4, 1, 4, 3, 4, 3)",17450.532864 +"(1, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 0, 0, 1, 3, 1, 3, 3, 4, 3)",22485.270528 +"(1, 2, 0, 0, 3, 1, 1, 0, 0, 0, 1, 1, 4, 4, 4, 1, 4, 1, 2, 4, 2, 4, 0, 3)",22169.714688 +"(1, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 1, 2, 0, 1, 3, 1, 3, 3, 4, 3)",22737.125376 +"(0, 2, 0, 1, 2, 1, 0, 0, 1, 1, 1, 1, 0, 4, 1, 0, 0, 1, 3, 0, 3, 3, 4, 2)",24496.570368 +"(1, 2, 0, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 2, 0, 4, 3, 1, 3, 3, 4, 3)",21016.608768 +"(1, 2, 1, 1, 3, 2, 1, 1, 0, 1, 1, 1, 4, 4, 4, 2, 4, 1, 3, 1, 2, 3, 4, 3)",19739.049984 +"(1, 2, 1, 1, 2, 2, 0, 0, 1, 1, 1, 0, 4, 4, 3, 1, 0, 4, 3, 1, 2, 3, 4, 3)",21534.47424 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 0, 1, 4, 3, 1, 0, 1, 2, 1, 2, 3, 4, 3)",24849.874944 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 1, 4, 1, 1, 0, 1, 3, 0, 2, 3, 0, 3)",26958.495744 +"(1, 2, 1, 1, 3, 1, 1, 0, 1, 1, 1, 1, 3, 4, 4, 2, 4, 1, 3, 1, 3, 4, 4, 3)",19730.792448 +"(1, 2, 0, 1, 3, 1, 1, 0, 0, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 1, 3, 3, 0, 3)",20350.697472 +"(1, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 4, 3, 4, 4)",15928.786944 +"(1, 2, 1, 1, 1, 2, 1, 1, 0, 1, 1, 1, 0, 4, 1, 0, 4, 4, 4, 4, 3, 3, 4, 4)",18869.649408 +"(1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 4, 2, 1, 0, 1, 2, 0, 2, 3, 4, 2)",26685.997056 +"(1, 2, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 2, 3, 1, 3, 4, 3, 4, 4, 4)",17768.448 +"(0, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 0, 0, 1, 3, 1, 3, 3, 4, 3)",22485.270528 +"(1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 3, 4, 4, 2, 4, 1, 4, 4, 3, 3, 4, 2)",18078.1056 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 1, 0, 4, 3, 1, 0, 1, 2, 1, 2, 3, 0, 2)",26701.922304 +"(1, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 4, 1, 3, 4, 4, 4)",19547.947008 +"(1, 2, 1, 1, 3, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 3, 4, 3, 0, 3, 3, 4, 4)",18013.814784 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 0, 1, 4, 3, 1, 0, 1, 3, 0, 3, 3, 4, 3)",23877.255168 +"(1, 2, 0, 0, 1, 2, 1, 1, 0, 0, 1, 0, 4, 3, 4, 1, 0, 1, 2, 0, 2, 4, 4, 3)",23967.49824 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 3, 4, 4, 3, 4, 4, 3, 4, 3, 3, 4, 4)",16400.646144 +"(1, 1, 1, 1, 3, 1, 1, 0, 1, 1, 1, 1, 0, 4, 2, 3, 4, 4, 4, 4, 4, 3, 0, 4)",19297.271808 +"(1, 2, 1, 1, 3, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 4, 4, 4)",16002.514944 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 4, 1, 3, 4, 4, 3)",17025.26976 +"(1, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 4, 1, 3, 4, 4, 4)",19453.575168 +"(1, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 0, 4, 1, 1, 0, 4, 4, 4, 4, 4, 4, 3)",19713.097728 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 3, 0, 2, 3, 0, 2)",28674.29376 +"(1, 2, 0, 0, 2, 2, 0, 0, 1, 1, 1, 0, 1, 4, 3, 3, 4, 1, 2, 4, 2, 3, 4, 2)",22012.821504 +"(1, 2, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 3, 4, 4)",15845.031936 +"(1, 2, 1, 1, 3, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 1, 3, 4, 4, 2)",17647.53408 +"(1, 1, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 3, 4, 3, 2, 3, 4, 4, 4)",19575.668736 +"(0, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 0, 4, 1, 0, 0, 1, 3, 0, 2, 3, 0, 2)",27494.64576 +"(1, 2, 0, 1, 2, 2, 0, 1, 0, 1, 1, 1, 4, 4, 3, 1, 0, 1, 2, 0, 2, 3, 0, 2)",24741.937152 +"(1, 2, 1, 0, 3, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 1, 4, 3, 4, 2)",17856.9216 +"(1, 2, 1, 1, 2, 2, 1, 0, 0, 1, 1, 1, 4, 4, 4, 0, 4, 4, 3, 1, 3, 3, 4, 3)",18693.292032 +"(1, 2, 0, 1, 2, 2, 1, 1, 1, 1, 1, 1, 0, 4, 1, 3, 4, 1, 3, 4, 4, 4, 4, 4)",19169.28 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 1, 1, 3, 1, 0, 1, 2, 1, 2, 3, 4, 3)",26311.458816 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 4, 4, 4, 4)",15236.923392 +"(1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 3, 4, 4, 4)",15268.184064 +"(1, 2, 0, 1, 3, 2, 1, 1, 0, 1, 1, 1, 4, 4, 4, 3, 4, 1, 3, 1, 3, 3, 4, 4)",18909.75744 +"(1, 2, 1, 0, 2, 1, 0, 0, 1, 1, 1, 1, 1, 4, 4, 0, 0, 1, 2, 0, 3, 3, 0, 2)",25118.244864 +"(1, 2, 1, 1, 2, 1, 1, 1, 0, 1, 1, 1, 4, 4, 4, 1, 0, 4, 3, 0, 4, 3, 0, 4)",20741.16096 +"(1, 2, 0, 1, 3, 2, 1, 0, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 1, 3, 4, 4, 4)",17991.401472 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 4, 3, 3, 4, 2)",16558.129152 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 3, 3, 4, 4, 4)",15508.832256 +"(1, 2, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 4, 1, 0, 0, 1, 3, 0, 2, 3, 4, 2)",25784.15616 +"(1, 2, 1, 0, 2, 1, 1, 0, 1, 1, 1, 0, 1, 4, 4, 3, 4, 4, 4, 4, 4, 4, 3, 4)",17537.236992 +"(1, 2, 1, 1, 2, 2, 0, 1, 1, 1, 1, 1, 0, 4, 4, 0, 0, 1, 3, 3, 3, 4, 0, 3)",22472.884224 +"(1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 0, 4, 4, 4, 0, 1, 3, 4, 4, 3, 4, 4)",18706.857984 +"(1, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 4, 4, 4, 1, 0, 4, 4, 1, 3, 3, 4, 3)",19547.947008 +"(1, 2, 0, 0, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 0, 2, 3, 4, 3, 0, 2, 3, 0, 2)",23762.239488 +"(1, 2, 0, 1, 3, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 4, 4, 3, 4, 4)",16551.641088 +"(1, 2, 1, 1, 3, 1, 1, 0, 0, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 4, 4, 3)",16431.316992 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 3, 4, 3, 2, 0, 1, 3, 0, 2, 3, 0, 2)",25916.86656 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 1, 3, 4, 4, 4)",16445.472768 +"(1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 4, 4, 3, 4, 4, 4)",15268.184064 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 0, 4, 4, 0, 0, 1, 3, 1, 4, 3, 4, 3)",21342.191616 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 1, 4, 3, 1, 3, 4, 2, 1, 2, 3, 0, 3)",23926.800384 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 1, 0, 0, 1, 3, 1, 2, 3, 0, 3)",26097.352704 +"(1, 2, 0, 1, 2, 2, 1, 0, 0, 1, 1, 1, 3, 4, 3, 3, 3, 4, 3, 1, 3, 3, 4, 4)",19723.71456 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 3, 0, 2, 3, 0, 2)",28382.920704 +"(1, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 4, 2, 3, 1, 3, 1, 3, 3, 4, 3)",20810.760192 +"(1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 4, 4, 2, 4, 0, 3)",17996.709888 +"(1, 2, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 2, 4, 4, 3, 4, 4, 3, 4, 3)",15942.352896 +"(1, 2, 0, 1, 2, 1, 0, 0, 0, 1, 1, 1, 0, 4, 1, 0, 0, 1, 3, 1, 2, 3, 4, 2)",24992.022528 +"(1, 2, 0, 1, 2, 2, 1, 0, 0, 1, 1, 1, 4, 4, 4, 3, 3, 4, 2, 1, 2, 3, 0, 2)",21636.513792 +"(1, 2, 1, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 4, 4, 0, 0, 4, 3, 1, 3, 3, 4, 3)",21258.436608 +"(1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 4, 4, 2, 0, 4, 4, 1, 3, 3, 0, 3)",23880.204288 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 4, 4, 3, 2, 4, 4, 3, 1, 2, 3, 4, 4)",19746.717696 +"(1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 3, 4, 4, 3, 4, 4, 4, 4, 3, 4, 4, 4)",15823.798272 +"(1, 1, 1, 1, 2, 2, 1, 0, 0, 1, 1, 1, 0, 4, 4, 2, 4, 4, 4, 1, 3, 4, 4, 4)",18971.099136 +"(1, 2, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 1, 4, 3, 1, 0, 1, 2, 0, 2, 3, 0, 3)",27069.382656 +"(1, 2, 0, 1, 2, 1, 0, 1, 0, 1, 1, 1, 0, 4, 1, 0, 0, 1, 4, 4, 4, 3, 4, 2)",21876.57216 +"(1, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 3, 4, 4, 3, 4, 4, 3, 4, 3, 3, 4, 3)",17018.191872 +"(1, 2, 0, 1, 3, 1, 1, 0, 1, 1, 1, 1, 0, 4, 4, 0, 4, 4, 3, 1, 3, 3, 4, 4)",19789.774848 +"(1, 2, 0, 1, 3, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 2, 3, 4, 3, 1, 2, 3, 0, 4)",20936.982528 +"(1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 0, 4, 4, 0, 4, 1, 3, 1, 3, 3, 4, 4)",20450.377728 +"(1, 2, 1, 1, 2, 1, 1, 0, 1, 1, 1, 1, 3, 4, 4, 3, 3, 1, 3, 1, 3, 4, 4, 2)",20101.20192 +"(0, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 3, 2, 3, 4, 3, 0, 2, 3, 0, 3)",22866.886656 +"(1, 2, 1, 1, 3, 1, 1, 0, 1, 1, 1, 1, 1, 4, 3, 1, 4, 4, 3, 4, 3, 4, 4, 3)",18571.788288 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 1, 3, 4, 4, 3, 4, 4)",16683.761664 +"(1, 1, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 0, 3, 2, 1, 3, 1, 2, 0, 2, 3, 4, 3)",24606.867456 +"(1, 2, 0, 1, 3, 1, 1, 0, 1, 1, 1, 1, 3, 4, 4, 2, 3, 4, 3, 1, 3, 3, 4, 3)",19489.554432 +"(1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 3, 4, 3, 3, 4, 4)",15845.031936 +"(1, 2, 1, 1, 3, 1, 1, 0, 1, 1, 1, 1, 4, 4, 4, 2, 3, 4, 4, 1, 3, 3, 4, 4)",18053.922816 +"(1, 2, 0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 3, 4, 3, 2, 3, 4, 3, 1, 2, 3, 4, 2)",21158.166528 +"(0, 2, 1, 1, 3, 2, 1, 0, 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "35 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"35 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "38 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"36 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "38 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "44 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"41 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "50 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"42 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "44 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"43 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "44 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"44 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "45 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"50 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" -> "51 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"51 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "54 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"51 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "57 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"51 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "62 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"51 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "81 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"52 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "54 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"53 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "54 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"56 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "57 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"57 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "58 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"58 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "59 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"59 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "67 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"60 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "63 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"63 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "64 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"64 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "73 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"65 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "66 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"66 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"67 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "69 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"69 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "70 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"70 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "71 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"71 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "72 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"72 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "73 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"73 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "74 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"74 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "75 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"75 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "76 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"76 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "79 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"77 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"82 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "85 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"82 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "91 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"83 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "85 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"84 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "85 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"85 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "86 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"86 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "89 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"87 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "89 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"88 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "89 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"89 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "90 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"90 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "91 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"91 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "92 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"92 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "95 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"92 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"92 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "103 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"92 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "122 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"93 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "95 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"94 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "95 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"95 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "106 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"96 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "98 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"97 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "98 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"98 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "99 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"99 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "100 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"100 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "108 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"101 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "103 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"102 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "103 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"103 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "104 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"104 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "105 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"105 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "114 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"106 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "107 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"107 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "109 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"108 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "109 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"109 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "110 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"110 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "111 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"111 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "112 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"112 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "113 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"113 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "114 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"114 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "115 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"115 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "116 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"116 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "117 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"117 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "120 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"118 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "120 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"119 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "120 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"120 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "121 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"121 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "122 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"122 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "123 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"123 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"123 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "132 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"124 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"125 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "127 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"127 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "130 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"128 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "130 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"129 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "130 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"130 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "131 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"131 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "132 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"132 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "133 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"133 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "136 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"133 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "139 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"133 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "144 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"133 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "163 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"134 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "136 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"135 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "136 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"136 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "147 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"137 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "139 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"138 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "139 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"139 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "140 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"140 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "141 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"141 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "149 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"142 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "144 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"143 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "144 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"144 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "145 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"145 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "146 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"146 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"147 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "148 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"148 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "150 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"149 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "150 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"150 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "151 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"151 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "152 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"152 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "153 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"153 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "154 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"154 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "156 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"156 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "157 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"157 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "158 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"158 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "161 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"159 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "161 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"160 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "161 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"161 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "162 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"162 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "163 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"163 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "164 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"164 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "167 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"164 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "173 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"165 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "167 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"166 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "167 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"167 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "168 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"168 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "171 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"169 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "171 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"170 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "171 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"171 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "172 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"172 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "173 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"173 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "174 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"174 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"174 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "180 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"174 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"174 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "204 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"175 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "177 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"176 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "177 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"177 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "188 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"178 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "180 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"179 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "180 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"180 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "181 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"181 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "182 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"182 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "190 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"183 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "185 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"184 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "185 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"185 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "186 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"186 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "187 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"187 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "196 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"188 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "189 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"189 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "191 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"190 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "191 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"191 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "192 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"192 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "193 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"193 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "194 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"194 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "195 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"195 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "196 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"196 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "197 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"197 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "198 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"198 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "199 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"199 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "202 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"200 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "202 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"201 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "202 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"202 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "203 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"203 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "204 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"204 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "205 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"205 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"205 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"206 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "208 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"207 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "208 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"208 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"209 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "212 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"210 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "212 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"211 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "212 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"212 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "213 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"213 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "214 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"214 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "215 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"215 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"215 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "221 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"215 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "226 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"215 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "245 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"216 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "218 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"217 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "218 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"218 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "229 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"219 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "221 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"220 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "221 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"221 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "222 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"222 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "223 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"223 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "231 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"224 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "226 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"225 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "226 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"226 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "227 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"227 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "228 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"228 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "237 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"229 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "230 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"230 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "232 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"231 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "232 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"232 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "233 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"233 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "234 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"234 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "235 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"235 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "236 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"236 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "237 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"237 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "238 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"238 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "239 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"239 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "240 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"240 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "243 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"241 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "243 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"242 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "243 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"243 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "244 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"244 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "245 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"245 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "246 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"246 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "249 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"246 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "255 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"247 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "249 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"248 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "249 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"249 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "250 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"250 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "253 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"251 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "253 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"252 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "253 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"253 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "254 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"254 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "255 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"255 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "256 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"256 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "259 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"256 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "262 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"256 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "267 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"256 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "286 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"257 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "259 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"258 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "259 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"259 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "270 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"260 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "262 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"261 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "262 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"262 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "263 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"263 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "264 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"264 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "272 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"265 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "267 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"266 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "267 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"267 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "268 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"268 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "269 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"269 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "278 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"270 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "271 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"271 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "273 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"272 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "273 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"273 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "274 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"274 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "275 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"275 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "276 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"276 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "277 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"277 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "278 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"278 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "279 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"279 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "280 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"280 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "281 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"281 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "284 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"282 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "284 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"283 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "284 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"284 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "285 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"285 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "286 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"286 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "287 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"287 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "290 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"287 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "296 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"288 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "290 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"289 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "290 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"290 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "291 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"291 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "294 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"292 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "294 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"293 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "294 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"294 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "295 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"295 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "296 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"296 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "297 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"297 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"297 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "303 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"297 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "308 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"297 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "327 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"298 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"299 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "311 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"301 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "303 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"302 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "303 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"303 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "304 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"304 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "305 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"305 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "313 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"306 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "308 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"307 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "308 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"308 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "309 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"309 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "310 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"310 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "319 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"311 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "312 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"312 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "314 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"313 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "314 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"314 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "315 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"315 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "316 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"316 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "317 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"317 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "318 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"318 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "319 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"319 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "320 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"320 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "321 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"321 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "322 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"322 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "325 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"323 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "325 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"324 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "325 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"325 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "326 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"326 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "327 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"327 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "328 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"328 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "331 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"328 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "337 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"329 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "331 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"330 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "331 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"331 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "332 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"332 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "335 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"333 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "335 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"334 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "335 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"335 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "336 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"336 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "337 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"337 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "338 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"338 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "341 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"338 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "344 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"338 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "349 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"338 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "368 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"339 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "341 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"340 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "341 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"341 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "352 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"342 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "344 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"343 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "344 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"344 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "345 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"345 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "346 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"346 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "354 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"347 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "349 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"348 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "349 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"349 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "350 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"350 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "351 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"351 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "360 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"352 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "353 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"353 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "355 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"354 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "355 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"355 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "356 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"356 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "357 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"357 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "358 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"358 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "359 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"359 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "360 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"360 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "361 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"361 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "362 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"362 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "363 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"363 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "366 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"364 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "366 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"365 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "366 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"366 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "367 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"367 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "368 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"368 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "369 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"369 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "372 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"369 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "378 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"370 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "372 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"371 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "372 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"372 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "373 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"373 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "376 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"374 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "376 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"375 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "376 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"376 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "377 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"377 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "378 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"378 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "379 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"379 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "382 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"379 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "385 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"379 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "390 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"379 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "409 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"380 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "382 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"381 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "382 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"382 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "393 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"383 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "385 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"384 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "385 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"385 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "386 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"386 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "387 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"387 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "395 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"388 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "390 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"389 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "390 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"390 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "391 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"391 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "392 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"392 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "401 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"393 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "394 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"394 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "396 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"395 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "396 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"396 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "397 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"397 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "398 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"398 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "399 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"399 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "400 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"400 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "401 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"401 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "402 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"402 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "403 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"403 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "404 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"404 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "407 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"405 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "407 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"406 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "407 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"407 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "408 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"408 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "409 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"409 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "410 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"410 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "413 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"410 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "419 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"411 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "413 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"412 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "413 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"413 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "414 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"414 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "417 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"415 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "417 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"416 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "417 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"417 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "418 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"418 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "419 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"419 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "420 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"420 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "423 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"420 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "426 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"420 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "431 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"420 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "450 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"421 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "423 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"422 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "423 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"423 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "434 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"424 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "426 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"425 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "426 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"426 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "427 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"427 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "428 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"428 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "436 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"429 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "431 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"430 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "431 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"431 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "432 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"432 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "433 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"433 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "442 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"434 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "435 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"435 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "437 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"436 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "437 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"437 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "438 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"438 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "439 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"439 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "440 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"440 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "441 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"441 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "442 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"442 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "443 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"443 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "444 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"444 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "445 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"445 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "448 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"446 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "448 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"447 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "448 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"448 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "449 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"449 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "450 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"450 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "451 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"451 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "454 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"451 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "460 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"452 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "454 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"453 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "454 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"454 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"Viking incursions", + "56dde1d966d3e219004dad8d": "", + "5ad3ae14604f3c001a3fec39": "", + "5ad3ae14604f3c001a3fec3a": "", + "56dde27d9a695914005b9651": "", + "56dde27d9a695914005b9652": "north", + "5ad3af11604f3c001a3fec63": "", + "5ad3af11604f3c001a3fec64": "", + "5ad3af11604f3c001a3fec65": "", + "56dde2fa66d3e219004dad9b": "fighting horsemen", + "5ad3c626604f3c001a3ff011": "France", + "5ad3c626604f3c001a3ff012": "", + "5ad3c626604f3c001a3ff013": "Many Normans", + "56de0f6a4396321400ee257f": "the Pechenegs, the Bulgars, and especially the Seljuk Turks", + "5ad3dbc6604f3c001a3ff3e9": "the Normans", + "5ad3dbc6604f3c001a3ff3ea": "Pechenegs, the Bulgars, and especially the Seljuk Turks", + "5ad3dbc6604f3c001a3ff3eb": "", + "5ad3dbc6604f3c001a3ff3ec": "Sicilian campaign of George Maniaces", + "56de0ffd4396321400ee258d": "1050s", + "56de0ffd4396321400ee258e": "1060s", + "56de0ffd4396321400ee258f": "Alexius Komnenos", + "5ad3de8b604f3c001a3ff467": "Herv\u00e9", + "5ad3de8b604f3c001a3ff468": "1050s", + "5ad3de8b604f3c001a3ff469": "Roussel de Bailleul", + "5ad3de8b604f3c001a3ff46a": "1060s", + "56de10b44396321400ee2593": "Oursel", + "56de10b44396321400ee2594": "Oursel", + "56de10b44396321400ee2595": "the Armenian state", + "5ad3e96b604f3c001a3ff689": "Some Normans", + "5ad3e96b604f3c001a3ff68a": "Armenian state", + "5ad3e96b604f3c001a3ff68b": "Oursel", + "5ad3e96b604f3c001a3ff68c": "upper Euphrates valley in northern Syria", + "56de11154396321400ee25aa": "Italo-Norman named Raoul", + "5ad3ea79604f3c001a3ff6e9": "Byzantine Greece", + "5ad3ea79604f3c001a3ff6ea": "", + "5ad3ea79604f3c001a3ff6eb": "", + "56de148dcffd8e1900b4b5bc": "Robert Guiscard", + "56de148dcffd8e1900b4b5bd": "February 1082", + "56de148dcffd8e1900b4b5be": "30,000", + "5ad3ed26604f3c001a3ff799": "", + "5ad3ed26604f3c001a3ff79a": "", + "5ad3ed26604f3c001a3ff79b": "", + "5ad3ed26604f3c001a3ff79c": "30,000", + "56de15104396321400ee25b7": "Deabolis", + "56de15104396321400ee25b8": "Bohemond", + "56de15104396321400ee25b9": "river Deabolis", + "5ad3ee2d604f3c001a3ff7e1": "", + "5ad3ee2d604f3c001a3ff7e2": "Bohemond", + "5ad3ee2d604f3c001a3ff7e3": "Robert", + "56de1563cffd8e1900b4b5c2": "1185", + "56de1563cffd8e1900b4b5c3": "Dyrrachium", + "56de1563cffd8e1900b4b5c4": "Adriatic", + "5ad3f028604f3c001a3ff823": "", + "5ad3f028604f3c001a3ff824": "high Byzantine officials", + "5ad3f028604f3c001a3ff825": "Dyrrachium", + "56de15dbcffd8e1900b4b5c8": "Duke Richard II of Normandy", + "56de15dbcffd8e1900b4b5c9": "Duke Richard II of Normandy", + "56de15dbcffd8e1900b4b5ca": "Normandy", + "56de15dbcffd8e1900b4b5cb": "", + "5ad3f187604f3c001a3ff86f": "", + "5ad3f187604f3c001a3ff870": "", + "5ad3f187604f3c001a3ff871": "The Normans", + "56de1645cffd8e1900b4b5d0": "Harthacnut", + "56de1645cffd8e1900b4b5d1": "1041", + "56de1645cffd8e1900b4b5d2": "Robert of Jumi\u00e8ges", + "5ad3f350604f3c001a3ff8ef": "1041", + "5ad3f350604f3c001a3ff8f0": "English cavalry force", + "5ad3f350604f3c001a3ff8f1": "", + "56de16ca4396321400ee25c5": "Battle of Hastings", + "56de16ca4396321400ee25c6": "Duke William II of Normandy", + "56de16ca4396321400ee25c7": "1066", + "56de16ca4396321400ee25c8": "Anglo-Saxons", + "5ad3f4b1604f3c001a3ff951": "", + "5ad3f4b1604f3c001a3ff952": "", + "5ad3f4b1604f3c001a3ff953": "", + "5ad3f4b1604f3c001a3ff954": "", + "56de1728cffd8e1900b4b5d7": "Modern English", + "5ad3f5b0604f3c001a3ff9ab": "", + "5ad3f5b0604f3c001a3ff9ac": "", + "5ad3f5b0604f3c001a3ff9ad": "", + "56de179dcffd8e1900b4b5da": "1169", + "56de179dcffd8e1900b4b5db": "Bannow Bay", + "56de179dcffd8e1900b4b5dc": "", + "5ad3f6f5604f3c001a3ffa09": "", + "5ad3f6f5604f3c001a3ffa0a": "", + "5ad3f6f5604f3c001a3ffa0b": "", + "56de17f9cffd8e1900b4b5e0": "", + "56de17f9cffd8e1900b4b5e1": "King Malcolm III of Scotland", + "56de17f9cffd8e1900b4b5e2": "1072", + "56de17f9cffd8e1900b4b5e3": "his son Duncan", + "5ad3f7ac604f3c001a3ffa3b": "Margaret", + "5ad3f7ac604f3c001a3ffa3c": "", + "5ad3f7ac604f3c001a3ffa3d": "Duncan", + "56de3cd0cffd8e1900b4b6be": "Sybilla of Normandy", + "56de3cd0cffd8e1900b4b6bf": "Norman", + "5ad3f8d2604f3c001a3ffa8d": "Sybilla of Normandy", + "5ad3f8d2604f3c001a3ffa8e": "", + "56de3d594396321400ee26ca": "Hereford", + "56de3d594396321400ee26cb": "the Welsh", + "56de3d594396321400ee26cc": "Edward the Confessor", + "5ad3fb01604f3c001a3ffb35": "", + "5ad3fb01604f3c001a3ffb36": "", + "56de3dbacffd8e1900b4b6d2": "Wales", + "5ad3fb6e604f3c001a3ffb5f": "", + "5ad3fb6e604f3c001a3ffb60": "Bernard de Neufmarch\u00e9, Roger of Montgomery in Shropshire and Hugh Lupus in Cheshire", + "56de3e414396321400ee26d8": "1018", + "56de3e414396321400ee26d9": "William of Montreuil", + "5ad3fc41604f3c001a3ffb8f": "Antioch", + "5ad3fc41604f3c001a3ffb90": "", + "5ad3fc41604f3c001a3ffb91": "Roger de Tosny", + "5ad3fc41604f3c001a3ffb92": "the War of Barbastro", + "56de3ebc4396321400ee26e6": "1097", + "56de3ebc4396321400ee26e7": "Tancred", + "56de3ebc4396321400ee26e8": "Jerusalem", + "5ad4017a604f3c001a3ffd1f": "1097", + "5ad4017a604f3c001a3ffd20": "Bohemond of Taranto", + "56de3efccffd8e1900b4b6fe": "380 years", + "5ad401f2604f3c001a3ffd41": "", + "5ad401f2604f3c001a3ffd42": "", + "56de3f784396321400ee26fa": "a storm", + "56de3f784396321400ee26fb": "Berengaria", + "56de3f784396321400ee26fc": "1191", + "56de3f784396321400ee26fd": "Richard the Lion-hearted", + "5ad40280604f3c001a3ffd57": "", + "5ad40280604f3c001a3ffd58": "1191", + "5ad40280604f3c001a3ffd59": "", + "56de40da4396321400ee2708": "Conrad of Montferrat", + "56de40da4396321400ee2709": "silver", + "56de40da4396321400ee270a": "Guy de Lusignan", + "5ad404a6604f3c001a3ffde1": "", + "5ad404a6604f3c001a3ffde2": "Guy de Lusignan", + "5ad404a6604f3c001a3ffde3": "", + "56de49564396321400ee277a": "Africa", + "5ad40419604f3c001a3ffdb7": "", + "5ad40419604f3c001a3ffdb8": "", + "56de49a8cffd8e1900b4b7a7": "Bethencourt", + "56de49a8cffd8e1900b4b7a8": "Enrique P\u00e9rez de Guzm\u00e1n", + "56de49a8cffd8e1900b4b7a9": "Enrique P\u00e9rez de Guzm\u00e1n", + "5ad403c1604f3c001a3ffd97": "", + "5ad403c1604f3c001a3ffd98": "", + "56de4a474396321400ee2786": "the Channel Islands", + "56de4a474396321400ee2787": "two", + "5ad40358604f3c001a3ffd7d": "", + "5ad40358604f3c001a3ffd7e": "", + "5ad40358604f3c001a3ffd7f": "", + "56de4a89cffd8e1900b4b7bd": "unique Romanesque", + "56de4a89cffd8e1900b4b7be": "rounded arches", + "5ad402ce604f3c001a3ffd67": "rounded arches", + "56de4b074396321400ee2793": "Early Gothic", + "56de4b074396321400ee2794": "Anglo-Saxon", + "56de4b074396321400ee2795": "Kingdom of Sicily", + "5ad400b0604f3c001a3ffcdf": "", + "5ad400b0604f3c001a3ffce0": "Norman", + "5ad400b0604f3c001a3ffce1": "", + "56de4b5c4396321400ee2799": "early 11th century", + "56de4b5c4396321400ee279a": "the dukes", + "5ad3ffd7604f3c001a3ffca7": "", + "5ad3ffd7604f3c001a3ffca8": "", + "5ad3ffd7604f3c001a3ffca9": "duchy", + "5ad3ffd7604f3c001a3ffcaa": "", + "56de4bb84396321400ee27a2": "16th century", + "5ad3ff1b604f3c001a3ffc73": "", + "5ad3ff1b604f3c001a3ffc74": "", + "56de4c324396321400ee27ab": "embroidery", + "56de4c324396321400ee27ac": "Bayeux Tapestry", + "56de4c324396321400ee27ad": "Odo, the Bishop of Bayeux and first Earl of Kent", + "5ad3fe91604f3c001a3ffc47": "", + "5ad3fe91604f3c001a3ffc48": "", + "56de51244396321400ee27ef": "sculptured fonts, capitals, and more importantly mosaics", + "5ad3fe0d604f3c001a3ffc1b": "", + "5ad3fe0d604f3c001a3ffc1c": "stonework or metalwork", + "5ad3fe0d604f3c001a3ffc1d": "", + "56de51c64396321400ee27f7": "11th", + "56de51c64396321400ee27f8": "William of Volpiano and John of Ravenna", + "5ad3fd68604f3c001a3ffbe7": "", + "5ad3fd68604f3c001a3ffbe8": "musical production and education", + "56de52614396321400ee27fb": "southern Italy", + "56de52614396321400ee27fc": "Sant'Eufemia", + "56de52614396321400ee27fd": "Robert Guiscard", + "56de52614396321400ee27fe": "singing", + "5ad3fccf604f3c001a3ffbb5": "", + "56e16182e3433e1400422e28": "Computational complexity theory", + "56e16182e3433e1400422e29": "inherent difficulty", + "56e16182e3433e1400422e2a": "A computational problem", + "5ad5316b5b96ef001a10ab72": "", + "5ad5316b5b96ef001a10ab73": "Computational complexity theory", + "5ad5316b5b96ef001a10ab74": "", + "5ad5316b5b96ef001a10ab75": "", + "5ad5316b5b96ef001a10ab76": "", + "56e16839cd28a01900c67887": "if its solution requires significant resources", + "56e16839cd28a01900c67888": "introducing mathematical models of computation", + "56e16839cd28a01900c67889": "time and storage", + "56e16839cd28a01900c6788a": "gates", + "56e16839cd28a01900c6788b": "to determine the practical limits on what computers can and cannot do", + "5ad532575b96ef001a10ab7c": "", + "5ad532575b96ef001a10ab7d": "", + "5ad532575b96ef001a10ab7e": "time and storage", + "5ad532575b96ef001a10ab7f": "", + "5ad532575b96ef001a10ab80": "processors", + "56e17644e3433e1400422f40": "analysis of algorithms and computability theory", + "56e17644e3433e1400422f41": "computational complexity theory", + "56e17644e3433e1400422f42": "computational complexity theory", + "56e17644e3433e1400422f43": "computational complexity theory", + "5ad5344b5b96ef001a10ab86": "analysis of algorithms and computability theory", + "5ad5344b5b96ef001a10ab87": "", + "5ad5344b5b96ef001a10ab88": "", + "5ad5344b5b96ef001a10ab89": "computational complexity theory", + "5ad5344b5b96ef001a10ab8a": "", + "56e17a7ccd28a01900c679a1": "problem instance", + "56e17a7ccd28a01900c679a2": "a problem", + "56e17a7ccd28a01900c679a3": "concrete", + "56e17a7ccd28a01900c679a4": "", + "56e17a7ccd28a01900c679a5": "solution", + "5ad5364c5b96ef001a10ab90": "", + "5ad5364c5b96ef001a10ab91": "problem instance", + "5ad5364c5b96ef001a10ab92": "", + "5ad5364c5b96ef001a10ab93": "", + "5ad5364c5b96ef001a10ab94": "", + "56e17e6ee3433e1400422f7f": "2000", + "56e17e6ee3433e1400422f80": "asking for a round trip through all sites in Milan", + "56e17e6ee3433e1400422f81": "computational problems", + "5ad537a15b96ef001a10ab9a": "", + "5ad537a15b96ef001a10ab9b": "", + "5ad537a15b96ef001a10ab9c": "", + "5ad537a15b96ef001a10ab9d": "", + "56e181d9e3433e1400422fa0": "binary alphabet", + "56e181d9e3433e1400422fa1": "binary alphabet", + "56e181d9e3433e1400422fa2": "", + "56e181d9e3433e1400422fa3": "", + "56e181d9e3433e1400422fa4": "adjacency matrices", + "5ad5391e5b96ef001a10aba2": "", + "5ad5391e5b96ef001a10aba3": "", + "5ad5391e5b96ef001a10aba4": "", + "5ad5391e5b96ef001a10aba5": "", + "5ad5391e5b96ef001a10aba6": "", + "56e190bce3433e1400422fc8": "Decision problems", + "56e190bce3433e1400422fc9": "yes or no, or alternately either 1 or 0", + "56e190bce3433e1400422fca": "yes or no, or alternately either 1 or 0", + "56e190bce3433e1400422fcb": "yes", + "56e190bce3433e1400422fcc": "yes", + "5ad53b9d5b96ef001a10abc8": "Decision problems", + "5ad53b9d5b96ef001a10abc9": "", + "5ad53b9d5b96ef001a10abca": "", + "5ad53b9d5b96ef001a10abcb": "yes or no, or alternately either 1 or 0", + "5ad53b9d5b96ef001a10abcc": "", + "56e19557e3433e1400422fee": "arbitrary", + "56e19557e3433e1400422ff0": "formal language", + "56e19557e3433e1400422ff1": "", + "5ad53d705b96ef001a10abd2": "", + "5ad53d705b96ef001a10abd3": "", + "5ad53d705b96ef001a10abd4": "", + "5ad53d705b96ef001a10abd5": "", + "56e19724cd28a01900c679f6": "traveling salesman problem and the integer factorization problem", + "56e19724cd28a01900c679f7": "single", + "56e19724cd28a01900c679f8": "function problem", + "56e19724cd28a01900c679f9": "integer factorization problem", + "56e19724cd28a01900c679fa": "more complex", + "5ad53e615b96ef001a10abda": "", + "5ad53e615b96ef001a10abdb": "", + "5ad53e615b96ef001a10abdc": "", + "5ad53e615b96ef001a10abdd": "", + "5ad53e615b96ef001a10abde": "more complex", + "56e1a0dccd28a01900c67a2e": "as decision problems", + "56e1a0dccd28a01900c67a2f": "triples", + "5ad53f815b96ef001a10abe4": "", + "5ad53f815b96ef001a10abe5": "", + "5ad53f815b96ef001a10abe6": "", + "56e1a38de3433e140042305c": "", + "56e1a38de3433e140042305d": "the instance", + "56e1a38de3433e140042305e": "as a function of the size of the instance", + "56e1a38de3433e140042305f": "", + "56e1a38de3433e1400423060": "input size", + "5ad541ad5b96ef001a10abea": "", + "5ad541ad5b96ef001a10abeb": "", + "5ad541ad5b96ef001a10abec": "as a function of the size of the instance", + "5ad541ad5b96ef001a10abed": "", + "5ad541ad5b96ef001a10abee": "", + "56e1a564cd28a01900c67a48": "Cobham", + "56e1a564cd28a01900c67a49": "the time taken", + "56e1a564cd28a01900c67a4a": "the worst-case time complexity T(n)", + "56e1a564cd28a01900c67a4b": "", + "56e1a564cd28a01900c67a4c": "polynomial time algorithm", + "5ad542db5b96ef001a10abf4": "", + "5ad542db5b96ef001a10abf5": "Cobham", + "5ad542db5b96ef001a10abf6": "", + "5ad542db5b96ef001a10abf7": "", + "5ad542db5b96ef001a10abf8": "", + "56e1aba0e3433e1400423094": "Turing machine", + "56e1aba0e3433e1400423095": "an algorithm", + "56e1aba0e3433e1400423097": "the Turing machine", + "56e1aba0e3433e1400423098": "manipulates symbols", + "5ad543c05b96ef001a10abfe": "A Turing machine", + "5ad543c05b96ef001a10abff": "", + "5ad543c05b96ef001a10ac00": "", + "5ad543c05b96ef001a10ac01": "Turing machine", + "56e1aff7cd28a01900c67a68": "A deterministic Turing machine", + "56e1aff7cd28a01900c67a69": "", + "56e1aff7cd28a01900c67a6a": "probabilistic Turing machine", + "56e1aff7cd28a01900c67a6b": "non-deterministic Turing machine", + "56e1aff7cd28a01900c67a6c": "randomized algorithms", + "5ad546c75b96ef001a10ac0e": "", + "5ad546c75b96ef001a10ac0f": "", + "5ad546c75b96ef001a10ac10": "", + "5ad546c75b96ef001a10ac11": "non-deterministic Turing machine", + "5ad546c75b96ef001a10ac12": "", + "56e1b00ce3433e140042309e": "complexity classes", + "56e1b00ce3433e140042309f": "when resources (such as time or space) are bounded", + "56e1b00ce3433e14004230a1": "deterministic Turing machines, probabilistic Turing machines, non-deterministic Turing machines", + "5ad545545b96ef001a10ac06": "", + "5ad545545b96ef001a10ac07": "when resources (such as time or space) are bounded", + "5ad545545b96ef001a10ac08": "", + "5ad545545b96ef001a10ac09": "", + "56e1b169cd28a01900c67a72": "random access machines", + "56e1b169cd28a01900c67a73": "time", + "56e1b169cd28a01900c67a74": "time and memory", + "56e1b169cd28a01900c67a75": "the machines operate deterministically", + "5ad547945b96ef001a10ac18": "", + "5ad547945b96ef001a10ac19": "", + "5ad547945b96ef001a10ac1a": "", + "5ad547945b96ef001a10ac1b": "", + "56e1b355e3433e14004230b0": "non-deterministic", + "56e1b355e3433e14004230b1": "more unusual resources", + "56e1b355e3433e14004230b2": "many of the mathematical models", + "56e1b355e3433e14004230b3": "non-deterministic time", + "5ad5489b5b96ef001a10ac2a": "", + "5ad5489b5b96ef001a10ac2b": "", + "5ad5489b5b96ef001a10ac2c": "", + "5ad5489b5b96ef001a10ac2d": "", + "5ad5489b5b96ef001a10ac2e": "", + "56e1b62ecd28a01900c67aa3": "\"yes\" or \"no\"", + "56e1b62ecd28a01900c67aa4": "difficulty", + "56e1b62ecd28a01900c67aa5": "DTIME(f(n))", + "56e1b62ecd28a01900c67aa6": "complexity theory", + "5ad54a375b96ef001a10ac48": "", + "5ad54a375b96ef001a10ac49": "", + "5ad54a375b96ef001a10ac4a": "DTIME(f(n))", + "5ad54a375b96ef001a10ac4b": "", + "5ad54a375b96ef001a10ac4c": "", + "56e1b754cd28a01900c67abc": "complexity", + "56e1b754cd28a01900c67abd": "computational", + "56e1b754cd28a01900c67abe": "Blum complexity axioms", + "56e1b754cd28a01900c67abf": "complexity measures used in complexity theory", + "56e1b754cd28a01900c67ac0": "complexity measures used in complexity theory include communication complexity, circuit complexity, and decision tree complexity", + "5ad54b035b96ef001a10ac52": "", + "5ad54b035b96ef001a10ac53": "", + "5ad54b035b96ef001a10ac54": "", + "5ad54b035b96ef001a10ac55": "", + "5ad54b035b96ef001a10ac56": "", + "56e1b8f3e3433e14004230e6": "best, worst and average", + "56e1b8f3e3433e14004230e7": "time complexity", + "56e1b8f3e3433e14004230e8": "time complexity", + "56e1b8f3e3433e14004230e9": "", + "5ad54c2f5b96ef001a10ac5c": "", + "5ad54c2f5b96ef001a10ac5d": "", + "5ad54c2f5b96ef001a10ac5e": "", + "5ad54c2f5b96ef001a10ac5f": "", + "56e1ba41cd28a01900c67ae0": "quicksort", + "56e1ba41cd28a01900c67ae1": "", + "56e1ba41cd28a01900c67ae2": "time O(n2)", + "5ad54d625b96ef001a10ac64": "", + "5ad54d625b96ef001a10ac65": "", + "5ad54d625b96ef001a10ac66": "", + "5ad54d625b96ef001a10ac67": "", + "5ad54d625b96ef001a10ac68": "", + "56e1bc3ae3433e1400423104": "the most efficient algorithm solving a given problem", + "56e1bc3ae3433e1400423105": "algorithms", + "56e1bc3ae3433e1400423106": "lower bounds", + "56e1bc3ae3433e1400423107": "", + "56e1bc3ae3433e1400423108": "", + "5ad54e7c5b96ef001a10ac76": "one is interested in proving upper and lower bounds on the minimum amount of time required by the most efficient algorithm solving a given problem", + "5ad54e7c5b96ef001a10ac77": "", + "5ad54e7c5b96ef001a10ac78": "", + "5ad54e7c5b96ef001a10ac79": "", + "5ad54e7c5b96ef001a10ac7a": "", + "56e1bd4acd28a01900c67afc": "big O notation", + "56e1bd4acd28a01900c67afd": "constant factors and smaller terms", + "56e1bd4acd28a01900c67afe": "if T(n) = 7n2 + 15n + 40, in big O notation", + "56e1bd4acd28a01900c67aff": "", + "5ad54f775b96ef001a10ac88": "", + "5ad54f775b96ef001a10ac89": "", + "5ad54f775b96ef001a10ac8a": "", + "5ad54f775b96ef001a10ac8b": "", + "56e1c0f6cd28a01900c67b2c": "some complexity classes", + "56e1c0f6cd28a01900c67b2d": "framework", + "56e1c0f6cd28a01900c67b2e": "complicated definitions", + "5ad5501f5b96ef001a10ac90": "", + "5ad5501f5b96ef001a10ac91": "", + "5ad5501f5b96ef001a10ac92": "this framework", + "5ad5501f5b96ef001a10ac93": "", + "56e1c2eee3433e1400423134": "the chosen machine model", + "56e1c2eee3433e1400423135": "quadratic time", + "56e1c2eee3433e1400423136": "single-tape", + "56e1c2eee3433e1400423137": "Cobham-Edmonds", + "56e1c2eee3433e1400423138": "complexity class P", + "5ad55ee35b96ef001a10ace4": "", + "5ad55ee35b96ef001a10ace5": "", + "5ad55ee35b96ef001a10ace6": "", + "5ad55ee35b96ef001a10ace7": "", + "5ad55ee35b96ef001a10ace8": "", + "56e1c3e1e3433e1400423148": "", + "56e1c3e1e3433e1400423149": "", + "56e1c3e1e3433e140042314a": "complexity classes", + "5ad55fe75b96ef001a10ad0c": "", + "5ad55fe75b96ef001a10ad0d": "time or space", + "5ad55fe75b96ef001a10ad0e": "", + "5ad55fe75b96ef001a10ad0f": "", + "56e1c4fce3433e140042314e": "BPP, ZPP and RP", + "56e1c4fce3433e140042314f": "Boolean", + "56e1c4fce3433e1400423150": "quantum", + "56e1c4fce3433e1400423151": "#P", + "56e1c4fce3433e1400423152": "Interactive", + "5ad560b85b96ef001a10ad1e": "BPP, ZPP and RP", + "5ad560b85b96ef001a10ad1f": "", + "5ad560b85b96ef001a10ad20": "", + "5ad560b85b96ef001a10ad21": "", + "5ad560b85b96ef001a10ad22": "", + "56e1c720e3433e140042316a": "computation time", + "56e1c720e3433e140042316b": "DTIME(n2", + "56e1c720e3433e140042316c": "time and space hierarchy theorems", + "56e1c720e3433e140042316d": "", + "56e1c720e3433e140042316e": "quantitative", + "5ad561c85b96ef001a10ad3c": "", + "5ad561c85b96ef001a10ad3d": "", + "5ad561c85b96ef001a10ad3e": "", + "5ad561c85b96ef001a10ad3f": "", + "5ad561c85b96ef001a10ad40": "", + "56e1c7e2cd28a01900c67b74": "time and space hierarchy theorems", + "56e1c7e2cd28a01900c67b75": "strictly contained in EXPTIME", + "56e1c7e2cd28a01900c67b76": "PSPACE", + "5ad562525b96ef001a10ad50": "", + "5ad562525b96ef001a10ad51": "", + "5ad562525b96ef001a10ad52": "", + "5ad562525b96ef001a10ad53": "", + "56e1c9bfe3433e1400423192": "a reduction", + "56e1c9bfe3433e1400423193": "", + "56e1c9bfe3433e1400423194": "X reduces to Y", + "56e1c9bfe3433e1400423195": "Cook reductions, Karp reductions and Levin reductions", + "56e1c9bfe3433e1400423196": "bound on the complexity of reductions", + "5ad5632f5b96ef001a10ad6c": "", + "5ad5632f5b96ef001a10ad6d": "", + "5ad5632f5b96ef001a10ad6e": "", + "5ad5632f5b96ef001a10ad6f": "", + "5ad5632f5b96ef001a10ad70": "", + "56e1cbe2cd28a01900c67bac": "polynomial-time reduction", + "56e1cbe2cd28a01900c67bad": "", + "56e1cbe2cd28a01900c67bae": "", + "56e1cbe2cd28a01900c67baf": "input", + "56e1cbe2cd28a01900c67bb0": "multiplication", + "5ad5648b5b96ef001a10ad94": "", + "5ad5648b5b96ef001a10ad95": "", + "5ad5648b5b96ef001a10ad96": "", + "5ad5648b5b96ef001a10ad97": "", + "5ad5648b5b96ef001a10ad98": "", + "56e1ce08e3433e14004231a4": "the type of reduction being used", + "56e1ce08e3433e14004231a5": "", + "56e1ce08e3433e14004231a6": "solve any problem in C", + "56e1ce08e3433e14004231a8": "NP-hard problems", + "5ad565575b96ef001a10adb2": "", + "5ad565575b96ef001a10adb3": "", + "5ad565575b96ef001a10adb4": "no", + "5ad565575b96ef001a10adb5": "", + "56e1d9fee3433e14004231cb": "", + "56e1d9fee3433e14004231cc": "", + "56e1d9fee3433e14004231cd": "there is no known polynomial-time solution", + "56e1d9fee3433e14004231ce": "", + "5ad566375b96ef001a10adce": "", + "5ad566375b96ef001a10adcf": "", + "5ad566375b96ef001a10add0": "", + "5ad566375b96ef001a10add1": "", + "56e1dc62cd28a01900c67bca": "P", + "56e1dc62cd28a01900c67bcb": "Cobham\u2013Edmonds thesis", + "56e1dc62cd28a01900c67bcc": "", + "56e1dc62cd28a01900c67bcd": "Boolean satisfiability problem, the Hamiltonian path problem and the vertex cover problem", + "56e1dc62cd28a01900c67bce": "", + "5ad567055b96ef001a10adea": "", + "5ad567055b96ef001a10adeb": "", + "5ad567055b96ef001a10adec": "", + "5ad567055b96ef001a10aded": "Boolean satisfiability problem, the Hamiltonian path problem and the vertex cover problem", + "5ad567055b96ef001a10adee": "", + "56e1ddfce3433e14004231d5": "more efficient solutions", + "56e1ddfce3433e14004231d6": "protein structure prediction", + "56e1ddfce3433e14004231d8": "US$1,000,000", + "5ad568175b96ef001a10ae10": "", + "5ad568175b96ef001a10ae11": "", + "5ad568175b96ef001a10ae12": "", + "5ad568175b96ef001a10ae13": "", + "5ad568175b96ef001a10ae14": "", + "56e1ded7cd28a01900c67bd4": "Ladner", + "56e1ded7cd28a01900c67bd5": "NP-intermediate problems", + "56e1ded7cd28a01900c67bd6": "The graph isomorphism problem, the discrete logarithm problem and the integer factorization problem", + "5ad568d35b96ef001a10ae1a": "", + "5ad568d35b96ef001a10ae1b": "", + "5ad568d35b96ef001a10ae1c": "", + "5ad568d35b96ef001a10ae1d": "graph isomorphism problem, the discrete logarithm problem and the integer factorization problem", + "56e1e9dfe3433e14004231fc": "graph isomorphism problem", + "56e1e9dfe3433e14004231fd": "NP-complete", + "56e1e9dfe3433e14004231fe": "", + "56e1e9dfe3433e14004231ff": "second level", + "56e1e9dfe3433e1400423200": "Laszlo Babai and Eugene Luks", + "5ad569c05b96ef001a10ae36": "", + "5ad569c05b96ef001a10ae37": "", + "5ad569c05b96ef001a10ae38": "", + "5ad569c05b96ef001a10ae39": "", + "5ad569c05b96ef001a10ae3a": "", + "56e1ec83cd28a01900c67c0a": "integer factorization problem", + "56e1ec83cd28a01900c67c0b": "k", + "56e1ec83cd28a01900c67c0c": "", + "56e1ec83cd28a01900c67c0e": "general number field sieve", + "5ad56aea5b96ef001a10ae48": "", + "5ad56aea5b96ef001a10ae49": "", + "5ad56aea5b96ef001a10ae4a": "", + "5ad56aea5b96ef001a10ae4b": "", + "5ad56aea5b96ef001a10ae4c": "", + "56e1ee4de3433e1400423210": "", + "56e1ee4de3433e1400423211": "", + "56e1ee4de3433e1400423212": "between P and PSPACE", + "56e1ee4de3433e1400423214": "any of these classes are unequal", + "5ad56bcd5b96ef001a10ae62": "unequal", + "5ad56bcd5b96ef001a10ae63": "", + "5ad56bcd5b96ef001a10ae64": "between P and PSPACE", + "5ad56bcd5b96ef001a10ae65": "", + "5ad56bcd5b96ef001a10ae66": "", + "56e1efa0e3433e140042321a": "co-NP", + "56e1efa0e3433e140042321b": "reversed", + "56e1efa0e3433e140042321c": "It is believed that NP is not equal to co-NP", + "56e1efa0e3433e140042321d": "P is not equal to NP", + "5ad56c6b5b96ef001a10ae6c": "", + "5ad56c6b5b96ef001a10ae6d": "", + "5ad56c6b5b96ef001a10ae6e": "", + "5ad56c6b5b96ef001a10ae6f": "", + "56e1f10ee3433e1400423222": "L", + "56e1f10ee3433e1400423223": "", + "56e1f10ee3433e1400423224": "complexity classes", + "56e1f10ee3433e1400423225": "NL and NC", + "56e1f10ee3433e1400423226": "", + "5ad56d3e5b96ef001a10ae84": "", + "5ad56d3e5b96ef001a10ae85": "", + "5ad56d3e5b96ef001a10ae86": "", + "5ad56d3e5b96ef001a10ae87": "", + "5ad56d3e5b96ef001a10ae88": "it is not known if they are distinct or equal classes", + "56e1fc57e3433e140042322c": "", + "56e1fc57e3433e140042322f": "polynomial time", + "56e1fc57e3433e1400423230": "NP-complete", + "5ad56e5c5b96ef001a10ae9e": "", + "5ad56e5c5b96ef001a10ae9f": "", + "5ad56e5c5b96ef001a10aea0": "", + "5ad56e5c5b96ef001a10aea1": "", + "5ad56e5c5b96ef001a10aea2": "", + "56e1febfe3433e1400423236": "Presburger", + "56e1febfe3433e1400423237": "algorithms", + "56e1febfe3433e1400423238": "NP-complete knapsack", + "56e1febfe3433e1400423239": "less than quadratic time", + "56e1febfe3433e140042323a": "Boolean satisfiability", + "5ad56ef05b96ef001a10aea8": "Presburger", + "5ad56ef05b96ef001a10aea9": "", + "5ad56ef05b96ef001a10aeaa": "", + "5ad56ef05b96ef001a10aeab": "", + "56e200e4cd28a01900c67c14": "", + "56e200e4cd28a01900c67c15": "Alan Turing", + "56e200e4cd28a01900c67c16": "a computer", + "56e200e4cd28a01900c67c17": "1936", + "56e200e4cd28a01900c67c18": "a computer", + "5ad56fe65b96ef001a10aec2": "", + "5ad56fe65b96ef001a10aec3": "", + "5ad56fe65b96ef001a10aec4": "", + "5ad56fe65b96ef001a10aec5": "", + "5ad56fe65b96ef001a10aec6": "a computer", + "56e202e9e3433e1400423240": "\"On the Computational Complexity of Algorithms", + "56e202e9e3433e1400423241": "Juris Hartmanis and Richard Stearns", + "56e202e9e3433e1400423242": "1965", + "56e202e9e3433e1400423243": "time and space complexity", + "56e202e9e3433e1400423244": "1965", + "5ad570b25b96ef001a10aedc": "", + "5ad570b25b96ef001a10aedd": "", + "5ad570b25b96ef001a10aede": "", + "5ad570b25b96ef001a10aedf": "time and space complexity", + "56e2042ecd28a01900c67c1e": "John Myhill", + "56e2042ecd28a01900c67c1f": "", + "56e2042ecd28a01900c67c20": "Hisao Yamada", + "5ad5719f5b96ef001a10aeec": "", + "5ad5719f5b96ef001a10aeed": "", + "5ad5719f5b96ef001a10aeee": "", + "5ad5719f5b96ef001a10aeef": "", + "5ad5719f5b96ef001a10aef0": "", + "56e20a27cd28a01900c67c24": "input encoding", + "56e20a27cd28a01900c67c25": "", + "5ad53ac65b96ef001a10abac": "", + "5ad53ac65b96ef001a10abad": "input encoding", + "5ad53ac65b96ef001a10abae": "", + "5ad53ac65b96ef001a10abaf": "", + "56e20a3ae3433e140042324a": "Manuel Blum", + "56e20a3ae3433e140042324b": "speed-up theorem", + "56e20a3ae3433e140042324d": "Reducibility Among Combinatorial Problems", + "56e20a3ae3433e140042324e": "21", + "5ad572b15b96ef001a10af06": "", + "5ad572b15b96ef001a10af07": "", + "5ad572b15b96ef001a10af08": "", + "5ad572b15b96ef001a10af09": "", + "5ad572b15b96ef001a10af0a": "", + "5705e26d75f01819005e76d4": "SoCal", + "5705e26d75f01819005e76d5": "10", + "5705e26d75f01819005e76d6": "economic center", + "5705e26d75f01819005e76d7": "demographics and economic", + "5705e26d75f01819005e76d8": "demographics and economic ties", + "5ad0178577cf76001a68698a": "", + "5ad0178577cf76001a68698b": "", + "5ad0178577cf76001a68698c": "", + "5705e33f52bb89140068964c": "greater Southern California Megaregion", + "5705e33f52bb89140068964d": "11", + "5705e33f52bb89140068964e": "Las Vegas, Nevada", + "5705e33f52bb89140068964f": "Mexican border", + "5705e33f52bb891400689650": "Tijuana", + "5ad0185a77cf76001a6869b8": "", + "5ad0185a77cf76001a6869b9": "", + "5ad0185a77cf76001a6869ba": "", + "5705e3f252bb89140068966a": "Pacific coast", + "5705e3f252bb89140068966b": "seven", + "5705e3f252bb89140068966c": "12 million", + "5705e3f252bb89140068966d": "", + "5705e3f252bb89140068966e": "17.5 million", + "5ad01a6277cf76001a686a0c": "60", + "5ad01a6277cf76001a686a0d": "", + "5ad01a6277cf76001a686a0e": "over four million", + "5ad01a6277cf76001a686a0f": "", + 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"Video On Demand", + "5a2c3efbbfd06b001a5aea96": "", + "5a2c3efbbfd06b001a5aea97": "", + "570960cf200fba1400367f01": "July 2013", + "570960cf200fba1400367f02": "2013", + "570960cf200fba1400367f03": "SkyDrive cloud storage service", + "570960cf200fba1400367f04": "", + "570960cf200fba1400367f05": "cloud storage", + "5a2c41c8bfd06b001a5aeaa7": "", + "5a2c41c8bfd06b001a5aeaa8": "", + "5a2c41c8bfd06b001a5aeaa9": "", + "5a2c41c8bfd06b001a5aeaaa": "", + "5a2c41c8bfd06b001a5aeaab": "27 January 2014", + "570961aa200fba1400367f15": "Sam Chisholm and Rupert Murdoch", + "570961aa200fba1400367f16": "Astra", + "570961aa200fba1400367f17": "27 September 2001", + "570961aa200fba1400367f18": "Sky Digital", + "570961aa200fba1400367f19": "3.5 million", + "5a2c0e0dbfd06b001a5ae9af": "Sky Digital", + "5a2c0e0dbfd06b001a5ae9b0": "", + "5a2c0e0dbfd06b001a5ae9b1": "", + "5a2c0e0dbfd06b001a5ae9b2": "", + "5a2c0e0dbfd06b001a5ae9b3": "", + "570963a5200fba1400367f33": "British Sky Broadcasting or BSkyB", + "570963a5200fba1400367f34": "British telecommunications company", + "570963a5200fba1400367f35": "11 million", + "570963a5200fba1400367f36": "Freeview", + "5a2c07d5bfd06b001a5ae97f": "British Sky Broadcasting or BSkyB", + "5a2c07d5bfd06b001a5ae980": "", + "5a2c07d5bfd06b001a5ae981": "", + "5a2c07d5bfd06b001a5ae982": "", + "5a2c07d5bfd06b001a5ae983": "", + "57096505ed30961900e84082": "Sky Q Hub", + "57096505ed30961900e84083": "Sky Q Silver set top boxes", + "57096505ed30961900e84084": "share recordings and other media", + "57096505ed30961900e84085": "2016", + "57096505ed30961900e84086": "2016", + "5a2c31abbfd06b001a5aea33": "Sky Q Hub", + "5a2c31abbfd06b001a5aea34": "", + "5a2c31abbfd06b001a5aea35": "", + "5a2c31abbfd06b001a5aea36": "", + "570966e0200fba1400367f4f": "DVB-compliant MPEG-2", + "570966e0200fba1400367f50": "Dolby Digital soundtracks", + "570966e0200fba1400367f51": "MPEG-4", + "570966e0200fba1400367f52": "OpenTV", + "570966e0200fba1400367f53": "DVB-S2", + "5a2c382dbfd06b001a5aea71": "", + "5a2c382dbfd06b001a5aea72": "", + "5a2c382dbfd06b001a5aea73": "", + "5a2c382dbfd06b001a5aea74": "", + "570967c4ed30961900e840ba": "1998", + "570967c4ed30961900e840bb": "Astra 2A", + "570967c4ed30961900e840bc": "Astra 2A", + "570967c4ed30961900e840bd": "hundreds", + "570967c4ed30961900e840be": "28.5\u00b0E", + "5a2c3595bfd06b001a5aea5f": "", + "5a2c3595bfd06b001a5aea60": "", + "5a2c3595bfd06b001a5aea61": "", + "5a2c3595bfd06b001a5aea62": "", + "5709686c200fba1400367f77": "22 May 2006", + "5709686c200fba1400367f78": "40,000", + "5709686c200fba1400367f79": "Thomson", + "5709686c200fba1400367f7a": "17,000", + "5709686c200fba1400367f7b": "4,222,000", + "5a2c30dabfd06b001a5aea29": "", + "5a2c30dabfd06b001a5aea2a": "", + "5a2c30dabfd06b001a5aea2b": "", + "5a2c30dabfd06b001a5aea2c": "the BBC", + "5a2c30dabfd06b001a5aea2d": "", + "57096b66200fba1400367fa7": "8 February 2007", + "57096b66200fba1400367fa8": "March", + "57096b66200fba1400367fa9": "", + "57096b66200fba1400367faa": "Virgin Media", + "57096b66200fba1400367fab": "English Premier League Football", + "5a2c1622bfd06b001a5ae9dd": "", + "5a2c1622bfd06b001a5ae9de": "", + "5a2c1622bfd06b001a5ae9df": "", + "5a2c1622bfd06b001a5ae9e0": "", + "5a2c1622bfd06b001a5ae9e1": "", + "57096c95200fba1400367fbb": "", + "57096c95200fba1400367fbc": "", + "57096c95200fba1400367fbd": "a VideoGuard UK equipped receiver", + "57096c95200fba1400367fbe": "LNB", + "57096c95200fba1400367fbf": "", + "5a2c36c4bfd06b001a5aea67": "", + "5a2c36c4bfd06b001a5aea68": "", + "5a2c36c4bfd06b001a5aea69": "", + "5a2c36c4bfd06b001a5aea6a": "", + "5a2c36c4bfd06b001a5aea6b": "", + "57096e1ced30961900e84102": "", + "57096e1ced30961900e84103": "ITV were the current rights holders", + "57096e1ced30961900e84104": "\u00a334m per year", + "57096e1ced30961900e84105": "The BBC", + "57096e1ced30961900e84106": "\u00a3304m", + "5a2c0a5abfd06b001a5ae993": "", + "5a2c0a5abfd06b001a5ae994": "\u00a3304m", + "5a2c0a5abfd06b001a5ae995": "", + "5a2c0a5abfd06b001a5ae996": "", + "57096f37200fba1400367fe5": "Ofcom", + "57096f37200fba1400367fe6": "\u00a315\u2013100,000", + "57096f37200fba1400367fe7": "BSkyB has no veto", + "57096f37200fba1400367fe8": "BSkyB does not carry any control over the channel's content", + "57096f37200fba1400367fe9": "BSkyB does not carry any control over the channel's content or carriage issues such as picture quality", + "5a2c3ca9bfd06b001a5aea83": "", + "5a2c3ca9bfd06b001a5aea84": "", + "5a2c3ca9bfd06b001a5aea85": "", + "5a2c3ca9bfd06b001a5aea86": "", + "57097051ed30961900e84132": "1 October 1998", + "57097051ed30961900e84133": "Sky Digital", + "57097051ed30961900e84134": "Sky Active", + "57097051ed30961900e84135": "", + "57097051ed30961900e84136": "over 100,000", + "5a2c0fb8bfd06b001a5ae9b9": "", + "5a2c0fb8bfd06b001a5ae9ba": "", + "5a2c0fb8bfd06b001a5ae9bb": "", + "5a2c0fb8bfd06b001a5ae9bc": "", + "57097141200fba1400367ff9": "2007", + "57097141200fba1400367ffa": "", + "57097141200fba1400367ffb": "Video On Demand service", + "57097141200fba1400367ffc": "BBC HD", + "57097141200fba1400367ffd": "Channel 4 HD", + "5a2c3d73bfd06b001a5aea8b": "2007", + "5a2c3d73bfd06b001a5aea8c": "", + "5a2c3d73bfd06b001a5aea8d": "", + "5a2c3d73bfd06b001a5aea8e": "", + "57097b50200fba140036804d": "10 million", + "57097b50200fba140036804e": "more than 25m", + "57097b50200fba140036804f": "August 2004", + "57097b50200fba1400368050": "36%", + "57097b50200fba1400368051": "flattened", + "5a2c116ebfd06b001a5ae9c1": "", + "5a2c116ebfd06b001a5ae9c2": "", + "5a2c116ebfd06b001a5ae9c3": "", + "5a2c116ebfd06b001a5ae9c4": "", + "57097c8fed30961900e841f2": "Welfare Cash Card", + "57097c8fed30961900e841f3": "only \"essentials", + "57097c8fed30961900e841f4": "often damaging", + "57097c8fed30961900e841f5": "Sky TV bills", + "57097c8fed30961900e841f6": "betray a man's presence in the household", + "5a2c1397bfd06b001a5ae9c9": "", + "5a2c1397bfd06b001a5ae9ca": "", + "5a2c1397bfd06b001a5ae9cb": "often damaging", + "5a2c1397bfd06b001a5ae9cc": "", + "5a2c1397bfd06b001a5ae9cd": "", + "57097d63ed30961900e841fc": "\u00a330m", + "57097d63ed30961900e841fd": "there is no indication as to whether", + "57097d63ed30961900e841fe": "Virgin Media", + "57097d63ed30961900e841ff": "", + "57097d63ed30961900e84200": "", + "5a2c40b8bfd06b001a5aea9d": "", + "5a2c40b8bfd06b001a5aea9e": "", + "5a2c40b8bfd06b001a5aea9f": "", + "5a2c40b8bfd06b001a5aeaa0": "", + "5a2c40b8bfd06b001a5aeaa1": "", + "570d2417fed7b91900d45c3d": "highly diversified", + "570d2417fed7b91900d45c3e": "second", + "570d2417fed7b91900d45c3f": "fourth", + "570d2417fed7b91900d45c40": "Melbourne", + "570d2417fed7b91900d45c41": "Melbourne Cricket Ground", + "5a6374de68151a001a9222e6": "public universities", + "5a6374de68151a001a9222e7": "second", + "5a6374de68151a001a9222e8": "fourth", + "5a6374de68151a001a9222e9": "Melbourne", + "5a6374de68151a001a9222ea": "eight", + "570d2556fed7b91900d45c47": "", + "570d2556fed7b91900d45c48": "New South Wales", + "570d2556fed7b91900d45c49": "Buckland Valley near Bright", + "570d2556fed7b91900d45c4a": "over 1,000", + "570d2556fed7b91900d45c4b": "cramped and unsanitary", + "5a637a8868151a001a922304": "", + "5a637a8868151a001a922305": "", + "5a637a8868151a001a922306": "Buckland Valley", + "5a637a8868151a001a922307": "", + "5a637a8868151a001a922308": "", + "570d26efb3d812140066d48f": "multi-member proportional representation system", + "570d26efb3d812140066d490": "eight", + "570d26efb3d812140066d491": "five", + "570d26efb3d812140066d492": "four years", + "570d26efb3d812140066d493": "November every four years", + "5a637f8768151a001a922318": "eight", + "5a637f8768151a001a922319": "five", + "5a637f8768151a001a92231b": "", + "5a637f8768151a001a92231c": "November", + "570d28bdb3d812140066d4a3": "Labor", + "570d28bdb3d812140066d4a4": "Liberals", + "570d28bdb3d812140066d4a5": "Liberals", + "570d28bdb3d812140066d4a6": "The Greens", + "570d28bdb3d812140066d4a7": "Liberals", + "5a63866968151a001a922336": "", + "5a63866968151a001a922337": "Australian Labor Party", + "5a63866968151a001a922338": "The Greens", + "5a63866968151a001a922339": "Australian Labor Party", + "5a63866968151a001a92233a": "Liberals", + "570d29c2b3d812140066d4bd": "61.1%", + "570d29c2b3d812140066d4be": "", + "570d29c2b3d812140066d4bf": "Buddhism", + "570d29c2b3d812140066d4c0": "168,637", + "570d29c2b3d812140066d4c1": "", + "5a63888168151a001a922340": "", + "5a63888168151a001a922341": "", + "5a63888168151a001a922342": "", + "5a63888168151a001a922343": "168,637", + "5a63888168151a001a922344": "152,775", + "570d2af0fed7b91900d45c93": "south-east", + "570d2af0fed7b91900d45c94": "second-most populous state overall", + "570d2af0fed7b91900d45c95": "most densely populated state and its second-most populous state overall", + "570d2af0fed7b91900d45c96": "Melbourne", + "570d2af0fed7b91900d45c97": "second-largest", + "5a636c5a68151a001a9222c8": "", + "5a636c5a68151a001a9222c9": "second-most populous state overall", + "5a636c5a68151a001a9222ca": "most densely populated state and its second-most populous state overall", + "5a636c5a68151a001a9222cb": "Melbourne", + "5a636c5a68151a001a9222cc": "", + "570d2c20fed7b91900d45ca7": "the Koori", + "570d2c20fed7b91900d45ca8": "1788", + "570d2c20fed7b91900d45ca9": "Sullivan Bay", + "570d2c20fed7b91900d45caa": "Sullivan Bay", + "570d2c20fed7b91900d45cab": "1803", + "5a636ede68151a001a9222d2": "the Koori", + "5a636ede68151a001a9222d3": "", + "5a636ede68151a001a9222d4": "Sullivan Bay", + "5a636ede68151a001a9222d5": "Sullivan Bay", + "5a636ede68151a001a9222d6": "1927", + "570d2d68fed7b91900d45cbb": "More than 26,000 square kilometres", + "570d2d68fed7b91900d45cbc": "50%", + "570d2d68fed7b91900d45cbd": "6,000 square kilometres", + "570d2d68fed7b91900d45cbe": "", + "570d2d68fed7b91900d45cbf": "270,000", + "5a638d2768151a001a92236e": "", + "5a638d2768151a001a92236f": "", + "5a638d2768151a001a922370": "", + "5a638d2768151a001a922371": "", + "5a638d2768151a001a922372": "", + "570d2f5bfed7b91900d45ccf": "1975", + "570d2f5bfed7b91900d45cd0": "1855 colonial constitution", + "570d2f5bfed7b91900d45cd1": "Parliament of Victoria", + "570d2f5bfed7b91900d45cd2": "an absolute majority in both houses, a three-fifths majority in both houses, or the approval of the Victorian people in a referendum", + "570d2f5bfed7b91900d45cd3": "Victoria Constitution Act 1855", + "5a63835a68151a001a92232c": "", + "5a63835a68151a001a92232d": "1855 colonial constitution", + "5a63835a68151a001a92232e": "", + "5a63835a68151a001a92232f": "\"entrenched\" provisions that require either an absolute majority in both houses, a three-fifths majority in both houses", + "5a63835a68151a001a922330": "", + "570d30fdfed7b91900d45ce3": "warmest", + "570d30fdfed7b91900d45ce4": "32 \u00b0C (90 \u00b0F)", + "570d30fdfed7b91900d45ce5": "32 \u00b0C (90 \u00b0F)", + "570d30fdfed7b91900d45ce6": "48.8 \u00b0C", + "570d30fdfed7b91900d45ce7": "7 February 2009", + "5a6395e668151a001a9223a0": "hot winds blowing from nearby semi-deserts", + "5a6395e668151a001a9223a1": "15 \u00b0C (59 \u00b0F)", + "5a6395e668151a001a9223a2": "32 \u00b0C (90 \u00b0F)", + "5a6395e668151a001a9223a3": "48.8 \u00b0C", + "5a6395e668151a001a9223a4": "7 February 2009", + "570d32e4fed7b91900d45d01": "state or government schools", + "570d32e4fed7b91900d45d02": "Victoria Department of Education", + "570d32e4fed7b91900d45d03": "extra costs", + "570d32e4fed7b91900d45d04": "Roman Catholic Church", + "570d32e4fed7b91900d45d05": "curriculum standards", + "5a638a2468151a001a92234a": "", + "5a638a2468151a001a92234b": "", + "5a638a2468151a001a92234c": "", + "5a638a2468151a001a92234d": "Roman Catholic Church", + "5a638a2468151a001a92234e": "", + "570d3468b3d812140066d543": "", + "570d3468b3d812140066d544": "February 2014", + "570d3468b3d812140066d545": "May 2013", + "570d3468b3d812140066d546": "October 2016", + "570d3468b3d812140066d547": "", + "5a638ffe68151a001a922382": "", + "5a638ffe68151a001a922383": "", + "5a638ffe68151a001a922384": "May 2013", + "5a638ffe68151a001a922385": "", + "5a638ffe68151a001a922386": "", + "570d35b7b3d812140066d54d": "2,000 m (6,600 ft)", + "570d35b7b3d812140066d54e": "Mount Bogong", + "570d35b7b3d812140066d54f": "1,986 m", + "570d35b7b3d812140066d550": "", + "570d35b7b3d812140066d551": "helmeted honeyeater", + "5a6394b768151a001a922396": "2,000 m (6,600 ft)", + "5a6394b768151a001a922397": "Mount Bogong", + "5a6394b768151a001a922398": "", + "5a6394b768151a001a922399": "", + "5a6394b768151a001a92239a": "pink", + "570d391fb3d812140066d575": "The Victorian Alps in the northeast", + "570d391fb3d812140066d576": "Great Dividing Range mountain system", + "570d391fb3d812140066d577": "east-west", + "570d391fb3d812140066d578": "0 \u00b0C (32 \u00b0F)", + "570d391fb3d812140066d579": "\u221211.7 \u00b0C", + "5a63969068151a001a9223aa": "", + "5a63969068151a001a9223ab": "Great Dividing Range", + "5a63969068151a001a9223ac": "east-west", + "5a63969068151a001a9223ad": "less than 9 \u00b0C (48 \u00b0F)", + "5a63969068151a001a9223ae": "\u221211.7 \u00b0C", + "570d4030fed7b91900d45d9f": "government", + "570d4030fed7b91900d45da0": "Metro Trains Melbourne", + "570d4030fed7b91900d45da1": "Victorian Government", + "570d4030fed7b91900d45da2": "freight services", + "570d4030fed7b91900d45da3": "extensive, electrified, passenger system", + "5a63981168151a001a9223b4": "private and public railway operators", + "5a63981168151a001a9223b5": "Great Southern Rail which operates The Overland Melbourne\u2014Adelaide; and NSW TrainLink", + "5a63981168151a001a9223b6": "Victorian Government", + "5a63981168151a001a9223b7": "CFCL Australia", + "5a63981168151a001a9223b8": "Pacific National, CFCL Australia", + "570d418dfed7b91900d45dbd": "37", + "570d418dfed7b91900d45dbe": "12", + "570d418dfed7b91900d45dbf": "Legislative Assembly", + "570d418dfed7b91900d45dc0": "the Legislative Council", + "570d418dfed7b91900d45dc1": "Linda Dessau", + "5a63730568151a001a9222dc": "37", + "5a63730568151a001a9222dd": "12", + "5a63730568151a001a9222de": "Legislative Assembly", + "5a63730568151a001a9222df": "the Legislative Council", + "5a63730568151a001a9222e0": "", + "570d4329fed7b91900d45dd7": "1 July 1851", + "570d4329fed7b91900d45dd8": "1851", + "570d4329fed7b91900d45dd9": "one of the largest gold rushes", + "570d4329fed7b91900d45dda": "sevenfold", + "570d4329fed7b91900d45ddb": "20 million ounces", + "5a63787868151a001a9222fa": "", + "5a63787868151a001a9222fb": "", + "5a63787868151a001a9222fc": "", + "5a63787868151a001a9222fd": "", + "5a63787868151a001a9222fe": "20 million ounces", + "570d44abb3d812140066d5fd": "1,548", + "570d44abb3d812140066d5fe": "489", + "570d44abb3d812140066d5ff": "Just under 540,800", + "570d44abb3d812140066d600": "63,519", + "570d44abb3d812140066d601": "Over 61", + "5a638b3668151a001a92235a": "", + "5a638b3668151a001a92235b": "489", + "5a638b3668151a001a92235c": "", + "5a638b3668151a001a92235d": "", + "5a638b3668151a001a92235e": "", + "570d4606b3d812140066d619": "Victoria", + "570d4606b3d812140066d61a": "3 million", + "570d4606b3d812140066d61b": "60%", + "570d4606b3d812140066d61c": "nearly two-thirds", + "570d4606b3d812140066d61d": "Asia", + "5a638e4468151a001a922378": "", + "5a638e4468151a001a922379": "", + "5a638e4468151a001a92237a": "60%", + "5a638e4468151a001a92237b": "60%", + "5a638e4468151a001a92237c": "", + "570d47b8b3d812140066d62d": "1,600 mm (5 ft 3 in) broad gauge", + "570d47b8b3d812140066d62e": "1,435 mm (4 ft 8 1\u20442 in) standard gauge", + "570d47b8b3d812140066d62f": "760 mm", + "570d47b8b3d812140066d630": "mountainous areas", + "570d47b8b3d812140066d631": "five", + "5a6398fd7f3c80001a150aef": "1,600 mm (5 ft 3 in) broad gauge", + "5a6398fd7f3c80001a150af0": "", + "5a6398fd7f3c80001a150af1": "", + "5a6398fd7f3c80001a150af2": "", + "5a6398fd7f3c80001a150af3": "", + "570d4a6bfed7b91900d45e13": "1788", + "570d4a6bfed7b91900d45e14": "New South Wales", + "570d4a6bfed7b91900d45e15": "New Holland", + "570d4a6bfed7b91900d45e16": "Sydney", + "5a63772268151a001a9222f0": "", + "5a63772268151a001a9222f2": "New Holland", + "5a63772268151a001a9222f3": "", + "5a63772268151a001a9222f4": "", + "570d4c3bfed7b91900d45e31": "1854", + "570d4c3bfed7b91900d45e32": "Eureka Stockade", + "570d4c3bfed7b91900d45e33": "British troops", + "570d4c3bfed7b91900d45e34": "mining licence fees", + "570d4c3bfed7b91900d45e35": "Colony of Victoria Act 1855", + "5a637c6268151a001a92230e": "1854", + "5a637c6268151a001a92230f": "British troops", + "5a637c6268151a001a922310": "mining licence fees", + "5a637c6268151a001a922311": "", + "5a637c6268151a001a922312": "", + "570d4e6cb3d812140066d66d": "political party or coalition", + "570d4e6cb3d812140066d66e": "cabinet", + "570d4e6cb3d812140066d66f": "representatives elected to either house of parliament", + "570d4e6cb3d812140066d670": "Daniel Andrews", + "570d4e6cb3d812140066d671": "elected to either house of parliament", + "5a6381d868151a001a922322": "", + "5a6381d868151a001a922323": "", + "5a6381d868151a001a922324": "", + "5a6381d868151a001a922325": "", + "5a6381d868151a001a922326": "", + "570d50a5fed7b91900d45e7d": "17% to $8.7 billion", + "570d50a5fed7b91900d45e7e": "17%", + "570d50a5fed7b91900d45e7f": "32,463", + "570d50a5fed7b91900d45e80": "60%", + "570d50a5fed7b91900d45e81": "60%", + "5a638bf768151a001a922364": "", + "5a638bf768151a001a922365": "", + "5a638bf768151a001a922366": "", + "5a638bf768151a001a922367": "A quarter", + "5a638bf768151a001a922368": "A quarter", + "570d529fb3d812140066d6bb": "tourism", + "570d529fb3d812140066d6bc": "sports tourism", + "570d529fb3d812140066d6bd": "Melbourne", + "570d529fb3d812140066d6be": "regional cities", + "570d529fb3d812140066d6bf": "SurfClassic", + "5a6391c268151a001a92238c": "", + "5a6391c268151a001a92238d": "Australian International Airshow", + "5a6391c268151a001a92238e": "", + "5a6391c268151a001a92238f": "regional cities", + "5a6391c268151a001a922390": "Port Fairy Folk Festival", + "57105da9a58dae1900cd699e": "southern and central parts", + "57105da9a58dae1900cd699f": "one-eighth", + "57105da9a58dae1900cd69a0": "1562 to 1598", + "57105da9a58dae1900cd69a1": "Edict of Nantes", + "57105da9a58dae1900cd69a2": "Catholic hostility grew", + "5ad23fded7d075001a4288fc": "1562", + "5ad23fded7d075001a4288fd": "", + "5ad23fded7d075001a4288fe": "", + "5ad23fded7d075001a4288ff": "", + "5ad23fded7d075001a428900": "", + "57106185b654c5140001f8db": "derision", + "57106185b654c5140001f8dc": "Besan\u00e7on Hugues", + "57106185b654c5140001f8dd": "Geneva", + "57106185b654c5140001f8de": "Amboise", + "57106185b654c5140001f8df": "1560", + "5ad241c7d7d075001a428978": "", + "5ad241c7d7d075001a428979": "housemates", + "5ad241c7d7d075001a42897a": "Geneva", + "5ad241c7d7d075001a42897b": "Geneva was John Calvin's adopted home and the centre of the Calvinist", + "5ad241c7d7d075001a42897c": "", + "57106644b654c5140001f8e5": "The availability of the Bible in vernacular languages", + "57106644b654c5140001f8e6": "1294", + "57106644b654c5140001f8e7": "Guyard de Moulin", + "57106644b654c5140001f8e8": "1487", + "57106644b654c5140001f8e9": "Paris", + "5ad243abd7d075001a428a10": "", + "5ad243abd7d075001a428a11": "France", + "5ad243abd7d075001a428a12": "", + "5ad243abd7d075001a428a13": "", + "5ad243abd7d075001a428a14": "Paris", + "57106d2fb654c5140001f8ef": "villes de s\u00fbret\u00e9", + "57106d2fb654c5140001f8f0": "Montpellier", + "57106d2fb654c5140001f8f1": "1622", + "57106d2fb654c5140001f8f2": "", + "57106d2fb654c5140001f8f3": "1598", + "5ad24a2ad7d075001a428bb8": "Protestant rule was dead", + "5ad24a2ad7d075001a428bb9": "Huguenots", + "5ad24a2ad7d075001a428bba": "", + "5ad24a2ad7d075001a428bbb": "1629", + "5ad24a2ad7d075001a428bbc": "", + "571077ecb654c5140001f909": "Cape of Good Hope", + "571077ecb654c5140001f90a": "Cape Town", + "571077ecb654c5140001f90b": "Maria de la Queillerie", + "571077ecb654c5140001f90c": "Dutch East India Company", + "571077ecb654c5140001f90d": "", + "5ad25b9ed7d075001a428e6e": "", + "5ad25b9ed7d075001a428e6f": "", + "5ad25b9ed7d075001a428e70": "", + "5ad25b9ed7d075001a428e71": "", + "5ad25b9ed7d075001a428e72": "", + "57107932a58dae1900cd69ca": "1624", + "57107932a58dae1900cd69cb": "Jess\u00e9 de Forest", + "57107932a58dae1900cd69cc": "L'\u00c9glise fran\u00e7aise \u00e0 la Nouvelle-Amsterdam", + "57107932a58dae1900cd69cd": "L'Eglise du Saint-Esprit", + "57107932a58dae1900cd69ce": "Brooklyn", + "5ad25e99d7d075001a428f2e": "", + "5ad25e99d7d075001a428f2f": "", + "5ad25e99d7d075001a428f30": "", + "5ad25e99d7d075001a428f31": "New Netherland", + "5ad25e99d7d075001a428f32": "", + "57107a3ea58dae1900cd69de": "Charleston", + "57107a3ea58dae1900cd69df": "Charleston", + "57107a3ea58dae1900cd69e0": "1697", + "57107a3ea58dae1900cd69e1": "Edmund Bellinger", + "57107a3ea58dae1900cd69e2": "Pons", + "5ad263d9d7d075001a429122": "", + "5ad263d9d7d075001a429123": "", + "5ad263d9d7d075001a429124": "1685", + "5ad263d9d7d075001a429125": "", + "5ad263d9d7d075001a429126": "", + "57107c24a58dae1900cd69e8": "William III of Orange", + "57107c24a58dae1900cd69e9": "King of England", + "57107c24a58dae1900cd69ea": "League of Augsburg", + "57107c24a58dae1900cd69eb": "", + "57107c24a58dae1900cd69ec": "", + "5ad267dbd7d075001a42923e": "", + "5ad267dbd7d075001a42923f": "", + "5ad267dbd7d075001a429240": "", + "5ad267dbd7d075001a429241": "", + "57107d73b654c5140001f91d": "Edict of Fontainebleau", + "57107d73b654c5140001f91e": "1685", + "57107d73b654c5140001f91f": "", + "57107d73b654c5140001f920": "", + "5ad24056d7d075001a42892c": "", + "5ad24057d7d075001a42892e": "", + "5ad24057d7d075001a42892f": "", + "5ad24057d7d075001a428930": "", + "57107e6ca58dae1900cd69f2": "The Catholic Church in France", + "57107e6ca58dae1900cd69f3": "", + "57107e6ca58dae1900cd69f4": "5,000 to 30,000", + "57107e6ca58dae1900cd69f5": "the Huguenots had their own militia", + "57107e6ca58dae1900cd69f6": "", + "5ad2454cd7d075001a428a92": "", + "5ad2454cd7d075001a428a93": "", + "5ad2454cd7d075001a428a94": "", + "5ad2454cd7d075001a428a95": "", + "57108073b654c5140001f925": "Huguenot rebellions", + "57108073b654c5140001f926": "southwestern France", + "57108073b654c5140001f927": "between 1621 and 1629", + "57108073b654c5140001f928": "Louis XIII", + "57108073b654c5140001f929": "Louis XIII", + "5ad24b60d7d075001a428be4": "", + "5ad24b60d7d075001a428be5": "", + "5ad24b60d7d075001a428be6": "Italian", + "5ad24b60d7d075001a428be7": "foreign powers", + "5ad24b60d7d075001a428be8": "", + "57108198b654c5140001f937": "Approximately one million", + "57108198b654c5140001f938": "2%", + "57108198b654c5140001f939": "Alsace", + "57108198b654c5140001f93a": "C\u00e9vennes mountain region", + "57108198b654c5140001f93b": "", + "5ad25878d7d075001a428dc6": "", + "5ad25878d7d075001a428dc7": "", + "5ad25878d7d075001a428dc8": "", + "5ad25878d7d075001a428dc9": "", + "5ad25878d7d075001a428dca": "", + "57108c95b654c5140001f979": "New Rochelle", + "57108c95b654c5140001f97a": "New Rochelle", + "57108c95b654c5140001f97b": "Huguenot Street Historic District", + "57108c95b654c5140001f97c": "Huguenot Street Historic District", + "57108c95b654c5140001f97d": "Staten Island", + "5ad25f29d7d075001a428f60": "21 miles north", + "5ad25f29d7d075001a428f61": "21 miles", + "5ad25f29d7d075001a428f62": "21 miles", + "5ad25f29d7d075001a428f63": "south shore of Staten Island along the New York Harbor", + "5ad25f29d7d075001a428f64": "south shore of Staten Island", + "57108d69b654c5140001f983": "the Dutch Republic", + "57108d69b654c5140001f984": "75,000 to 100,000", + "57108d69b654c5140001f985": "", + "57108d69b654c5140001f986": "Amsterdam and the area of West Frisia", + "57108d69b654c5140001f987": "Edict of Nantes", + "5ad268cbd7d075001a429292": "", + "5ad268cbd7d075001a429293": "", + "5ad268cbd7d075001a429294": "", + "5ad268cbd7d075001a429295": "200", + "5ad268cbd7d075001a429296": "", + "57108ee6a58dae1900cd6a1a": "Huguon", + "57108ee6a58dae1900cd6a1b": "Huguon", + "57108ee6a58dae1900cd6a1c": "le roi Huguet", + "57108ee6a58dae1900cd6a1d": "pr\u00e9tendus r\u00e9form\u00e9s", + "57108ee6a58dae1900cd6a1e": "night", + "5ad24319d7d075001a4289cc": "", + "5ad24319d7d075001a4289cd": "", + "5ad24319d7d075001a4289ce": "", + "5ad24319d7d075001a4289cf": "", + "5ad24319d7d075001a4289d0": "", + "571090abb654c5140001f995": "", + "571090abb654c5140001f996": "The Weavers", + "571090abb654c5140001f997": "the variety of occupations necessary to sustain the community", + "571090abb654c5140001f998": "", + "571090abb654c5140001f999": "", + "5ad26c87d7d075001a429398": "", + "5ad26c87d7d075001a429399": "", + "5ad26c87d7d075001a42939a": "", + "5ad26c87d7d075001a42939b": "", + "5ad26c87d7d075001a42939c": "", + "57109180a58dae1900cd6a40": "", + "57109180a58dae1900cd6a41": "Cork City", + "57109180a58dae1900cd6a42": "Dublin", + "57109180a58dae1900cd6a43": "a High Sheriff and one of the founders of the Bank of Ireland", + "57109180a58dae1900cd6a44": "1696", + "5ad27081d7d075001a429454": "", + "5ad27081d7d075001a429455": "", + "5ad27081d7d075001a429456": "", + "5ad27081d7d075001a429457": "", + "5ad27081d7d075001a429458": "", + "57109275b654c5140001f99f": "brain drain", + "57109275b654c5140001f9a0": "", + "57109275b654c5140001f9a1": "non-Catholics", + "57109275b654c5140001f9a2": "the North American front of the Seven Years' War", + "57109275b654c5140001f9a3": "1759-60", + "5ad27473d7d075001a4294e8": "", + "5ad27473d7d075001a4294e9": "", + "5ad27473d7d075001a4294ea": "", + "5ad27473d7d075001a4294eb": "", + "571093aba58dae1900cd6a5c": "", + "571093aba58dae1900cd6a5d": "1598", + "571093aba58dae1900cd6a5e": "", + "571093aba58dae1900cd6a5f": "the founding of new Protestant churches", + "571093aba58dae1900cd6a60": "Protestantism", + "5ad248f7d7d075001a428b8c": "", + "5ad248f7d7d075001a428b8d": "", + "5ad248f7d7d075001a428b8e": "", + "5ad248f7d7d075001a428b8f": "", + "571094b7a58dae1900cd6a66": "education", + "571094b7a58dae1900cd6a67": "prohibited emigration", + "571094b7a58dae1900cd6a68": "Four thousand", + "571094b7a58dae1900cd6a69": "new converts", + "571094b7a58dae1900cd6a6a": "New York and Virginia", + "5ad24e85d7d075001a428c4e": "", + "5ad24e85d7d075001a428c4f": "", + "5ad24e85d7d075001a428c50": "France", + "5ad24e85d7d075001a428c51": "", + "5ad24e85d7d075001a428c52": "", + "571095a8a58dae1900cd6a76": "Switzerland and the Netherlands", + "571095a8a58dae1900cd6a77": "", + "571095a8a58dae1900cd6a78": "", + "571095a8a58dae1900cd6a79": "1560", + "571095a8a58dae1900cd6a7a": "the Guanabara Confession of Faith", + "5ad25963d7d075001a428e0c": "", + "5ad25963d7d075001a428e0d": "", + "5ad25963d7d075001a428e0e": "", + "5ad25963d7d075001a428e0f": "", + "5710968aa58dae1900cd6a86": "Afrikaans", + "5710968aa58dae1900cd6a87": "wine", + "5710968aa58dae1900cd6a88": "Western Cape province", + "5710968aa58dae1900cd6a89": "surnames", + "5ad25c69d7d075001a428ea4": "Huguenots", + "5ad25c69d7d075001a428ea5": "Huguenots", + "5ad25c69d7d075001a428ea6": "", + "5ad25c69d7d075001a428ea7": "", + "571097baa58dae1900cd6a98": "", + "571097baa58dae1900cd6a99": "Henry Laurens", + "571097baa58dae1900cd6a9a": "Charleston, South Carolina", + "571097baa58dae1900cd6a9b": "Manakin Episcopal Church", + "571097baa58dae1900cd6a9c": "Texas", + "5ad26586d7d075001a4291b2": "", + "5ad26586d7d075001a4291b3": "", + "5ad26586d7d075001a4291b4": "", + "5ad26586d7d075001a4291b5": "", + "5ad26586d7d075001a4291b6": "", + "571098f8a58dae1900cd6ab2": "British lace", + "571098f8a58dae1900cd6ab3": "Bucks Point", + "571098f8a58dae1900cd6ab4": "", + "571098f8a58dae1900cd6ab5": "first half of the eighteenth century", + "5ad26e85d7d075001a4293f2": "", + "5ad26e85d7d075001a4293f3": "", + "5ad26e85d7d075001a4293f4": "", + "5ad26e85d7d075001a4293f5": "", + "571099b2b654c5140001f9b3": "Dorotheenstadt and Friedrichstadt", + "571099b2b654c5140001f9b4": "one-fifth", + "571099b2b654c5140001f9b5": "in protest against the occupation of Prussia", + "571099b2b654c5140001f9b6": "1806-07", + "571099b2b654c5140001f9b7": "", + "5ad27294d7d075001a42949a": "", + "5ad27294d7d075001a42949b": "", + "5ad27294d7d075001a42949c": "", + "5ad27294d7d075001a42949d": "", + "5ad27294d7d075001a42949e": "", + "5710e8c8a58dae1900cd6b26": "", + "5710e8c8a58dae1900cd6b27": "C\u00e9vennes region", + "5710e8c8a58dae1900cd6b28": "Camisards", + "5710e8c8a58dae1900cd6b29": "the Catholic Church", + "5710e8c8a58dae1900cd6b2a": "1702 and 1709", + "5ad24f27d7d075001a428c88": "", + "5ad24f27d7d075001a428c89": "", + "5ad24f27d7d075001a428c8a": "", + "5ad24f27d7d075001a428c8b": "", + "5ad24f27d7d075001a428c8c": "", + "5710e9f8a58dae1900cd6b30": "", + "5710e9f8a58dae1900cd6b31": "", + "5710e9f8a58dae1900cd6b32": "Fort Caroline", + "5710e9f8a58dae1900cd6b33": "French", + "5710e9f8a58dae1900cd6b34": "", + "5ad25aa1d7d075001a428e40": "", + "5ad25aa1d7d075001a428e41": "", + "5ad25aa1d7d075001a428e42": "", + "5ad25aa1d7d075001a428e43": "", + "5710eb6fb654c5140001fa17": "Charlesfort", + "5710eb6fb654c5140001fa18": "Fort Caroline", + "5710eb6fb654c5140001fa19": "Pedro Men\u00e9ndez de Avil\u00e9s", + "5710eb6fb654c5140001fa1a": "1562", + "5710eb6fb654c5140001fa1b": "The Wars of Religion", + "5ad25d49d7d075001a428eec": "", + "5ad25d49d7d075001a428eed": "", + "5ad25d49d7d075001a428eee": "", + "5ad25d49d7d075001a428eef": "", + "5ad25d49d7d075001a428ef0": "", + "5710eca0a58dae1900cd6b3a": "Virginia", + "5710eca0a58dae1900cd6b3b": "Lower Norfolk County", + "5710eca0a58dae1900cd6b3c": "Manakin Town", + "5710eca0a58dae1900cd6b3d": "390", + "5710eca0a58dae1900cd6b3e": "", + "5ad26278d7d075001a4290ac": "", + "5ad26278d7d075001a4290ad": "", + "5ad26278d7d075001a4290ae": "", + "5ad26278d7d075001a4290af": "", + "5ad26278d7d075001a4290b0": "", + "5710ed7bb654c5140001fa2b": "1568\u20131609", + "5710ed7bb654c5140001fa2c": "Spain", + "5710ed7bb654c5140001fa2d": "William the Silent", + "5710ed7bb654c5140001fa2e": "William the Silent", + "5710ed7bb654c5140001fa2f": "", + "5ad266f8d7d075001a429206": "", + "5ad266f8d7d075001a429207": "Huguenot", + "5ad266f8d7d075001a429208": "", + "5ad266f8d7d075001a429209": "", + "5ad266f8d7d075001a42920a": "", + "5710f114a58dae1900cd6b60": "Foreign Protestants Naturalization Act", + "5710f114a58dae1900cd6b61": "1708", + "5710f114a58dae1900cd6b62": "50,000", + "5710f114a58dae1900cd6b63": "Andrew Lortie", + "5710f114a58dae1900cd6b64": "the Pope", + "5ad26ba1d7d075001a429358": "50,000", + "5ad26ba1d7d075001a429359": "50,000", + "5ad26ba1d7d075001a42935a": "Andr\u00e9 Lortie", + "5ad26ba1d7d075001a42935b": "", + "5ad26ba1d7d075001a42935c": "50,000", + "5710f2e2a58dae1900cd6b72": "Williamite war", + "5710f2e2a58dae1900cd6b73": "William of Orange", + "5710f2e2a58dae1900cd6b74": "Dublin, Cork, Portarlington, Lisburn, Waterford and Youghal", + "5710f2e2a58dae1900cd6b75": "flax", + "5710f2e2a58dae1900cd6b76": "linen", + "5ad26f6ed7d075001a429422": "", + "5ad26f6ed7d075001a429423": "", + "5ad26f6ed7d075001a429424": "Killeshandra in County Cavan", + "5ad26f6ed7d075001a429425": "land grants and titles", + "5ad26f6ed7d075001a429426": "", + "5710f4b8b654c5140001fa45": "Prince Louis de Cond\u00e9", + "5710f4b8b654c5140001fa46": "", + "5710f4b8b654c5140001fa47": "glass-making works", + "5710f4b8b654c5140001fa48": "1890s", + "5710f4b8b654c5140001fa49": "1604", + "5ad273b5d7d075001a4294b8": "", + "5ad273b5d7d075001a4294b9": "", + "5ad273b5d7d075001a4294ba": "", + "5ad273b5d7d075001a4294bb": "1604", + "5711119cb654c5140001fae3": "", + "5711119cb654c5140001fae4": "Protestant", + "5711119cb654c5140001fae5": "Dutch Cape Colony", + "5711119cb654c5140001fae6": "", + "5711119cb654c5140001fae7": "", + "5ad240eed7d075001a428940": "", + "5ad240eed7d075001a428941": "", + "5ad240eed7d075001a428942": "", + "5ad240eed7d075001a428943": "", + "5ad240eed7d075001a428944": "", + "571112ada58dae1900cd6bcc": "Hugues Capet", + "571112ada58dae1900cd6bcd": "Hugues hypothesis", + "571112ada58dae1900cd6bce": "Janet Gray", + "571112ada58dae1900cd6bcf": "little Hugos", + "571112ada58dae1900cd6bd0": "double or triple", + "5ad2424cd7d075001a42898a": "", + "5ad2424cd7d075001a42898b": "", + "5ad2424cd7d075001a42898c": "", + "5ad2424cd7d075001a42898d": "", + "57111380a58dae1900cd6bd6": "", + "57111380a58dae1900cd6bd7": "University of Paris", + "57111380a58dae1900cd6bd8": "1530", + "57111380a58dae1900cd6bd9": "William Farel", + "57111380a58dae1900cd6bda": "Jean Cauvin", + "5ad2447dd7d075001a428a68": "", + "5ad2447dd7d075001a428a69": "", + "5ad2447dd7d075001a428a6a": "", + "5ad2447dd7d075001a428a6b": "", + "5ad2447dd7d075001a428a6c": "", + "57111428b654c5140001faff": "24 August \u2013 3 October 1572", + "57111428b654c5140001fb00": "Catholics", + "57111428b654c5140001fb01": "Nearly 3,000", + "57111428b654c5140001fb02": "1573", + "57111429b654c5140001fb03": "25,000", + "5ad24600d7d075001a428ac8": "", + "5ad24600d7d075001a428ac9": "Paris", + "5ad24600d7d075001a428aca": "thousands", + "5ad24600d7d075001a428acb": "", + "5ad24600d7d075001a428acc": "Nearly 3,000", + "571114cfb654c5140001fb09": "Louis XIV", + "571114cfb654c5140001fb0a": "increasingly aggressively to force the Huguenots to convert", + "571114cfb654c5140001fb0b": "sent missionaries", + "571114cfb654c5140001fb0c": "imposed penalties, closed Huguenot schools", + "571114cfb654c5140001fb0d": "dragonnades", + "5ad24d2ad7d075001a428c1e": "", + "5ad24d2ad7d075001a428c1f": "", + "5ad24d2ad7d075001a428c20": "", + "5ad24d2ad7d075001a428c21": "", + "5ad24d2ad7d075001a428c22": "", + "5711163bb654c5140001fb13": "Westchester", + "5711163bb654c5140001fb14": "New Rochelle", + "5711163bb654c5140001fb15": "John Pell", + "5711163bb654c5140001fb16": "La Rochelle", + "5711163bb654c5140001fb17": "Trinity-St. Paul's Episcopal Church", + "5ad2615ed7d075001a429018": "New Rochelle", + "5ad2615ed7d075001a429019": "six thousand one hundred acres", + "5ad2615ed7d075001a42901a": "John Pell", + "5ad2615ed7d075001a42901b": "", + "5ad2615ed7d075001a42901c": "New Rochelle", + "57111713a58dae1900cd6c00": "quickly and often married outside their immediate French communities", + "57111713a58dae1900cd6c01": "married outside their immediate French communities", + "57111713a58dae1900cd6c02": "du Pont", + "57111713a58dae1900cd6c03": "well into the nineteenth century", + "57111713a58dae1900cd6c04": "Eleutherian gunpowder mills", + "5ad264d7d7d075001a429174": "", + "5ad264d7d7d075001a429175": "", + "5ad264d7d7d075001a429176": "", + "5ad264d7d7d075001a429177": "The Huguenots adapted quickly and often married outside their immediate French communities", + "571117d4a58dae1900cd6c0a": "Pierre Bayle", + "571117d4a58dae1900cd6c0b": "Rotterdam", + "571117d4a58dae1900cd6c0c": "Historical and Critical Dictionary", + "571117d4a58dae1900cd6c0d": "US Library of Congress", + "571117d4a58dae1900cd6c0e": "Nicolas", + "5ad26acad7d075001a42932a": "", + "5ad26acad7d075001a42932b": "", + "5ad26acad7d075001a42932c": "Sinterklaas", + "5ad26acad7d075001a42932d": "multi", + "57111992b654c5140001fb43": "The French Protestant Church of London", + "57111992b654c5140001fb44": "1550", + "57111992b654c5140001fb45": "Soho Square", + "57111992b654c5140001fb46": "Shoreditch", + "57111992b654c5140001fb47": "1724", + "5ad26dbcd7d075001a4293d4": "1550", + "5ad26dbcd7d075001a4293d5": "1724", + "5ad26dbcd7d075001a4293d6": "", + "5ad26dbcd7d075001a4293d7": "about a third", + "5ad26dbcd7d075001a4293d8": "", + "57111ab8a58dae1900cd6c3c": "", + "57111ab8a58dae1900cd6c3d": "", + "57111ab8a58dae1900cd6c3e": "Edict of Potsdam", + "57111ab8a58dae1900cd6c3f": "Elector of Brandenburg and Duke of Prussia", + "57111ab8a58dae1900cd6c40": "", + "5ad271c2d7d075001a429472": "", + "5ad271c2d7d075001a429473": "", + "5ad271c2d7d075001a429474": "4,000", + "5ad271c2d7d075001a429475": "1,500", + "5ad271c2d7d075001a429476": "", + "57111b95a58dae1900cd6c50": "Frederick William", + "57111b95a58dae1900cd6c51": "Theodor Fontane", + "57111b95a58dae1900cd6c52": "Adolf Galland", + "57111b95a58dae1900cd6c53": "Lothar de Maizi\u00e8re", + "57111b95a58dae1900cd6c54": "German Federal Minister of the Interior", + "5ad275ccd7d075001a42950e": "", + "5ad275ccd7d075001a42950f": "", + "5ad275ccd7d075001a429510": "", + "5ad275ccd7d075001a429511": "Huguenot", + "5ad275ccd7d075001a429512": "", + "57112686b654c5140001fbd3": "solar power", + "57112686b654c5140001fbd4": "Rankine cycle", + "57112686b654c5140001fbd5": "steam", + "57112686b654c5140001fbd6": "high pressure", + "57112686b654c5140001fbd7": "external combustion engines", + "5ad3bd8f604f3c001a3fef2d": "solar power", + "5ad3bd8f604f3c001a3fef2e": "Rankine cycle", + "5ad3bd8f604f3c001a3fef2f": "", + "5ad3bd8f604f3c001a3fef30": "", + "5ad3bd8f604f3c001a3fef31": "", + "571126dfa58dae1900cd6cb2": "atmospheric engine", + "571126dfa58dae1900cd6cb3": "Thomas Newcomen", + "571126dfa58dae1900cd6cb4": "1712", + "571126dfa58dae1900cd6cb5": "", + "571126dfa58dae1900cd6cb6": "Papin", + "5ad3c637604f3c001a3ff017": "", + "5ad3c637604f3c001a3ff018": "", + "5ad3c637604f3c001a3ff019": "1712", + "5ad3c637604f3c001a3ff01a": "", + "5ad3c637604f3c001a3ff01b": "", + "571127a5a58dae1900cd6cc4": "United Kingdom", + "571127a5a58dae1900cd6cc5": "21 February 1804", + "571127a5a58dae1900cd6cc6": "Abercynon in south Wales", + "571127a5a58dae1900cd6cc7": "", + "571127a5a58dae1900cd6cc8": "south", + "5ad3cd43604f3c001a3ff183": "United Kingdom", + "5ad3cd43604f3c001a3ff184": "21 February 1804", + "5ad3cd43604f3c001a3ff185": "Abercynon in south Wales", + "5ad3cd43604f3c001a3ff186": "", + "5ad3cd43604f3c001a3ff187": "south Wales", + "571135b8a58dae1900cd6d0e": "water pump", + "571135b8a58dae1900cd6d0f": "multi-stage centrifugal pumps", + "571135b8a58dae1900cd6d10": "1850s", + "571135b8a58dae1900cd6d11": "steam locomotives", + "571135b8a58dae1900cd6d12": "lower-pressure boiler feed water", + "5ad3e83e604f3c001a3ff63b": "injector", + "5ad3e83e604f3c001a3ff63c": "", + "5ad3e83e604f3c001a3ff63d": "1850s", + "5ad3e83e604f3c001a3ff63e": "", + "5ad3e83e604f3c001a3ff63f": "", + "57113639a58dae1900cd6d18": "three or four", + "57113639a58dae1900cd6d19": "triple and quadruple expansion engines", + "57113639a58dae1900cd6d1a": "19th", + "57113639a58dae1900cd6d1b": "marine triple expansion engines", + "57113639a58dae1900cd6d1c": "Olympic class", + "5ad41b12604f3c001a4004fb": "three or four", + "5ad41b12604f3c001a4004fc": "", + "5ad41b12604f3c001a4004fd": "", + "5ad41b12604f3c001a4004fe": "", + "5ad41b12604f3c001a4004ff": "", + "571136b8a58dae1900cd6d22": "Corliss", + "571136b8a58dae1900cd6d23": "Joy", + "571136b8a58dae1900cd6d24": "lengthening rubbing surfaces", + "5ad3f35c604f3c001a3ff8f5": "Corliss", + "5ad3f35c604f3c001a3ff8f6": "Joy", + "5ad3f35c604f3c001a3ff8f7": "lengthening rubbing surfaces", + "5ad3f35c604f3c001a3ff8f8": "1840s and 50s", + "57113ba6b654c5140001fc1f": "Lead fusible plugs", + "57113ba6b654c5140001fc20": "the lead melts and the steam escapes", + "57113ba6b654c5140001fc21": "the steam escapes", + "57113ba6b654c5140001fc22": "manually suppress the fire", + "57113ba6b654c5140001fc23": "dampening the fire", + "5ad40ec6604f3c001a40012f": "Lead fusible plugs", + "5ad40ec6604f3c001a400130": "the lead melts and the steam escapes", + "5ad40ec6604f3c001a400131": "the steam escapes", + "5ad40ec6604f3c001a400132": "manually suppress the fire", + "5ad40ec6604f3c001a400133": "little effect on dampening the fire", + "57113be3a58dae1900cd6d28": "James Watt", + "57113be3a58dae1900cd6d29": "rotary", + "57113be3a58dae1900cd6d2a": "ten", + "57113be3a58dae1900cd6d2b": "", + "57113be3a58dae1900cd6d2c": "Industrial Revolution", + "5ad3bf63604f3c001a3fef5b": "", + "5ad3bf63604f3c001a3fef5c": "", + "5ad3bf63604f3c001a3fef5d": "", + "5ad3bf63604f3c001a3fef5e": "", + "5ad3bf63604f3c001a3fef5f": "", + "57113c6da58dae1900cd6d32": "first century AD", + "57113c6da58dae1900cd6d33": "Greek mathematician Hero of Alexandria", + "57113c6da58dae1900cd6d34": "Greek", + "57113c6da58dae1900cd6d35": "Giovanni Branca", + "57113c6da58dae1900cd6d36": "1606", + "5ad3c46a604f3c001a3fefb1": "first century AD", + "5ad3c46a604f3c001a3fefb2": "Denis Papin", + "5ad3c46a604f3c001a3fefb3": "", + "5ad3c46a604f3c001a3fefb4": "Denis Papin", + "5ad3c46a604f3c001a3fefb5": "1606", + "57113f83b654c5140001fc29": "compound engines", + "57113f83b654c5140001fc2a": "expansions", + "57113f83b654c5140001fc2b": "shipping", + "57113f83b654c5140001fc2c": "coal", + "57113f83b654c5140001fc2d": "internal combustion engines", + "5ad3cc47604f3c001a3ff143": "", + "5ad3cc47604f3c001a3ff144": "expansions", + "5ad3cc47604f3c001a3ff145": "shipping", + "5ad3cc47604f3c001a3ff146": "coal", + "5ad3cc47604f3c001a3ff147": "internal combustion engines", + "571142b3a58dae1900cd6d5a": "steam turbines", + "571142b3a58dae1900cd6d5b": "late", + "571142b3a58dae1900cd6d5c": "several hundred horsepower", + "571142b3a58dae1900cd6d5d": "90%", + "571142b3a58dae1900cd6d5e": "electric", + "5ad3d3af604f3c001a3ff293": "", + "5ad3d3af604f3c001a3ff294": "", + "5ad3d3af604f3c001a3ff295": "several hundred horsepower", + "5ad3d3af604f3c001a3ff296": "90%", + "5ad3d3af604f3c001a3ff297": "", + "571144d1a58dae1900cd6d6e": "burning combustible materials", + "571144d1a58dae1900cd6d6f": "combustion chamber", + "571144d1a58dae1900cd6d70": "solar energy", + "571144d1a58dae1900cd6d71": "electric", + "5ad3d689604f3c001a3ff30d": "burning combustible materials", + "5ad3d689604f3c001a3ff30e": "combustion chamber", + "5ad3d689604f3c001a3ff30f": "electric", + "5ad3d689604f3c001a3ff310": "solar energy", + "5ad3d689604f3c001a3ff311": "", + "57114667a58dae1900cd6d80": "steam engine indicator", + "57114667a58dae1900cd6d81": "1851", + "57114667a58dae1900cd6d82": "Charles Porter", + "57114667a58dae1900cd6d83": "Charles Richard", + "57114667a58dae1900cd6d84": "London Exhibition", + "5ad3e8f6604f3c001a3ff66b": "", + "5ad3e8f6604f3c001a3ff66c": "1851", + "5ad3e8f6604f3c001a3ff66d": "Charles Porter", + "5ad3e8f6604f3c001a3ff66e": "Charles Richard", + "5ad3e8f6604f3c001a3ff66f": "London Exhibition", + "5711475ca58dae1900cd6d8a": "90\u00b0", + "5711475ca58dae1900cd6d8b": "180\u00b0", + "5711475ca58dae1900cd6d8c": "90\u00b0", + "5ad3ed37604f3c001a3ff7a1": "90\u00b0", + "5ad3ed37604f3c001a3ff7a2": "180\u00b0", + "5ad3ed37604f3c001a3ff7a3": "90\u00b0", + "5ad3ed37604f3c001a3ff7a4": "the individual pistons within the group are usually balanced at 180\u00b0, the groups being set at 90\u00b0 to each other", + "5ad3ed37604f3c001a3ff7a5": "the pistons worked in the same phase driving a common crosshead and crank, again set at 90\u00b0 as for a two-cylinder engine", + "5711488ab654c5140001fc3d": "counterflow", + "5711488ab654c5140001fc3e": "two", + "5711488ab654c5140001fc3f": "one", + "5711488ab654c5140001fc40": "four", + "5711488ab654c5140001fc41": "expansion", + "5ad3f03c604f3c001a3ff829": "counterflow", + "5ad3f03c604f3c001a3ff82a": "two", + "5ad3f03c604f3c001a3ff82b": "one", + "5ad3f03c604f3c001a3ff82c": "four", + "5ad3f03c604f3c001a3ff82d": "expansion", + "57114aceb654c5140001fc47": "The Quasiturbine", + "57114aceb654c5140001fc48": "counterflow cycle", + "57114aceb654c5140001fc49": "an additional port uncovered by the piston", + "5ad3f4ed604f3c001a3ff963": "The Quasiturbine", + "5ad3f4ed604f3c001a3ff964": "", + "5ad3f4ed604f3c001a3ff965": "", + "5ad3f4ed604f3c001a3ff966": "", + "5ad3f4ed604f3c001a3ff967": "", + "57114b1a2419e31400955575": "oscillating cylinder steam engine", + "57114b1a2419e31400955576": "trunnion", + "57114b1a2419e31400955577": "models", + "57114b1a2419e31400955578": "ships", + "5ad3fc1f604f3c001a3ffb7b": "oscillating cylinder steam engine", + "5ad3fc1f604f3c001a3ffb7c": "", + "5ad3fc1f604f3c001a3ffb7d": "", + "5ad3fc1f604f3c001a3ffb7e": "ships", + "5ad3fc1f604f3c001a3ffb7f": "", + "57114dfb50c2381900b54a53": "the working fluid is recycled continuously", + "57114dfb50c2381900b54a54": "open loop\" system", + "57114dfb50c2381900b54a55": "Mercury", + "57114dfb50c2381900b54a56": "Mercury", + "5ad415fd604f3c001a400327": "", + "5ad415fd604f3c001a400328": "", + "5ad415fd604f3c001a400329": "Mercury", + "5ad415fd604f3c001a40032a": "Mercury", + "5ad415fd604f3c001a40032b": "a closed loop system", + "57114e8d50c2381900b54a5b": "the working fluid", + "57114e8d50c2381900b54a5c": "565 \u00b0C", + "57114e8d50c2381900b54a5d": "stainless steel", + "57114e8d50c2381900b54a5e": "30 \u00b0C", + "57114e8d50c2381900b54a5f": "63%", + "5ad418fb604f3c001a400431": "the working fluid", + "5ad418fb604f3c001a400432": "", + "5ad418fb604f3c001a400433": "", + "5ad418fb604f3c001a400434": "30 \u00b0C", + "5ad418fb604f3c001a400435": "", + "57114f0050c2381900b54a65": "Steam engines", + "57114f0050c2381900b54a66": "steamboats", + "57114f0050c2381900b54a67": "Stanley Steamer", + "57114f0050c2381900b54a68": "factories", + "57114f0050c2381900b54a69": "an increase in the land available for cultivation", + "5ad3c1ad604f3c001a3fef8d": "Steam engines", + "5ad3c1ad604f3c001a3fef8e": "steamboats", + "5ad3c1ad604f3c001a3fef8f": "", + "5ad3c1ad604f3c001a3fef90": "factories", + "5ad3c1ad604f3c001a3fef91": "", + "571153422419e3140095557d": "Catch Me Who Can", + "571153422419e3140095557e": "Matthew Murray", + "571153422419e3140095557f": "twin-cylinder", + "571153422419e31400955580": "rack and pinion Middleton Railway", + "571153422419e31400955581": "Stockton and Darlington Railway", + "5ad3d2aa604f3c001a3ff261": "", + "5ad3d2aa604f3c001a3ff262": "Matthew Murray", + "5ad3d2aa604f3c001a3ff263": "", + "5ad3d2aa604f3c001a3ff264": "Stockton and Darlington Railway", + "5ad3d2aa604f3c001a3ff265": "", + "5711541350c2381900b54a6f": "Arthur Woolf", + "5711541350c2381900b54a70": "British", + "5711541350c2381900b54a71": "torque variability", + "5711541350c2381900b54a72": "cylinder volume", + "5ad3eb61604f3c001a3ff71b": "", + "5ad3eb61604f3c001a3ff71c": "", + "5ad3eb61604f3c001a3ff71d": "torque variability", + "5ad3eb61604f3c001a3ff71e": "cylinder volume", + "5ad3eb61604f3c001a3ff71f": "Arthur Woolf", + "571154c72419e31400955587": "90%", + "571154c72419e31400955588": "", + "571154c72419e31400955589": "gas turbines", + "571154c72419e3140095558a": "", + "571154c72419e3140095558b": "reduction", + "5ad3f846604f3c001a3ffa5d": "", + "5ad3f846604f3c001a3ffa5e": "", + "5ad3f846604f3c001a3ffa5f": "gas turbines", + "5ad3f846604f3c001a3ffa60": "", + "5ad3f846604f3c001a3ffa61": "", + "571155ae2419e31400955591": "The Rankine cycle", + "571155ae2419e31400955592": "removed in a condenser", + "571155ae2419e31400955593": "1990s", + "571155ae2419e31400955594": "biomass", + "571155ae2419e31400955595": "Scottish", + "5ad41260604f3c001a40023f": "", + "5ad41260604f3c001a400240": "removed in a condenser", + "5ad41260604f3c001a400241": "1990s", + "5ad41260604f3c001a400242": "biomass", + "5ad41260604f3c001a400243": "", + "571156152419e3140095559b": "duty", + "571156152419e3140095559c": "Watt", + "571156152419e3140095559d": "94", + "571156152419e3140095559e": "the number of foot-pounds of work delivered by burning one bushel (94 pounds) of coal", + "571156152419e3140095559f": "17", + "5ad41813604f3c001a4003dd": "more efficient his engines were over the earlier Newcomen designs", + "5ad41813604f3c001a4003de": "Watt", + "5ad41813604f3c001a4003df": "", + "5ad41813604f3c001a4003e0": "the number of foot-pounds of work delivered by burning one bushel (94 pounds) of coal", + "5ad41813604f3c001a4003e1": "", + "57115ac550c2381900b54a77": "steam turbines", + "57115ac550c2381900b54a78": "turbine type", + "57115ac550c2381900b54a79": "turbine type steam engines", + "57115ac550c2381900b54a7a": "internal combustion engines", + "5ad3c061604f3c001a3fef6f": "steam turbines", + "5ad3c061604f3c001a3fef70": "turbine type steam engines", + "5ad3c061604f3c001a3fef71": "turbine type steam engines", + "5ad3c061604f3c001a3fef72": "internal combustion engines", + "5ad3c061604f3c001a3fef73": "", + "57115b2850c2381900b54a7f": "Thomas Savery", + "57115b2850c2381900b54a80": "water pump", + "57115b2850c2381900b54a81": "1698", + "57115b2850c2381900b54a82": "Bento de Moura Portugal", + "57115b2850c2381900b54a83": "John Smeaton", + "5ad3c57a604f3c001a3feff1": "Thomas Savery", + "5ad3c57a604f3c001a3feff2": "", + "5ad3c57a604f3c001a3feff3": "", + "5ad3c57a604f3c001a3feff4": "", + "5ad3c57a604f3c001a3feff5": "John Smeaton", + "57115b8b50c2381900b54a89": "Richard Trevithick", + "57115b8b50c2381900b54a8a": "Richard Trevithick and, separately, Oliver Evans", + "57115b8b50c2381900b54a8b": "1802", + "57115b8b50c2381900b54a8c": "transport", + "57115b8b50c2381900b54a8d": "power source", + "5ad3cab2604f3c001a3ff0e3": "", + "5ad3cab2604f3c001a3ff0e4": "Richard Trevithick and, separately, Oliver Evans", + "5ad3cab2604f3c001a3ff0e5": "", + "5ad3cab2604f3c001a3ff0e6": "", + "5ad3cab2604f3c001a3ff0e7": "", + "57115bf350c2381900b54a93": "Energiprojekt AB", + "57115bf350c2381900b54a94": "Sweden", + "57115bf350c2381900b54a95": "5", + "57115bf350c2381900b54a96": "8.8", + "57115bf350c2381900b54a97": "27-30%", + "5ad3d4db604f3c001a3ff2b1": "Energiprojekt AB", + "5ad3d4db604f3c001a3ff2b2": "", + "5ad3d4db604f3c001a3ff2b3": "", + "5ad3d4db604f3c001a3ff2b4": "8.8", + "5ad3d4db604f3c001a3ff2b5": "", + "57115c7450c2381900b54a9d": "surface condensers", + "57115c7450c2381900b54a9e": "automobile radiator", + "57115c7450c2381900b54a9f": "locations where water is costly", + "57115c7450c2381900b54aa0": "dry type", + "57115c7450c2381900b54aa1": "3600", + "5ad3d7e0604f3c001a3ff35d": "surface condensers", + "5ad3d7e0604f3c001a3ff35e": "", + "5ad3d7e0604f3c001a3ff35f": "", + "5ad3d7e0604f3c001a3ff360": "dry type", + "5ad3d7e0604f3c001a3ff361": "3600", + "57115dbe2419e314009555a5": "The centrifugal governor", + "57115dbe2419e314009555a6": "Boulton", + "57115dbe2419e314009555a7": "flour mill", + "57115dbe2419e314009555a8": "cotton spinning", + "57115dbe2419e314009555a9": "", + "5ad3ea77604f3c001a3ff6df": "", + "5ad3ea77604f3c001a3ff6e0": "", + "5ad3ea77604f3c001a3ff6e1": "flour mill Boulton & Watt were building", + "5ad3ea77604f3c001a3ff6e2": "", + "5ad3ea77604f3c001a3ff6e3": "", + "57115e532419e314009555af": "1880", + "57115e532419e314009555b0": "railway locomotives", + "57115e532419e314009555b1": "complicated", + "57115e532419e314009555b2": "1930", + "57115e532419e314009555b3": "road engines", + "5ad3ee11604f3c001a3ff7d7": "1880", + "5ad3ee11604f3c001a3ff7d8": "railway locomotives", + "5ad3ee11604f3c001a3ff7d9": "complicated", + "5ad3ee11604f3c001a3ff7da": "1930", + "5ad3ee11604f3c001a3ff7db": "road engines", + "57115f0a50c2381900b54aa7": "shortening the cutoff", + "57115f0a50c2381900b54aa8": "kick back", + "57115f0a50c2381900b54aa9": "evacuate the cylinder", + "57115f0a50c2381900b54aaa": "fixed", + "5ad3f13e604f3c001a3ff865": "", + "5ad3f13e604f3c001a3ff866": "kick back", + "5ad3f13e604f3c001a3ff867": "evacuate the cylinder", + "5ad3f13e604f3c001a3ff868": "fixed", + "5ad3f13e604f3c001a3ff869": "", + "57115f652419e314009555b9": "Jer\u00f3nimo de Ayanz y Beaumont", + "57115f652419e314009555ba": "Spanish", + "57115f652419e314009555bb": "1606", + "57115f652419e314009555bc": "1698", + "57115f652419e314009555bd": "1712", + "5ad3be46604f3c001a3fef37": "", + "5ad3be46604f3c001a3fef38": "", + "5ad3be46604f3c001a3fef39": "", + "5ad3be46604f3c001a3fef3a": "", + "5ad3be46604f3c001a3fef3b": "1712", + "57115ff82419e314009555c3": "rotating discs", + "57115ff82419e314009555c4": "a drive shaft", + "57115ff82419e314009555c5": "static discs", + "57115ff82419e314009555c6": "turbine casing", + "57115ff82419e314009555c7": "3600 revolutions per minute", + "5ad3f689604f3c001a3ff9e3": "", + "5ad3f689604f3c001a3ff9e4": "a drive shaft", + "5ad3f689604f3c001a3ff9e5": "", + "5ad3f689604f3c001a3ff9e6": "", + "5ad3f689604f3c001a3ff9e7": "3600 revolutions per minute", + "5711607f2419e314009555cd": "lower", + "5711607f2419e314009555ce": "electric motors", + "5711607f2419e314009555cf": "steam turbine plant", + "5711607f2419e314009555d0": "Advanced Steam movement", + "5711607f2419e314009555d1": "pollution", + "5ad3c3bc604f3c001a3fef9f": "lower", + "5ad3c3bc604f3c001a3fefa0": "electric motors", + "5ad3c3bc604f3c001a3fefa1": "steam turbine plant", + "5ad3c3bc604f3c001a3fefa2": "", + "5ad3c3bc604f3c001a3fefa3": "pollution", + "571161092419e314009555d7": "Wankel engine", + "571161092419e314009555d8": "cylinders and valve gear", + "571161092419e314009555d9": "thermal expansion", + "5ad40864604f3c001a3ffeeb": "", + "5ad40864604f3c001a3ffeec": "cylinders and valve gear", + "5ad40864604f3c001a3ffeed": "thermal expansion", + "5ad40864604f3c001a3ffeee": "", + "5ad40864604f3c001a3ffeef": "", + "5711619950c2381900b54aaf": "1775", + "5711619950c2381900b54ab0": "condenser", + "5711619950c2381900b54ab1": "half", + "5711619950c2381900b54ab2": "Newcomen", + "5711619950c2381900b54ab3": "partial vacuum generated by condensing steam", + "5ad3c75a604f3c001a3ff045": "1775", + "5ad3c75a604f3c001a3ff046": "condenser", + "5ad3c75a604f3c001a3ff047": "half as much coal", + "5ad3c75a604f3c001a3ff048": "Newcomen", + "5ad3c75a604f3c001a3ff049": "partial vacuum generated by condensing steam", + "5711623e50c2381900b54ab9": "two", + "5711623e50c2381900b54aba": "a plug valve", + "5711623e50c2381900b54abb": "adjustable spring-loaded valve", + "5711623e50c2381900b54abc": "a seal", + "5711623e50c2381900b54abd": "more power from the engine", + "5ad40b9a604f3c001a400019": "", + "5ad40b9a604f3c001a40001a": "", + "5ad40b9a604f3c001a40001b": "", + "5ad40b9a604f3c001a40001c": "seal", + "5ad40b9a604f3c001a40001d": "more power", + "5711628a2419e314009555dd": "Corliss steam engine", + "5711628a2419e314009555de": "1849", + "5711628a2419e314009555df": "four", + "5711628a2419e314009555e0": "Rumford medal", + "5711628a2419e314009555e1": "30%", + "5ad3cb62604f3c001a3ff111": "", + "5ad3cb62604f3c001a3ff112": "", + "5ad3cb62604f3c001a3ff113": "", + "5ad3cb62604f3c001a3ff114": "Rumford medal", + "5ad3cb62604f3c001a3ff115": "30%", + "571163172419e314009555e7": "thermodynamic", + "571163172419e314009555e8": "Watt", + "571163172419e314009555e9": "condenser", + "571163172419e314009555ea": "Joseph Black", + "571163172419e314009555eb": "latent heat", + "5ad41733604f3c001a40037f": "", + "5ad41733604f3c001a400380": "", + "5ad41733604f3c001a400381": "", + "5ad41733604f3c001a400382": "Joseph Black", + "5ad41733604f3c001a400383": "latent heat", + "5711648850c2381900b54ac3": "during the compression stage relatively little work is required to drive the pump", + "5711648850c2381900b54ac4": "liquid phase", + "5711648850c2381900b54ac5": "1% to 3%", + "5711648850c2381900b54ac6": "1500 \u00b0C", + "5ad419f8604f3c001a400499": "By condensing the fluid, the work required by the pump consumes only 1% to 3% of the turbine power", + "5ad419f8604f3c001a40049a": "liquid phase", + "5ad419f8604f3c001a40049b": "", + "5ad419f8604f3c001a40049c": "", + "5ad419f8604f3c001a40049d": "", + "5711651050c2381900b54acb": "an injector", + "5711651050c2381900b54acc": "recover the latent heat of vaporisation", + "5711651050c2381900b54acd": "superheaters", + "5711651050c2381900b54ace": "bunker", + "5711651050c2381900b54acf": "a chain or screw stoking mechanism", + "5ad3d560604f3c001a3ff2c5": "", + "5ad3d560604f3c001a3ff2c6": "", + "5ad3d560604f3c001a3ff2c7": "superheaters", + "5ad3d560604f3c001a3ff2c8": "", + "5ad3d560604f3c001a3ff2c9": "a chain or screw stoking mechanism", + "5711658e50c2381900b54ad5": "feed water", + "5711658e50c2381900b54ad6": "British", + "5711658e50c2381900b54ad7": "dreadnought battleships", + "5711658e50c2381900b54ad8": "dreadnought battleships", + "5711658e50c2381900b54ad9": "1905", + "5ad3ef13604f3c001a3ff7f9": "feed water", + "5ad3ef13604f3c001a3ff7fa": "", + "5ad3ef13604f3c001a3ff7fb": "dreadnought battleships", + "5ad3ef13604f3c001a3ff7fc": "dreadnought battleships", + "5ad3ef13604f3c001a3ff7fd": "", + "571166352419e314009555f1": "water", + "571166352419e314009555f2": "electricity by heating water to provide steam that drives a turbine connected to an electrical generator", + "571166352419e314009555f3": "an electrical generator", + "571166352419e314009555f4": "turbo-electric transmission", + "571166352419e314009555f5": "Sweden and for express passenger work in Britain", + "5ad3fabc604f3c001a3ffb1b": "water", + "5ad3fabc604f3c001a3ffb1c": "", + "5ad3fabc604f3c001a3ffb1d": "an electrical generator", + "5ad3fabc604f3c001a3ffb1e": "turbo-electric transmission", + "5ad3fabc604f3c001a3ffb1f": "Sweden and for express passenger work in Britain", + "5711669550c2381900b54adf": "a practical Carnot cycle", + "5711669550c2381900b54ae0": "condenser", + "5711669550c2381900b54ae1": "constant pressure", + "5711669550c2381900b54ae2": "isothermal", + "5711669550c2381900b54ae3": "liquid not as a gas", + "5ad414dd604f3c001a4002c7": "", + "5ad414dd604f3c001a4002c8": "condenser", + "5ad414dd604f3c001a4002c9": "", + "5ad414dd604f3c001a4002ca": "", + "5ad414dd604f3c001a4002cb": "", + "571a484210f8ca1400304fbd": "8", + "571a484210f8ca1400304fbe": "", + "571a484210f8ca1400304fbf": "Diatomic oxygen gas", + "571a484210f8ca1400304fc0": "two", + "571a484210f8ca1400304fc1": "half", + "571c3a685efbb31900334db2": "8", + "571c3a685efbb31900334db3": "chalcogen group", + "571c3a685efbb31900334db4": "oxides", + "571c3a685efbb31900334db5": "third", + "571c3a685efbb31900334db6": "dioxygen", + "5ad21646d7d075001a4283c4": "Oxygen", + "5ad21646d7d075001a4283c5": "", + "5ad21646d7d075001a4283c6": "", + "5ad21646d7d075001a4283c7": "", + "571a49de4faf5e1900b8a94a": "photosynthesis", + "571a49de4faf5e1900b8a94b": "sunlight", + "571a49de4faf5e1900b8a94c": "high-altitude ozone layer", + "571c3c47dd7acb1400e4c09c": "oxygen", + "571c3c47dd7acb1400e4c09d": "water", + "571c3c47dd7acb1400e4c09e": "photosynthesis", + "571c3c47dd7acb1400e4c09f": "water", + "571c3c47dd7acb1400e4c0a0": "", + "5ad21e1ad7d075001a42846e": "proteins, nucleic acids, carbohydrates, and fats", + "5ad21e1ad7d075001a42846f": "Oxygen", + "5ad21e1ad7d075001a428470": "", + "5ad21e1ad7d075001a428471": "", + "571a4b0f10f8ca1400304fd5": "Robert Boyle", + "571a4b0f10f8ca1400304fd6": "", + "571a4b0f10f8ca1400304fd7": "nitroaereus", + "571a4b0f10f8ca1400304fd8": "1679", + "571c3e8cdd7acb1400e4c0a6": "Robert Boyle", + "571c3e8cdd7acb1400e4c0a7": "spiritus nitroaereus", + "571c3e8cdd7acb1400e4c0a8": "17th", + "571c3e8cdd7acb1400e4c0a9": "respiration", + "571c3e8cdd7acb1400e4c0aa": "John Mayow", + "5ad22a95d7d075001a4285da": "", + "5ad22a95d7d075001a4285db": "", + "5ad22a96d7d075001a4285dc": "", + "5ad22a96d7d075001a4285dd": "English chemist John Mayow", + "5ad22a96d7d075001a4285de": "", + "571a4d1a4faf5e1900b8a958": "Joseph Priestley", + "571a4d1a4faf5e1900b8a959": "clergyman", + "571a4d1a4faf5e1900b8a95a": "mercuric oxide", + "571a4d1a4faf5e1900b8a95b": "HgO", + "571c4132dd7acb1400e4c0b0": "mercuric oxide", + "571c4132dd7acb1400e4c0b1": "dephlogisticated air", + "571c4132dd7acb1400e4c0b2": "1775", + "571c4132dd7acb1400e4c0b3": "", + "571c4132dd7acb1400e4c0b4": "more active and lived longer", + "5ad22cd0d7d075001a428618": "", + "5ad22cd0d7d075001a428619": "", + "5ad22cd0d7d075001a42861a": "An Account of Further Discoveries in Air", + "5ad22cd0d7d075001a42861b": "dephlogisticated air", + "571a4ead10f8ca1400304fdd": "Leonardo da Vinci", + "571a4ead10f8ca1400304fde": "Philo", + "571a4ead10f8ca1400304fdf": "2nd century BCE", + "571a4ead10f8ca1400304fe0": "Philo incorrectly surmised that parts of the air in the vessel were converted into the classical element fire", + "571c7abfdd7acb1400e4c0ba": "Philo of Byzantium", + "571c7abfdd7acb1400e4c0bb": "classical element fire", + "571c7abfdd7acb1400e4c0bc": "Pneumatica", + "571c7abfdd7acb1400e4c0bd": "Leonardo da Vinci", + "571c7abfdd7acb1400e4c0be": "air", + "5ad21f6fd7d075001a4284a4": "experiments on the relationship between combustion and air", + "5ad21f6fd7d075001a4284a5": "2nd century BCE", + "5ad21f6fd7d075001a4284a6": "Leonardo da Vinci", + "5ad21f6fd7d075001a4284a7": "", + "571a50df4faf5e1900b8a960": "heat or a spark", + "571a50df4faf5e1900b8a961": "the source of most of the chemical energy", + "571a50df4faf5e1900b8a962": "oxygen", + "571a50df4faf5e1900b8a963": "Oxygen", + "571cebc05efbb31900334e48": "rapid combustion", + "571cebc05efbb31900334e49": "ignition event", + "571cebc05efbb31900334e4a": "oxidant", + "571cebc05efbb31900334e4b": "chemical energy", + "571cebc05efbb31900334e4c": "peroxides, chlorates, nitrates, perchlorates, and dichromates", + "5ad2678ad7d075001a42922c": "rapid combustion", + "5ad2678ad7d075001a42922d": "the source of most of the chemical energy released in combustion", + "5ad2678ad7d075001a42922e": "", + "5ad2678ad7d075001a42922f": "oxidant", + "5ad2678ad7d075001a429230": "", + "571a52cb4faf5e1900b8a969": "Concentrated O\n2", + "571a52cb4faf5e1900b8a96a": "1\u20443", + "571a52cb4faf5e1900b8a96b": "special training", + "571ce9bddd7acb1400e4c1a0": "", + "571ce9bddd7acb1400e4c1a1": "ignition sources are minimized", + "571ce9bddd7acb1400e4c1a2": "act as a fuel", + "571ce9bddd7acb1400e4c1a4": "the Apollo 1 crew", + "5ad2685dd7d075001a429276": "rapidly and energetically", + "5ad2685dd7d075001a429278": "a launch pad test", + "5ad2685dd7d075001a429279": "proceed rapidly and energetically", + "571a53d410f8ca1400304fe5": "The Earth's mantle", + "571a53d410f8ca1400304fe6": "silicon", + "571a53d410f8ca1400304fe7": "carbon dioxide", + "571ce7f25efbb31900334e3e": "", + "571ce7f25efbb31900334e3f": "The Earth's crustal rock", + "571ce7f25efbb31900334e40": "The Earth's mantle", + "571ce7f25efbb31900334e41": "The Earth's mantle", + "571ce7f25efbb31900334e42": "oxygen", + "5ad26235d7d075001a429080": "carbon dioxide", + "5ad26235d7d075001a429081": "silicon", + "5ad26235d7d075001a429082": "", + "5ad26235d7d075001a429083": "iron(III) oxide", + "571c7d55dd7acb1400e4c0c4": "monatomic", + "571c7d55dd7acb1400e4c0c5": "simplest", + "571c7d55dd7acb1400e4c0c6": "HO", + "571c7d55dd7acb1400e4c0c7": "hydrogen", + "571c7d55dd7acb1400e4c0c8": "", + "5ad23e1bd7d075001a4288b4": "", + "5ad23e1bd7d075001a4288b5": "", + "5ad23e1bd7d075001a4288b6": "water is formed of two volumes of hydrogen and one volume of oxygen", + "5ad23e1bd7d075001a4288b7": "1805", + "5ad23e1bd7d075001a4288b8": "", + "571c8198dd7acb1400e4c0ce": "phlogiston", + "571c8198dd7acb1400e4c0cf": "non-combustible substances that corrode, such as iron", + "571c8198dd7acb1400e4c0d0": "buoyancy", + "571c8198dd7acb1400e4c0d1": "metals", + "571c8198dd7acb1400e4c0d2": "lighter", + "5ad22b87d7d075001a428600": "", + "5ad22b87d7d075001a428601": "", + "5ad22b87d7d075001a428602": "", + "5ad22b87d7d075001a428603": "", + "571c83f3dd7acb1400e4c0d8": "a covalent double bond", + "571c83f3dd7acb1400e4c0d9": "two", + "571c83f3dd7acb1400e4c0da": "Aufbau", + "571c83f3dd7acb1400e4c0db": "chemically bonded to each other", + "571c83f3dd7acb1400e4c0dc": "the filling of molecular orbitals formed from the atomic orbitals of the individual oxygen atoms", + "5ad24180d7d075001a428970": "", + "5ad24180d7d075001a428971": "", + "5ad24180d7d075001a428972": "", + "5ad24180d7d075001a428973": "", + "571c8539dd7acb1400e4c0e2": "1773", + "571c8539dd7acb1400e4c0e3": "1774", + "571c8539dd7acb1400e4c0e4": "his work was published first", + "571c8539dd7acb1400e4c0e5": "Antoine Lavoisier", + "571c8539dd7acb1400e4c0e6": "phlogiston theory of combustion and corrosion", + "5ad21ebdd7d075001a428488": "", + "5ad21ebdd7d075001a428489": "", + "5ad21ebdd7d075001a42848a": "", + "5ad21ebdd7d075001a42848b": "", + "571c879bdd7acb1400e4c0ec": "spin triplet state", + "571c879bdd7acb1400e4c0ed": "triplet oxygen", + "571c879bdd7acb1400e4c0ee": "unpaired electrons", + "571c879bdd7acb1400e4c0ef": "spontaneous", + "571c879bdd7acb1400e4c0f0": "", + "5ad24369d7d075001a4289ea": "", + "5ad24369d7d075001a4289eb": "", + "5ad24369d7d075001a4289ec": "", + "5ad24369d7d075001a4289ed": "", + "571c8eb9dd7acb1400e4c0f6": "", + "571c8eb9dd7acb1400e4c0f7": "increased in weight", + "571c8eb9dd7acb1400e4c0f8": "", + "571c8eb9dd7acb1400e4c0f9": "1777", + "571c8eb9dd7acb1400e4c0fa": "azote", + "5ad2381dd7d075001a42882a": "", + "5ad2381dd7d075001a42882b": "Azote", + "5ad2381dd7d075001a42882c": "1777", + "571c9074dd7acb1400e4c100": "Trioxygen", + "571c9074dd7acb1400e4c101": "", + "571c9074dd7acb1400e4c102": "ozone absorbs strongly in the UV region of the spectrum", + "571c9074dd7acb1400e4c103": "protective radiation shield", + "571c9074dd7acb1400e4c104": "UV", + "5ad24ce8d7d075001a428c0c": "", + "5ad24ce8d7d075001a428c0d": "", + "5ad24ce8d7d075001a428c0e": "", + "5ad24ce8d7d075001a428c0f": "", + "571c91c8dd7acb1400e4c10a": "dioxygen", + "571c91c8dd7acb1400e4c10b": "dioxygen", + "571c91c8dd7acb1400e4c10c": "dioxygen, O\n2", + "571c91c8dd7acb1400e4c10d": "energy content", + "571c91c8dd7acb1400e4c10e": "cellular respiration", + "5ad24b13d7d075001a428bcc": "dioxygen", + "5ad24b13d7d075001a428bcd": "", + "5ad24b13d7d075001a428bce": "", + "5ad24b13d7d075001a428bcf": "Due to its energy content", + "571c9348dd7acb1400e4c114": "James Dewar", + "571c9348dd7acb1400e4c115": "1891", + "571c9348dd7acb1400e4c116": "1895", + "571c9348dd7acb1400e4c118": "oxyacetylene", + "5ad23f8fd7d075001a4288ec": "", + "5ad23f8fd7d075001a4288ed": "", + "5ad23f8fd7d075001a4288ee": "", + "5ad23f8fd7d075001a4288ef": "", + "571c96095efbb31900334dbc": "Oxygen", + "571c96095efbb31900334dbd": "temperature", + "571c96095efbb31900334dbe": "", + "571c96095efbb31900334dbf": "", + "571c96095efbb31900334dc0": "", + "5ad24de6d7d075001a428c32": "", + "5ad24de6d7d075001a428c33": "1 molecule of dissolved O\n2 for every 2 molecules of N\n2", + "5ad24de6d7d075001a428c34": "temperature", + "5ad24de6d7d075001a428c35": "", + "571c97e2dd7acb1400e4c11e": "most abundant chemical element", + "571c97e2dd7acb1400e4c11f": "third", + "571c97e2dd7acb1400e4c120": "0.9%", + "571c97e2dd7acb1400e4c121": "world's oceans", + "571c97e2dd7acb1400e4c122": "ultraviolet radiation", + "5ad24ff3d7d075001a428ca4": "Oxygen", + "5ad24ff3d7d075001a428ca5": "hydrogen and helium", + "5ad24ff3d7d075001a428ca6": "", + "5ad24ff3d7d075001a428ca7": "", + "5ad24ff3d7d075001a428ca8": "Oxygen gas", + "571caac55efbb31900334dc6": "19th", + "571caac55efbb31900334dc7": "compressing and cooling it", + "571caac55efbb31900334dc8": "Louis Paul Cailletet", + "571caac55efbb31900334dc9": "a few drops", + "571caac55efbb31900334dca": "March 29, 1883", + "5ad23eefd7d075001a4288d8": "Swiss chemist and physicist", + "5ad23eefd7d075001a4288d9": "", + "5ad23eefd7d075001a4288da": "", + "5ad23eefd7d075001a4288db": "Zygmunt Wr\u00f3blewski and Karol Olszewski", + "5ad23eefd7d075001a4288dc": "Jagiellonian University", + "571cac5d5efbb31900334dd0": "", + "571cac5d5efbb31900334dd1": "oxygen-16", + "571cac5d5efbb31900334dd2": "Genesis", + "571cac5d5efbb31900334dd3": "unknown", + "571cac5d5efbb31900334dd4": "", + "5ad25553d7d075001a428d34": "", + "5ad25553d7d075001a428d35": "", + "5ad25553d7d075001a428d36": "silicon wafer", + "5ad25553d7d075001a428d37": "", + "571cb010dd7acb1400e4c128": "Singlet oxygen", + "571cb010dd7acb1400e4c129": "common organic molecules", + "571cb010dd7acb1400e4c12a": "photosynthesis", + "571cb010dd7acb1400e4c12b": "photolysis of ozone", + "571cb010dd7acb1400e4c12c": "Carotenoids", + "5ad245f9d7d075001a428ac0": "", + "5ad245f9d7d075001a428ac1": "all the electron spins", + "5ad245f9d7d075001a428ac2": "", + "5ad245f9d7d075001a428ac3": "Carotenoids", + "571cb27fdd7acb1400e4c132": "Paleoclimatologists", + "571cb27fdd7acb1400e4c133": "the climate", + "571cb27fdd7acb1400e4c134": "12%", + "571cb27fdd7acb1400e4c135": "oxygen-18", + "571cb27fdd7acb1400e4c136": "lower global temperatures", + "5ad254a5d7d075001a428d24": "", + "5ad254a5d7d075001a428d25": "", + "5ad254a5d7d075001a428d26": "12%", + "5ad254a5d7d075001a428d27": "", + "571cbe35dd7acb1400e4c13c": "687 and 760 nm", + "571cbe35dd7acb1400e4c13d": "carbon cycle", + "571cbe35dd7acb1400e4c13e": "vegetation canopies", + "571cbe35dd7acb1400e4c13f": "", + "571cbe35dd7acb1400e4c140": "remote sensing", + "5ad257e2d7d075001a428d98": "", + "5ad257e2d7d075001a428d99": "", + "5ad257e2d7d075001a428d9a": "", + "571cc3dedd7acb1400e4c146": "", + "571cc3dedd7acb1400e4c147": "liquid oxygen", + "571cc3dedd7acb1400e4c148": "the unpaired electrons", + "571cc3dedd7acb1400e4c149": "magnetic field", + "571cc3dedd7acb1400e4c14a": "a magnet", + "5ad2456dd7d075001a428aa2": "paramagnetic", + "5ad2456dd7d075001a428aa3": "they impart magnetic character to oxygen when it is in the presence of a magnetic field", + "5ad2456dd7d075001a428aa4": "", + "571cc5c45efbb31900334dda": "peroxide, superoxide, and singlet oxygen to destroy invading microbes", + "571cc5c45efbb31900334ddb": "destroy invading microbes", + "571cc5c45efbb31900334ddc": "pathogen attack", + "571cc5c45efbb31900334ddd": "obligately anaerobic", + "571cc5c45efbb31900334dde": "2.5 billion years ago", + "5ad258b4d7d075001a428dda": "", + "5ad258b4d7d075001a428ddb": "superoxide ion", + "5ad258b4d7d075001a428ddc": "", + "5ad258b4d7d075001a428ddd": "", + "5ad258b4d7d075001a428dde": "Great Oxygenation Event", + "571cc6f85efbb31900334de4": "90.20 K", + "571cc6f85efbb31900334de5": "", + "571cc6f85efbb31900334de6": "", + "571cc6f85efbb31900334de7": "liquid nitrogen", + "571cc6f85efbb31900334de8": "combustible", + "5ad24eb1d7d075001a428c62": "", + "5ad24eb1d7d075001a428c63": "", + "5ad24eb1d7d075001a428c64": "", + "5ad24eb1d7d075001a428c65": "", + "571cc8815efbb31900334dee": "world's water bodies", + "571cc8815efbb31900334def": "", + "571cc8815efbb31900334df0": "higher oxygen content", + "571cc8815efbb31900334df1": "biochemical oxygen demand", + "571cc8815efbb31900334df2": "algae", + "5ad252e6d7d075001a428d0c": "", + "5ad252e6d7d075001a428d0d": "", + "5ad252e6d7d075001a428d0e": "Water polluted with plant nutrients", + "5ad252e6d7d075001a428d0f": "", + "571cca4add7acb1400e4c150": "3.5 billion years ago", + "571cca4add7acb1400e4c151": "Paleoproterozoic", + "571cca4add7acb1400e4c152": "banded iron formations", + "571cca4add7acb1400e4c153": "1.7 billion years ago", + "571cca4add7acb1400e4c154": "3\u20132.7 billion years ago", + "5ad25b1cd7d075001a428e66": "", + "5ad25b1cd7d075001a428e67": "Paleoproterozoic", + "5ad25b1cd7d075001a428e68": "", + "5ad25b1cd7d075001a428e69": "", + "571ccc00dd7acb1400e4c15a": "oxygen cycle", + "571ccc00dd7acb1400e4c15b": "biogeochemical", + "571ccc00dd7acb1400e4c15c": "three", + "571ccc00dd7acb1400e4c15d": "photosynthesis", + "571ccc00dd7acb1400e4c15e": "oxygen", + "5ad251d6d7d075001a428ce8": "", + "5ad251d6d7d075001a428ce9": "the atmosphere, the biosphere, and the lithosphere", + "5ad251d6d7d075001a428cea": "", + "5ad251d6d7d075001a428ceb": "photosynthesis", + "571ccd9b5efbb31900334df8": "a pipeline", + "571ccd9b5efbb31900334df9": "", + "571ccd9b5efbb31900334dfa": "nitrogen", + "571ccd9b5efbb31900334dfb": "", + "571ccd9b5efbb31900334dfc": "", + "5ad25bf3d7d075001a428e94": "", + "5ad25bf3d7d075001a428e95": "gaseous oxygen to be pumped through a pipeline", + "5ad25bf3d7d075001a428e96": "", + "571ccfbadd7acb1400e4c164": "water", + "571ccfbadd7acb1400e4c165": "Oxygen gas", + "571ccfbadd7acb1400e4c166": "", + "571ccfbadd7acb1400e4c167": "oxides and oxoacids", + "571ccfbadd7acb1400e4c168": "Chemical", + "5ad25d05d7d075001a428ed0": "Oxygen gas", + "5ad25d05d7d075001a428ed1": "", + "5ad25d05d7d075001a428ed2": "oxides and oxoacids", + "5ad25d05d7d075001a428ed3": "", + "571cd11add7acb1400e4c16e": "recreational", + "571cd11add7acb1400e4c16f": "", + "571cd11add7acb1400e4c170": "performance", + "571cd11add7acb1400e4c171": "aerobic", + "571cd11add7acb1400e4c172": "placebo effect", + "5ad26105d7d075001a428ff4": "", + "5ad26105d7d075001a428ff5": "", + "5ad26105d7d075001a428ff6": "", + "5ad26105d7d075001a428ff7": "placebo", + "571cd3b55efbb31900334e03": "special oxygen chambers", + "571cd3b55efbb31900334e04": "carbon monoxide", + "571cd3b55efbb31900334e05": "anaerobic bacteria", + "571cd3b55efbb31900334e06": "Decompression sickness", + "5ad25f35d7d075001a428f6a": "special oxygen chambers", + "5ad25f35d7d075001a428f6b": "", + "5ad25f35d7d075001a428f6c": "", + "5ad25f35d7d075001a428f6d": "divers", + "571cd5b1dd7acb1400e4c178": "respiration", + "571cd5b1dd7acb1400e4c179": "oxygen supplementation", + "571cd5b1dd7acb1400e4c17a": "heart", + "571cd5b1dd7acb1400e4c17b": "", + "571cd5b1dd7acb1400e4c17c": "", + "5ad25e70d7d075001a428f1c": "", + "5ad25e70d7d075001a428f1d": "", + "5ad25e70d7d075001a428f1e": "emphysema, pneumonia", + "5ad25e70d7d075001a428f1f": "increases oxygen levels in the patient's blood", + "571cd703dd7acb1400e4c182": "electronegativity", + "571cd703dd7acb1400e4c183": "chemical bonds", + "571cd703dd7acb1400e4c184": "FeO", + "571cd703dd7acb1400e4c185": "chemical bonds", + "571cd703dd7acb1400e4c186": "further corrosion", + "5ad261bad7d075001a429050": "chemical", + "5ad261bad7d075001a429051": "electronegativity", + "5ad261bad7d075001a429052": "", + "5ad261bad7d075001a429053": "", + "571cd88ddd7acb1400e4c18d": "cabin depressurization", + "571cd88ddd7acb1400e4c18e": "exothermic reaction", + "571cd88ddd7acb1400e4c18f": "exothermic", + "571cd88ddd7acb1400e4c190": "oxygen", + "5ad26000d7d075001a428fae": "People who climb mountains or fly in non-pressurized fixed-wing aircraft", + "5ad26000d7d075001a428faf": "Passengers traveling in (pressurized) commercial airplanes", + "5ad26000d7d075001a428fb0": "emergency supply of O\n2", + "5ad26000d7d075001a428fb1": "exothermic", + "571cda1bdd7acb1400e4c196": "Oxygen storage methods", + "571cda1bdd7acb1400e4c197": "liquid", + "571cda1bdd7acb1400e4c198": "insulated tankers", + "571cda1bdd7acb1400e4c199": "compressed gas", + "571cda1bdd7acb1400e4c19a": "hospitals", + "5ad25dd3d7d075001a428f00": "", + "5ad25dd3d7d075001a428f01": "", + "5ad25dd3d7d075001a428f02": "", + "5ad25dd3d7d075001a428f03": "", + "571cdcb85efbb31900334e0c": "organic solvents", + "571cdcb85efbb31900334e0d": "organic", + "571cdcb85efbb31900334e0e": "feeder materials", + "571cdcb85efbb31900334e0f": "Epoxides", + "571cdcb85efbb31900334e10": "", + "5ad262e2d7d075001a4290ca": "acetone, methanol, ethanol, isopropanol, furan, THF, diethyl ether", + "5ad262e2d7d075001a4290cb": "alcohols (R-OH)", + "5ad262e2d7d075001a4290cc": "ethers", + "5ad262e2d7d075001a4290cd": "ethers", + "5ad262e2d7d075001a4290ce": "ethers", + "571cde695efbb31900334e16": "biomolecules", + "571cde695efbb31900334e17": "a few", + "571cde695efbb31900334e18": "carbohydrates", + "571cde695efbb31900334e19": "proteins", + "571cde695efbb31900334e1a": "", + "5ad26479d7d075001a42914e": "", + "5ad26479d7d075001a42914f": "oxygen", + "5ad26479d7d075001a429150": "", + "5ad26479d7d075001a429151": "oxygen", + "571ce3745efbb31900334e20": "pulmonary fibrosis", + "571ce3745efbb31900334e21": "permanent pulmonary fibrosis", + "571ce3745efbb31900334e22": "160 kPa", + "571ce3745efbb31900334e23": "seizures", + "571ce3745efbb31900334e24": "seizures", + "5ad266d0d7d075001a4291ec": "", + "5ad266d0d7d075001a4291ed": "", + "5ad266d0d7d075001a4291ee": "", + "5ad266d0d7d075001a4291ef": "", + "571ce5055efbb31900334e2a": "low total pressures used", + "571ce5055efbb31900334e2b": "", + "571ce5055efbb31900334e2c": "", + "571ce5055efbb31900334e2d": "", + "571ce5055efbb31900334e2e": "", + "5ad265efd7d075001a4291d0": "no damage due to the low total pressures used", + "5ad265efd7d075001a4291d1": "low total pressures used", + "5ad265efd7d075001a4291d2": "", + "5ad265efd7d075001a4291d3": "30 kPa", + "571ce6655efbb31900334e34": "at elevated partial pressures", + "571ce6655efbb31900334e35": "partial pressures more than 50 kilopascals (kPa)", + "571ce6655efbb31900334e36": "50% oxygen composition at standard pressure", + "571ce6655efbb31900334e37": "mechanical ventilators", + "571ce6655efbb31900334e38": "30%\u201350% O\n2", + "5ad26530d7d075001a4291a0": "", + "5ad26530d7d075001a4291a1": "", + "5ad26530d7d075001a4291a2": "", + "5ad26530d7d075001a4291a3": "", + "5725b33f6a3fe71400b8952d": "October 1973", + "5725b33f6a3fe71400b8952e": "US$3 per barrel", + "5725b33f6a3fe71400b8952f": "1979", + "5725b33f6a3fe71400b89530": "first oil shock", + "5725b33f6a3fe71400b89531": "the members of the Organization of Arab Petroleum Exporting Countries", + "5a38a8d2a4b263001a8c1875": "", + "5a38a8d2a4b263001a8c1876": "", + "5a38a8d2a4b263001a8c1877": "", + "5a38a8d2a4b263001a8c1878": "", + "5a38a8d2a4b263001a8c1879": "", + "5a75028897ca42001a521daf": "October", + "5a75028897ca42001a521db0": "Arab members of OPEC plus Egypt and Syria", + "5a75028897ca42001a521db1": "\"first oil shock\", followed by the 1979 oil crisis, termed the \"second oil shock.\"", + "5a75028897ca42001a521db2": "second oil shock", + "5a75028897ca42001a521db3": "The embargo", + "5725b5a689a1e219009abd28": "to avoid being targeted by the boycott", + "5725b5a689a1e219009abd29": "", + "5725b5a689a1e219009abd2a": "January 18, 1974", + "5725b5a689a1e219009abd2b": "March 1974", + "5a38aa28a4b263001a8c187f": "created a rift within NATO", + "5a38aa28a4b263001a8c1880": "", + "5a38aa28a4b263001a8c1881": "any future policy changes to peace between the belligerents", + "5a38aa28a4b263001a8c1882": "", + "5a38aa28a4b263001a8c1883": "embargo", + "5a7504cb97ca42001a521dc3": "NATO", + "5a7504cb97ca42001a521dc4": "Japan", + "5a7504cb97ca42001a521dc5": "Arab oil producers", + "5a7504cb97ca42001a521dc6": "multilateral negotiations with the combatants", + "5a7504cb97ca42001a521dc7": "Israel", + "5725b76389a1e219009abd4a": "August 15, 1971", + "5725b76389a1e219009abd4b": "rise and fall according to market demand", + "5725b76389a1e219009abd4c": "the industrialized nations increased their reserves", + "5725b76389a1e219009abd4d": "September 1971", + "5725b76389a1e219009abd4e": "", + "5a38ab9fa4b263001a8c1889": "", + "5a38ab9fa4b263001a8c188a": "", + "5a38ab9fa4b263001a8c188b": "floating the pound sterling", + "5a38ab9fa4b263001a8c188c": "", + "5a38ab9fa4b263001a8c188d": "", + "5a75054b97ca42001a521dcd": "Gold Exchange Standard", + "5a75054b97ca42001a521dce": "Gold Exchange Standard", + "5a75054b97ca42001a521dcf": "float\" (rise and fall according to market demand)", + "5a75054b97ca42001a521dd0": "rise and fall according to market demand", + "5a75054b97ca42001a521dd1": "September 1971", + "5725b92e38643c19005acbd3": "less than two percent per year", + "5725b92e38643c19005acbd4": "", + "5725b92e38643c19005acbd5": "", + "5725b92e38643c19005acbd6": "the oil shock", + "5a38ace7a4b263001a8c1893": "", + "5a38ace7a4b263001a8c1894": "fairly stable", + "5a38ace7a4b263001a8c1895": "", + "5a38ace7a4b263001a8c1896": "", + "5a38ace7a4b263001a8c1897": "", + "5a7505e497ca42001a521de1": "OPEC", + "5a7505e497ca42001a521de2": "", + "5a7505e497ca42001a521de3": "The substantial price increases", + "5a7505e497ca42001a521de4": "the oil shock", + "5725bad5271a42140099d0bd": "October 6, 1973", + "5725bad5271a42140099d0be": "Iran", + "5725bad5271a42140099d0bf": "ten", + "5725bad5271a42140099d0c0": "Iran", + "5725bad5271a42140099d0c1": "\"Of course [the price of oil] is going to rise", + "5a38b07ca4b263001a8c189d": "launched a surprise attack on Israel", + "5a38b07ca4b263001a8c189e": "", + "5a38b07ca4b263001a8c189f": "", + "5a38b07ca4b263001a8c18a0": "300 percent", + "5a38b07ca4b263001a8c18a1": "petrochemicals", + "5a75066297ca42001a521de9": "launched a surprise attack on Israel", + "5a75066297ca42001a521dea": "October 6, 1973", + "5a75066297ca42001a521deb": "second-largest", + "5a75066297ca42001a521dec": "close US ally", + "5a75066297ca42001a521ded": "ten times more", + "5725bcb6271a42140099d0eb": "American aid to Israel", + "5725bcb6271a42140099d0ec": "October 16, 1973", + "5725bcb6271a42140099d0ed": "September's output", + "5725bcb6271a42140099d0ee": "$2.2 billion", + "5725bcb6271a42140099d0ef": "a \"principal hostile country", + "5a38b29da4b263001a8c18a7": "", + "5a38b29da4b263001a8c18a8": "", + "5a38b29da4b263001a8c18a9": "embargo", + "5a38b29da4b263001a8c18aa": "embargo", + "5a38b29da4b263001a8c18ab": "", + "5a75082a97ca42001a521df3": "raised the posted price of oil by 70%, to $5.11 a barrel", + "5a75082a97ca42001a521df4": "70%", + "5a75082a97ca42001a521df5": "$5.11 a barrel", + "5a75082a97ca42001a521df6": "Libya", + "5a75082a97ca42001a521df7": "October 20, 1973", + "57261dab38643c19005ad037": "over 100 billion dollars", + "57261dab38643c19005ad038": "Al-Qaeda and the Taliban", + "57261dab38643c19005ad039": "Middle East", + "57261dab38643c19005ad03a": "shrinking Western demand", + "57261dab38643c19005ad03b": "Wahhabism", + "5a38b468a4b263001a8c18b1": "over 100 billion dollars", + "5a38b468a4b263001a8c18b2": "the Middle East", + "5a38b468a4b263001a8c18b3": "in the ensuing decades", + "5a38b468a4b263001a8c18b4": "", + "5a38b468a4b263001a8c18b5": "", + "57261f9f271a42140099d4a9": "distribution and price disruptions", + "57261f9f271a42140099d4aa": "the USSR", + "57261f9f271a42140099d4ab": "1973", + "57261f9f271a42140099d4ac": "Kissinger's dominance", + "5a38b5bca4b263001a8c18bb": "", + "5a38b5bca4b263001a8c18bc": "", + "5a38b5bca4b263001a8c18bd": "", + "5a38b5bca4b263001a8c18be": "", + "5a38b5bca4b263001a8c18bf": "", + "5726241189a1e219009ac2de": "The embargo", + "5726241189a1e219009ac2df": "automobiles", + "5726241189a1e219009ac2e0": "Macroeconomic problems", + "5726241189a1e219009ac2e1": "the Arctic", + "5726241189a1e219009ac2e2": "five to ten years", + "5a38b819a4b263001a8c18c5": "", + "5a38b819a4b263001a8c18c6": "usually required five to ten years before significant production", + "5a38b819a4b263001a8c18c7": "the price increases changed competitive positions", + "5a38b819a4b263001a8c18c8": "", + "5a38b819a4b263001a8c18c9": "", + "5726487b5951b619008f6edd": "Netherlands", + "5726487b5951b619008f6ede": "America", + "5726487b5951b619008f6edf": "UK", + "5726487b5951b619008f6ee0": "Israelis", + "5726487b5951b619008f6ee1": "Ted Heath", + "5a38b9b3a4b263001a8c18cf": "", + "5a38b9b3a4b263001a8c18d0": "airfields", + "5a38b9b3a4b263001a8c18d1": "the Israelis", + "5a38b9b3a4b263001a8c18d2": "", + "5a38b9b3a4b263001a8c18d3": "withdraw to its pre-1967 borders", + "572649d8f1498d1400e8db36": "", + "572649d8f1498d1400e8db37": "a series of strikes by coal miners and railroad workers", + "572649d8f1498d1400e8db38": "winter of 1973\u201374", + "572649d8f1498d1400e8db39": "Germany", + "572649d8f1498d1400e8db3a": "Sweden", + "5a38baa2a4b263001a8c18d9": "flying, driving and boating", + "5a38baa2a4b263001a8c18da": "", + "5a38baa2a4b263001a8c18db": "prison sentences", + "5a38baa2a4b263001a8c18dc": "", + "5a38baa2a4b263001a8c18dd": "", + "57264cac708984140094c1b3": "Price controls", + "57264cac708984140094c1b4": "to encourage investment", + "57264cac708984140094c1b5": "creating greater scarcity", + "57264cac708984140094c1b7": "rationing", + "5a38bbe3a4b263001a8c18e3": "to encourage investment", + "5a38bbe3a4b263001a8c18e4": "", + "5a38bbe3a4b263001a8c18e5": "", + "5a38bbe3a4b263001a8c18e6": "", + "5a38bbe3a4b263001a8c18e7": "rationing", + "57264d9edd62a815002e80fe": "William E. Simon", + "57264d9edd62a815002e80ff": "1973", + "57264d9edd62a815002e8100": "to coordinate the response to the embargo", + "57264d9edd62a815002e8101": "", + "5a38bd58a4b263001a8c18ed": "", + "5a38bd58a4b263001a8c18ee": "William E. Simon as the first Administrator of the Federal Energy Office", + "5a38bd58a4b263001a8c18ef": "", + "5a38bd58a4b263001a8c18f0": "", + "5a38bd58a4b263001a8c18f1": "lines at gasoline stations", + "57264efddd62a815002e8134": "55 mph", + "57264efddd62a815002e8135": "Emergency Highway Energy Conservation Act", + "57264efddd62a815002e8136": "", + "57264efddd62a815002e8137": "November 28, 1995", + "57264efddd62a815002e8138": "1977", + "5a38bf63a4b263001a8c18f7": "", + "5a38bf63a4b263001a8c18f8": "Bill Clinton", + "5a38bf63a4b263001a8c18f9": "", + "5a38bf63a4b263001a8c18fa": "", + "5a38bf63a4b263001a8c18fb": "55 mph", + "572650325951b619008f6fa9": "The energy crisis", + "572650325951b619008f6faa": "market and technology realities", + "572650325951b619008f6fab": "congresses and presidents", + "5a38c16aa4b263001a8c1901": "", + "5a38c16aa4b263001a8c1902": "", + "5a38c16aa4b263001a8c1903": "", + "5a38c16aa4b263001a8c1904": "", + "5a38c16aa4b263001a8c1905": "", + "57265200708984140094c237": "U.S.", + "57265200708984140094c238": "British", + "57265200708984140094c239": "10 years", + "57265200708984140094c23a": "the Arabs", + "5a38c34ea4b263001a8c190b": "", + "5a38c34ea4b263001a8c190c": "", + "5a38c34ea4b263001a8c190d": "", + "5a38c34ea4b263001a8c190e": "", + "5a38c34ea4b263001a8c190f": "", + "57265360dd62a815002e819a": "Japan", + "57265360dd62a815002e819b": "71%", + "57265360dd62a815002e819c": "declared Japan a \"nonfriendly\" country to encourage it to change its noninvolvement policy", + "57265360dd62a815002e819d": "November 22", + "57265360dd62a815002e819e": "December 25", + "5a38c6bca4b263001a8c1915": "Japan", + "5a38c6bca4b263001a8c1916": "5% production cut", + "5a38c6bca4b263001a8c1917": "threatening to reconsider its policy", + "5a38c6bca4b263001a8c1918": "", + "5a38c6bca4b263001a8c1919": "a panic", + "57265526708984140094c2bd": "USSR", + "57265526708984140094c2be": "Saudi Arabia and Iran", + "57265526708984140094c2bf": "Saudi", + "57265526708984140094c2c0": "January 1979", + "57265526708984140094c2c1": "November 1979", + "5a38c911a4b263001a8c191f": "", + "5a38c911a4b263001a8c1920": "increased American weapons sales, technology, and outright military presence", + "5a38c911a4b263001a8c1921": "", + "5a38c911a4b263001a8c1922": "", + "5a38c911a4b263001a8c1923": "near absolutist", + "5726581fdd62a815002e823a": "", + "5726581fdd62a815002e823b": "Japanese", + "5726581fdd62a815002e823c": "V8", + "5726581fdd62a815002e823d": "Japanese", + "5a38cd93a4b263001a8c1929": "", + "5a38cd93a4b263001a8c192a": "six cylinder", + "5a38cd93a4b263001a8c192b": "", + "5a38cd93a4b263001a8c192c": "Japanese", + "5a38cd93a4b263001a8c192d": "", + "572659535951b619008f703f": "A decade after the 1973 oil crisis", + "572659535951b619008f7040": "Toyota Corona Mark II", + "572659535951b619008f7041": "Toyota Corona Mark II", + "572659535951b619008f7042": "Acura, Lexus and Infiniti", + "5a38ceaaa4b263001a8c1933": "assembly plants", + "5a38ceaaa4b263001a8c1934": "", + "5a38ceaaa4b263001a8c1935": "", + "5a38ceaaa4b263001a8c1936": "", + "5a38ceaaa4b263001a8c1937": "", + "57265a58dd62a815002e8270": "Toyota Hilux and the Datsun Truck", + "57265a58dd62a815002e8271": "Dodge D-50", + "57265a58dd62a815002e8272": "Ford, Chrysler, and GM", + "57265a58dd62a815002e8273": "captive import", + "5a38d2f9a4b263001a8c193d": "", + "5a38d2f9a4b263001a8c193e": "", + "5a38d2f9a4b263001a8c193f": "", + "5a38d2f9a4b263001a8c1940": "", + "5a38d2f9a4b263001a8c1941": "Toyota Hilux and the Datsun Truck", + "57265bdfdd62a815002e829e": "An increase in imported cars", + "57265bdfdd62a815002e829f": "at least four", + "57265bdfdd62a815002e82a0": "1985", + "57265bdfdd62a815002e82a1": "Cadillac DeVille and Fleetwood, Buick Electra, Oldsmobile 98, Lincoln Continental, Mercury Marquis", + "57265bdfdd62a815002e82a2": "Chevrolet Bel Air, and Ford Galaxie 500", + "5a38d4b9a4b263001a8c1947": "introduce smaller and fuel-efficient models for domestic sales", + "5a38d4b9a4b263001a8c1948": "", + "5a38d4b9a4b263001a8c1949": "13.5", + "5a38d4b9a4b263001a8c194a": "Chevrolet Bel Air, and Ford Galaxie 500", + "5a38d4b9a4b263001a8c194b": "13.5", + "57265ceddd62a815002e82b8": "1979", + "57265ceddd62a815002e82b9": "1981", + "57265ceddd62a815002e82ba": "1974 Mustang I", + "5a38d6e6a4b263001a8c1951": "virtually all \"full-size\" American cars had shrunk", + "5a38d6e6a4b263001a8c1952": "1981", + "5a38d6e6a4b263001a8c1953": "", + "5a38d6e6a4b263001a8c1954": "full-sized", + "5a38d6e6a4b263001a8c1955": "M-body Dodge Diplomat/Plymouth Gran Fury and Chrysler New Yorker Fifth Avenue sedans", + "57265e11708984140094c3bb": "1981", + "57265e11708984140094c3bc": "1980s", + "57265e11708984140094c3bd": "recover market share", + "57265e11708984140094c3be": "$40 per barrel", + "5a38d93da4b263001a8c195b": "1981", + "5a38d93da4b263001a8c195c": "", + "5a38d93da4b263001a8c195d": "shrinking or eliminating profits for high-cost producers", + "5a38d93da4b263001a8c195e": "", + "5a38d93da4b263001a8c195f": "less than $10 per barrel", + "5725b7f389a1e219009abd5d": "a body of treaties and legislation", + "5725b7f389a1e219009abd5e": "the Treaties establishing the European Union", + "5725b7f389a1e219009abd5f": "regulations and directives", + "5725b7f389a1e219009abd60": "European Parliament and the Council of the European Union", + "5725c28a271a42140099d14d": "a body of treaties and legislation", + "5725c28a271a42140099d14e": "direct effect or indirect effect", + "5725c28a271a42140099d14f": "primary law, secondary law and supplementary law", + "5725c28a271a42140099d150": "European Parliament and the Council of the European Union", + "57268b43dd62a815002e88f0": "primary law, secondary law and supplementary law", + "57268b43dd62a815002e88f1": "the Treaties establishing the European Union", + "57268b43dd62a815002e88f2": "European Parliament and the Council of the European Union", + "57268b43dd62a815002e88f3": "three", + "5ad108f9645df0001a2d0a74": "", + "5ad108f9645df0001a2d0a75": "", + "5ad108f9645df0001a2d0a76": "", + "5ad108f9645df0001a2d0a77": "", + "5ad108f9645df0001a2d0a78": "", + "5725bbec271a42140099d0d1": "courts of member states and the Court of Justice of the European Union", + "5725bbec271a42140099d0d2": "courts of member states", + "5725bbec271a42140099d0d4": "The European Court of Justice", + "5725bbec271a42140099d0d5": "case law by the Court of Justice, international law and general principles of European Union law", + "5725c3a9ec44d21400f3d503": "member states and the Court of Justice of the European Union", + "5725c3a9ec44d21400f3d504": "Treaty on the Functioning of the European Union", + "5725c3a9ec44d21400f3d505": "The European Court of Justice", + "5725c3a9ec44d21400f3d506": "case law by the Court of Justice, international law and general principles of European Union law", + "57268bf9dd62a815002e890a": "the courts of member states and the Court of Justice of the European Union", + "57268bf9dd62a815002e890b": "the courts of member states", + "57268bf9dd62a815002e890c": "The European Court of Justice", + "57268bf9dd62a815002e890d": "case law by the Court of Justice, international law and general principles of European Union law", + "5ad10e0f645df0001a2d0b72": "", + "5ad10e0f645df0001a2d0b73": "", + "5ad10e0f645df0001a2d0b74": "", + "5ad10e0f645df0001a2d0b75": "", + "5ad10e0f645df0001a2d0b76": "", + "5725c743ec44d21400f3d549": "the Treaty on European Union (TEU) and the Treaty on the Functioning of the European Union (TFEU)", + "5725c743ec44d21400f3d54a": "The European Commission", + "5725c743ec44d21400f3d54b": "citizens", + "5725c743ec44d21400f3d54c": "The European Court of Justice", + "5725c743ec44d21400f3d54d": "The \"European Council", + "5ad10ece645df0001a2d0b98": "", + "5ad10ece645df0001a2d0b99": "", + "5ad10ece645df0001a2d0b9a": "", + "5ad10ece645df0001a2d0b9b": "", + "5ad10ece645df0001a2d0b9c": "", + "5725ca4389a1e219009abeb4": "The TEU", + "5725ca4389a1e219009abeb5": "The TEU specifically excludes certain regions", + "5725ca4389a1e219009abeb6": "can interpret the Treaties, but it cannot rule on their validity", + "5725ca4389a1e219009abeb7": "interpret the Treaties", + "5725ca4389a1e219009abeb8": "as soon as they enter into force", + "57268d2ddd62a815002e894e": "the Treaty on European Union (TEU) and the Treaty on the Functioning of the European Union (TFEU)", + "57268d2ddd62a815002e894f": "Gibraltar and the \u00c5land islands", + "57268d2ddd62a815002e8950": "as soon as they enter into force", + "57268d2ddd62a815002e8951": "The Court of Justice of the European Union", + "5ad10f94645df0001a2d0bc4": "", + "5ad10f94645df0001a2d0bc5": "", + "5ad10f94645df0001a2d0bc6": "", + "5ad10f94645df0001a2d0bc7": "", + "5ad10f94645df0001a2d0bc8": "", + "5725cc38ec44d21400f3d5bb": "with common rules for coal and steel, and then atomic energy", + "5725cc38ec44d21400f3d5bc": "Treaty of Rome 1957 and the Maastricht Treaty 1992", + "5725cc38ec44d21400f3d5bd": "1985", + "5725cc38ec44d21400f3d5be": "Norway did not end up joining", + "5725cc38ec44d21400f3d5bf": "Greenland", + "57268e2bf1498d1400e8e3b0": "common rules for coal and steel, and then atomic energy", + "57268e2bf1498d1400e8e3b1": "1992", + "57268e2bf1498d1400e8e3b2": "1986", + "57268e2bf1498d1400e8e3b3": "1972", + "57268e2bf1498d1400e8e3b4": "1985", + "5ad11097645df0001a2d0be0": "", + "5ad11097645df0001a2d0be1": "", + "5ad11097645df0001a2d0be2": "", + "5ad11097645df0001a2d0be3": "1985", + "5ad11097645df0001a2d0be4": "1972", + "57264865dd62a815002e8062": "Following the Nice Treaty", + "57264865dd62a815002e8063": "France and the referendum in the Netherlands", + "57264865dd62a815002e8064": "very similar", + "57264865dd62a815002e8065": "an amending treaty", + "57264865dd62a815002e8066": "it did not completely replace them", + "57268f2bf1498d1400e8e3c4": "the constitutional law of the European Union", + "57268f2bf1498d1400e8e3c5": "make it more transparent; this would have also produced a single constitutional document", + "57268f2bf1498d1400e8e3c6": "referendum in France and the referendum in the Netherlands", + "57268f2bf1498d1400e8e3c7": "the Lisbon Treaty", + "5ad11186645df0001a2d0bfe": "", + "5ad11186645df0001a2d0bff": "", + "5ad11186645df0001a2d0c00": "", + "5ad11186645df0001a2d0c01": "the Lisbon Treaty", + "5ad11186645df0001a2d0c02": "", + "57264a8cdd62a815002e808c": "The European Commission", + "57264a8cdd62a815002e808d": "", + "57264a8cdd62a815002e808e": "The Commission's President", + "57264a8cdd62a815002e808f": "one", + "57264a8cdd62a815002e8090": "Federica Mogherini", + "572691545951b619008f76e1": "Article 17", + "572691545951b619008f76e2": "The Commission's President", + "572691545951b619008f76e3": "a simple majority vote", + "572691545951b619008f76e4": "Ireland", + "572691545951b619008f76e5": "", + "5ad11288645df0001a2d0c30": "", + "5ad11288645df0001a2d0c31": "", + "5ad11288645df0001a2d0c32": "", + "5ad11288645df0001a2d0c33": "", + "5ad11288645df0001a2d0c34": "", + "57264e455951b619008f6f65": "Santer Commission", + "57264e455951b619008f6f66": "did in fact not break any law", + "57264e455951b619008f6f67": "a Committee of Independent Experts", + "57264e455951b619008f6f68": "European Council", + "57264e455951b619008f6f69": "do not have voting rights", + "5726926a5951b619008f7709": "1999", + "5726926a5951b619008f770a": "Commission v Edith Cresson", + "5726926a5951b619008f770b": "a Committee of Independent Experts", + "5726926a5951b619008f770c": "European Anti-fraud Office", + "5726926a5951b619008f770d": "2012", + "5ad11374645df0001a2d0c6c": "", + "5ad11374645df0001a2d0c6d": "", + "5ad11374645df0001a2d0c6e": "", + "5ad11374645df0001a2d0c6f": "", + "5ad11374645df0001a2d0c70": "", + "5726545f708984140094c2a5": "different ministers of the member states", + "5726545f708984140094c2a6": "Donald Tusk", + "5726545f708984140094c2a7": "inversely", + "5726545f708984140094c2a8": "352", + "5726545f708984140094c2a9": "260", + "57269424dd62a815002e8a1e": "", + "57269424dd62a815002e8a1f": "each six months", + "57269424dd62a815002e8a20": "352", + "57269424dd62a815002e8a21": "", + "5ad1373b645df0001a2d11cc": "", + "5ad1373b645df0001a2d11cd": "", + "5ad1373b645df0001a2d11ce": "", + "5ad1373b645df0001a2d11cf": "", + "5ad1373b645df0001a2d11d0": "", + "572656e4dd62a815002e81fa": "a majority of all MEPs", + "572656e4dd62a815002e81fb": "qualified majority", + "572656e4dd62a815002e81fc": "harder", + "572656e4dd62a815002e81fd": "TEU articles 4 and 5", + "572656e4dd62a815002e81fe": "the Court of Justice", + "572695285951b619008f774b": "294", + "572695285951b619008f774c": "a majority in Parliament", + "572695285951b619008f774d": "TEU articles 4 and 5", + "572695285951b619008f774e": "Conciliation Committee", + "5ad138f4645df0001a2d1258": "", + "5ad138f4645df0001a2d1259": "", + "5ad138f4645df0001a2d125a": "", + "5ad138f4645df0001a2d125b": "", + "5ad138f4645df0001a2d125c": "", + "572658435951b619008f7025": "judicial", + "572658435951b619008f7026": "Court of Justice of the European Union", + "572658435951b619008f7027": "28", + "572658435951b619008f7028": "member state courts", + "572658435951b619008f7029": "to \"ensure that in the interpretation and application of the Treaties the law is observed", + "5726965ef1498d1400e8e484": "by assuming the task of interpreting the treaties, and accelerating economic and political integration", + "5726965ef1498d1400e8e485": "Court of Justice of the European Union", + "5726965ef1498d1400e8e486": "Civil Service Tribunal", + "5726965ef1498d1400e8e487": "three years", + "5726965ef1498d1400e8e488": "to \"ensure that in the interpretation and application of the Treaties the law is observed", + "5ad139b2645df0001a2d1292": "", + "5ad139b2645df0001a2d1293": "", + "5ad139b2645df0001a2d1294": "", + "5ad139b2645df0001a2d1295": "", + "5ad139b2645df0001a2d1296": "", + "57265e455951b619008f70bb": "Community law", + "57265e455951b619008f70bc": "protest against the nationalisation of the Italian energy corporations", + "57265e455951b619008f70bd": "1964 and 1968", + "5726975c708984140094cb1f": "European Court of Justice and the highest national courts", + "5726975c708984140094cb20": "1964", + "5726975c708984140094cb21": "Court of Justice", + "5ad13b23645df0001a2d12f8": "", + "5ad13b23645df0001a2d12f9": "", + "5ad13b23645df0001a2d12fa": "", + "5ad13b23645df0001a2d12fb": "Court of Justice", + "572699db5951b619008f7799": "EU law", + "572699db5951b619008f779a": "", + "572699db5951b619008f779b": "1972", + "572699db5951b619008f779c": "if the EU does not comply with its basic constitutional rights and principles", + "572699db5951b619008f779d": "the ultimate authority of member states, its factual commitment to human rights, and the democratic will of the people", + "5ad13dbb645df0001a2d1368": "", + "5ad13dbb645df0001a2d1369": "", + "5ad13dbb645df0001a2d136a": "", + "5ad13dbb645df0001a2d136b": "", + "5ad13dbb645df0001a2d136c": "", + "57269aa65951b619008f77ab": "administrative law", + "57269aa65951b619008f77ac": "1986", + "57269aa65951b619008f77ad": "All actions", + "57269aa65951b619008f77ae": "constitutional law", + "5ad13ef3645df0001a2d138c": "", + "5ad13ef3645df0001a2d138d": "", + "5ad13ef3645df0001a2d138e": "", + "5ad13ef3645df0001a2d138f": "", + "5ad13ef3645df0001a2d1390": "", + "57269bb8708984140094cb95": "Van Gend en Loos v Nederlandse Administratie der Belastingen", + "57269bb8708984140094cb96": "article 30", + "57269bb8708984140094cb97": "postal", + "57269bb8708984140094cb98": "Treaty provisions", + "5ad14012645df0001a2d13b0": "", + "5ad14012645df0001a2d13b1": "", + "5ad14012645df0001a2d13b2": "", + "57269cc3dd62a815002e8b12": "Directives", + "57269cc3dd62a815002e8b13": "4 weeks", + "57269cc3dd62a815002e8b14": "28", + "57269cc3dd62a815002e8b15": "early 1990s", + "5ad140ab645df0001a2d13ca": "", + "5ad140ab645df0001a2d13cb": "", + "5ad140ab645df0001a2d13cc": "4 weeks", + "5ad140ab645df0001a2d13cd": "", + "57269e3bf1498d1400e8e516": "the member state cannot enforce conflicting laws", + "57269e3bf1498d1400e8e517": "", + "57269e3bf1498d1400e8e518": "10 years", + "57269e3bf1498d1400e8e519": "", + "57269e3bf1498d1400e8e51a": "60", + "5ad141e1645df0001a2d1402": "", + "5ad141e1645df0001a2d1403": "", + "5ad141e1645df0001a2d1404": "", + "5ad141e1645df0001a2d1405": "it can be invoked between private non-state parties before its deadline for implementation", + "5ad141e1645df0001a2d1406": "", + "57269f3ef1498d1400e8e534": "national courts", + "57269f3ef1498d1400e8e535": "incorporations would only be nullified for a fixed list of reasons", + "57269f3ef1498d1400e8e536": "set up an insurance fund for employees to claim unpaid wages", + "57269f3ef1498d1400e8e537": "6 million Lira", + "5ad14337645df0001a2d145a": "", + "5ad14337645df0001a2d145b": "", + "5ad14337645df0001a2d145c": "", + "5ad14337645df0001a2d145d": "", + "5ad14337645df0001a2d145e": "", + "5726a00cf1498d1400e8e550": "European Court of Justice", + "5726a00cf1498d1400e8e551": "fundamental rights (see human rights), proportionality, legal certainty, equality before the law and subsidiarity", + "5ad14468645df0001a2d148a": "", + "5ad14468645df0001a2d148b": "", + "5ad14468645df0001a2d148c": "", + "5ad14468645df0001a2d148d": "", + "5726a09f708984140094cc39": "since the 1950s", + "5726a09f708984140094cc3a": "Article 5", + "5726a09f708984140094cc3b": "the least onerous", + "5ad14573645df0001a2d14b0": "", + "5ad14573645df0001a2d14b1": "", + "5ad14573645df0001a2d14b2": "", + "5ad14573645df0001a2d14b3": "", + "5ad14573645df0001a2d14b4": "", + "5726a14c708984140094cc51": "since the 1960s", + "5726a14c708984140094cc52": "international law and public law", + "5726a14c708984140094cc53": "a proper legal basis", + "5726a14c708984140094cc54": "the principles of legal certainty and good faith", + "5ad146c0645df0001a2d1504": "", + "5ad146c0645df0001a2d1505": "", + "5ad146c0645df0001a2d1506": "", + "5ad146c0645df0001a2d1507": "", + "5ad146c0645df0001a2d1508": "", + "5726a1e5dd62a815002e8b86": "the constitutional traditions common to the member states", + "5726a1e5dd62a815002e8b87": "fundamental rights recognised and protected in the constitutions of member states", + "5ad14816645df0001a2d1540": "", + "5ad14816645df0001a2d1541": "", + "5ad14816645df0001a2d1542": "", + "5ad14816645df0001a2d1543": "", + "5726a299dd62a815002e8b9e": "None", + "5726a299dd62a815002e8b9f": "member states", + "5726a299dd62a815002e8ba0": "1950", + "5726a299dd62a815002e8ba1": "European Court of Human Rights", + "5726a299dd62a815002e8ba2": "1999", + "5ad14966645df0001a2d1580": "None", + "5ad14966645df0001a2d1581": "", + "5ad14966645df0001a2d1582": "1950", + "5ad14966645df0001a2d1583": "", + "5ad14966645df0001a2d1584": "", + "5726a34bf1498d1400e8e59e": "2007", + "5726a34bf1498d1400e8e59f": "the Charter of Fundamental Rights of the European Union", + "5726a34bf1498d1400e8e5a0": "European Union law", + "5726a34bf1498d1400e8e5a1": "European Court of Justice", + "5ad14a28645df0001a2d159e": "", + "5ad14a28645df0001a2d159f": "", + "5ad14a28645df0001a2d15a0": "", + "5ad14a28645df0001a2d15a1": "", + "5ad14a28645df0001a2d15a2": "", + "5726a3c6f1498d1400e8e5ae": "Treaty of Amsterdam", + "5726a3c6f1498d1400e8e5af": "1997", + "5726a3c6f1498d1400e8e5b0": "1989", + "5726a3c6f1498d1400e8e5b1": "30", + "5726a3c6f1498d1400e8e5b2": "40", + "5ad14b2e645df0001a2d15ea": "", + "5ad14b2e645df0001a2d15eb": "", + "5ad14b2e645df0001a2d15ec": "", + "5ad14b2e645df0001a2d15ed": "", + "5ad14b2e645df0001a2d15ee": "", + "5726a46cdd62a815002e8bd0": "11", + "5726a46cdd62a815002e8bd1": "The UK", + "5726a46cdd62a815002e8bd2": "Social Chapter", + "5726a46cdd62a815002e8bd3": "1992", + "5ad14d8e645df0001a2d16b6": "", + "5ad14d8e645df0001a2d16b7": "", + "5ad14d8e645df0001a2d16b8": "", + "5ad14d8e645df0001a2d16b9": "", + "5ad14d8e645df0001a2d16ba": "", + "5726a5525951b619008f78dd": "the election of the UK Labour Party to government", + "5726a5525951b619008f78de": "1997", + "5726a5525951b619008f78df": "Works Council Directive", + "5726a5525951b619008f78e0": "1996", + "5726a5525951b619008f78e1": "workforce consultation in businesses", + "5ad14e86645df0001a2d16de": "", + "5ad14e86645df0001a2d16df": "", + "5ad14e86645df0001a2d16e0": "", + "5ad14e86645df0001a2d16e1": "", + "5ad14e86645df0001a2d16e2": "", + "5726a638dd62a815002e8bf6": "France, Italy, Belgium, the Netherlands, Luxembourg and Germany", + "5726a638dd62a815002e8bf7": "1951", + "5726a638dd62a815002e8bf8": "cartels", + "5726a638dd62a815002e8bf9": "Article 65 of the agreement banned cartels and article 66", + "5726a638dd62a815002e8bfa": "1957", + "5ad14f5a645df0001a2d1710": "", + "5ad14f5a645df0001a2d1711": "", + "5ad14f5a645df0001a2d1712": "", + "5ad14f5a645df0001a2d1713": "", + "5ad14f5a645df0001a2d1714": "", + "5726a7ecf1498d1400e8e654": "Article 101", + "5726a7ecf1498d1400e8e655": "abuse of dominant position", + "5726a7ecf1498d1400e8e656": "Articles 106 and 107", + "5726a7ecf1498d1400e8e657": "Article 102", + "5ad15059645df0001a2d1722": "", + "5ad15059645df0001a2d1723": "", + "5ad15059645df0001a2d1724": "", + "5ad15059645df0001a2d1725": "", + "5ad15059645df0001a2d1726": "", + "5726b58f5951b619008f7b55": "2007", + "5726b58f5951b619008f7b56": "since the Treaty of Rome 1957", + "5726b58f5951b619008f7b57": "consumer prices", + "5726b58f5951b619008f7b58": "free trade", + "5726b58f5951b619008f7b59": "the Court of Justice", + "5ad15170645df0001a2d1734": "", + "5ad15170645df0001a2d1735": "", + "5ad15170645df0001a2d1736": "", + "5ad15170645df0001a2d1737": "", + "5ad15170645df0001a2d1738": "", + "5726b718dd62a815002e8dbe": "a customs union", + "5726b718dd62a815002e8dbf": "parallel importers", + "5726b718dd62a815002e8dc0": "private actors", + "5726b718dd62a815002e8dc1": "Commission v", + "5726b718dd62a815002e8dc2": "protest", + "5ad15289645df0001a2d175a": "", + "5ad15289645df0001a2d175b": "", + "5ad15289645df0001a2d175c": "", + "5ad15289645df0001a2d175d": "", + "5ad15289645df0001a2d175e": "", + "5726b929f1498d1400e8e8e8": "25 per cent", + "5726b929f1498d1400e8e8e9": "France", + "5726b929f1498d1400e8e8ea": "2003", + "5726b929f1498d1400e8e8eb": "cocoa butter", + "5726b929f1498d1400e8e8ec": "motorcycles or mopeds pulling trailers", + "5ad153e9645df0001a2d1796": "", + "5ad153e9645df0001a2d1797": "Italian", + "5ad153e9645df0001a2d1798": "", + "5ad153e9645df0001a2d1799": "", + "5726ba2c708984140094cf59": "Keck and Mithouard", + "5726ba2c708984140094cf5a": "prevent cut throat competition", + "5726ba2c708984140094cf5b": "Konsumentombudsmannen v De Agostini", + "5726ba2c708984140094cf5c": "Unfair Commercial Practices Directive", + "5ad1556e645df0001a2d17da": "", + "5ad1556e645df0001a2d17db": "", + "5ad1556e645df0001a2d17dc": "", + "5ad1556e645df0001a2d17dd": "", + "5726baf2dd62a815002e8e74": "people to pursue their life goals in any country", + "5726baf2dd62a815002e8e75": "the European Community", + "5726baf2dd62a815002e8e76": "citizenship", + "5726baf2dd62a815002e8e77": "Steymann v Staatssecretaris van Justitie", + "5726baf2dd62a815002e8e78": "stay", + "5ad15676645df0001a2d17f6": "", + "5ad15676645df0001a2d17f7": "", + "5ad15676645df0001a2d17f8": "", + "5ad15676645df0001a2d17f9": "", + "5ad15676645df0001a2d17fa": "", + "5726bc1add62a815002e8ea6": "articles 1 to 7", + "5726bc1add62a815002e8ea7": "Jean-Marc Bosman", + "5726bc1add62a815002e8ea8": "Gaelic", + "5726bc1add62a815002e8ea9": "Hendrix v Employee Insurance Institute", + "5726bc1add62a815002e8eaa": "between 3 and 14 hours a week", + "5ad157cf645df0001a2d1814": "", + "5ad157cf645df0001a2d1815": "employment in the public service", + "5ad157cf645df0001a2d1816": "", + "5ad157cf645df0001a2d1817": "", + "5ad157cf645df0001a2d1818": "", + "5726bcde708984140094cfbf": "Citizenship of the EU", + "5726bcde708984140094cfc0": "the number of social services that people can access wherever they move", + "5726bcde708984140094cfc1": "Commission v Austria", + "5726bcde708984140094cfc2": "higher education", + "5ad158c0645df0001a2d1828": "", + "5ad158c0645df0001a2d1829": "", + "5ad158c0645df0001a2d182a": "Commission v Austria", + "5ad158c0645df0001a2d182b": "", + "5726c002708984140094d073": "Treaty on the Functioning of the European Union", + "5726c002708984140094d074": "non-discriminatory", + "5726c002708984140094d075": "Reyners v Belgium", + "5726c002708984140094d076": "49", + "5726c002708984140094d077": "Commission v Italy", + "5ad15a11645df0001a2d1856": "", + "5ad15a11645df0001a2d1857": "", + "5ad15a11645df0001a2d1858": "", + "5ad15a11645df0001a2d1859": "", + "5ad15a11645df0001a2d185a": "", + "5726c19add62a815002e8f8a": "2006", + "5726c19add62a815002e8f8b": "shipping toxic waste", + "5726c19add62a815002e8f8c": "", + "5726c19add62a815002e8f8d": "2005", + "5ad15d77645df0001a2d18c0": "", + "5ad15d77645df0001a2d18c1": "", + "5ad15d77645df0001a2d18c2": "", + "5ad15d77645df0001a2d18c3": "October 2007", + "5726c3da708984140094d0d9": "people who give services \"for remuneration", + "5726c3da708984140094d0da": "Dutch law said only people established in the Netherlands could give legal advice", + "5726c3da708984140094d0db": "narcotic drugs", + "5726c3da708984140094d0dc": "treatment", + "5ad15c52645df0001a2d18ac": "", + "5ad15c52645df0001a2d18ad": "Dutch law said only people established in the Netherlands", + "5ad15c52645df0001a2d18ae": "secondary education", + "5ad15c52645df0001a2d18af": "", + "5ad15c52645df0001a2d18b0": "activity", + "5726c5a9f1498d1400e8eac4": "the Daily Mail", + "5726c5a9f1498d1400e8eac5": "\u00a31", + "5726c5a9f1498d1400e8eac6": "", + "5726c5a9f1498d1400e8eac7": "creditor protection", + "5726c5a9f1498d1400e8eac8": "\u00dcberseering BV v Nordic Construction GmbH", + "5ad15b19645df0001a2d187e": "", + "5ad15b19645df0001a2d187f": "", + "5ad15b19645df0001a2d1880": "", + "5ad15b19645df0001a2d1881": "", + "5ad15b19645df0001a2d1882": "", + "5725b81b271a42140099d097": "Amazonia or the Amazon Jungle", + "5725b81b271a42140099d098": "5,500,000", + "5725b81b271a42140099d099": "nine", + "5725b81b271a42140099d09a": "four", + "5725b81b271a42140099d09b": "over half", + "5728349dff5b5019007d9efe": "Amazoneregenwoud", + "5728349dff5b5019007d9eff": "The Amazon rainforest", + "5728349dff5b5019007d9f00": "Brazil", + "5728349dff5b5019007d9f01": "over half", + "5728349dff5b5019007d9f02": "16,000", + "5729e2316aef0514001550c4": "moist broadleaf", + "5729e2316aef0514001550c5": "5,500,000", + "5729e2316aef0514001550c6": "nine", + "5729e2316aef0514001550c7": "Brazil", + "5729e2316aef0514001550c8": "390 billion", + "5a0c6698f5590b0018dab3e4": "", + "5a0c6698f5590b0018dab3e5": "", + "5a0c6698f5590b0018dab3e6": "", + "5a0c6698f5590b0018dab3e7": "", + "5a0c6698f5590b0018dab3e8": "", + "5725be0f271a42140099d117": "wetter", + "5725be0f271a42140099d118": "Climate fluctuations", + "5725be0f271a42140099d119": "Oligocene", + "5725be0f271a42140099d11a": "last glacial maximum", + "5725be0f271a42140099d11b": "the rainforest still managed to thrive", + "57283adcff5b5019007d9f94": "", + "57283adcff5b5019007d9f95": "45", + "57283adcff5b5019007d9f96": "Climate fluctuations", + "57283adcff5b5019007d9f97": "Oligocene", + "57283adcff5b5019007d9f98": "", + "5729e500af94a219006aa6b5": "Cretaceous\u2013Paleogene extinction event", + "5729e500af94a219006aa6b6": "66\u201334 Mya", + "5729e500af94a219006aa6b7": "Middle Miocene", + "5729e500af94a219006aa6b8": "", + "5729e500af94a219006aa6b9": "", + "5a0c677bf5590b0018dab3ee": "", + "5a0c677bf5590b0018dab3ef": "dinosaurs", + "5a0c677bf5590b0018dab3f0": "", + "5a0c677bf5590b0018dab3f1": "", + "5a0c677bf5590b0018dab3f2": "", + "5725c071271a42140099d127": "Purus Arch", + "5725c071271a42140099d128": "toward the Atlantic", + "5725c071271a42140099d129": "Solim\u00f5es Basin", + "5725c071271a42140099d12a": "5\u201310 million years", + "5725c071271a42140099d12b": "the Atlantic", + "57283d173acd2414000df78f": "mid-Eocene", + "57283d173acd2414000df790": "the Atlantic", + "57283d173acd2414000df791": "the Pacific", + "57283d173acd2414000df792": "Amazonas Basin", + "57283d173acd2414000df793": "Solim\u00f5es Basin", + "5729e6313f37b319004785a9": "mid-Eocene", + "5729e6313f37b319004785aa": "middle", + "5729e6313f37b319004785ab": "the Atlantic", + "5729e6313f37b319004785ac": "the Pacific", + "5729e6313f37b319004785ad": "Solim\u00f5es Basin", + "5a0c6a7ef5590b0018dab3f8": "", + "5a0c6a7ef5590b0018dab3f9": "", + "5a0c6a7ef5590b0018dab3fa": "Pacific", + "5a0c6a7ef5590b0018dab3fb": "", + "5a0c6a7ef5590b0018dab3fc": "", + "5725c41eec44d21400f3d50b": "Last Glacial Maximum", + "5725c41eec44d21400f3d50c": "rainfall in the basin during the LGM was lower than for the present", + "5725c41eec44d21400f3d50d": "the rainforest was reduced to small, isolated refugia separated by open forest and grassland", + "5725c41eec44d21400f3d50e": "difficult to resolve", + "5725c41eec44d21400f3d50f": "by the available data", + "572841772ca10214002da1a6": "21,000", + "572841772ca10214002da1a7": "Last Glacial Maximum (LGM) and subsequent deglaciation", + "572841772ca10214002da1a8": "sediment deposits from Amazon basin paleolakes and from the Amazon Fan", + "572841772ca10214002da1a9": "reduced moist tropical vegetation cover", + "572a0bfaaf94a219006aa779": "21,000", + "572a0bfaaf94a219006aa77a": "sediment", + "572a0bfaaf94a219006aa77b": "moist tropical", + "572a0bfaaf94a219006aa77c": "open forest and grassland", + "572a0bfaaf94a219006aa77d": "practical limitations of working in the rainforest", + "5a0c6c78f5590b0018dab402": "", + "5a0c6c78f5590b0018dab403": "", + "5a0c6c78f5590b0018dab404": "", + "5a0c6c78f5590b0018dab405": "rainforest", + "5725c63438643c19005acc9f": "CALIPSO", + "5725c63438643c19005acca0": "182 million", + "5725c63438643c19005acca1": "1,600", + "5725c63438643c19005acca2": "Amazon basin", + "5725c63438643c19005acca3": "132 million", + "5728455bff5b5019007da078": "CALIPSO satellite", + "5728455bff5b5019007da079": "182 million tons", + "5728455bff5b5019007da07a": "27.7 million tons", + "5728455bff5b5019007da07b": "", + "5728455bff5b5019007da07c": "43 million tons", + "5729ea263f37b319004785bd": "CALIPSO", + "5729ea263f37b319004785be": "NASA", + "5729ea263f37b319004785bf": "182 million tons", + "5729ea263f37b319004785c0": "1,600", + "5729ea263f37b319004785c1": "", + "5a0c6d26f5590b0018dab40a": "", + "5a0c6d26f5590b0018dab40b": "", + "5a0c6d26f5590b0018dab40c": "", + "5a0c6d26f5590b0018dab40d": "", + "5a0c6d26f5590b0018dab40e": "", + "5725c95f38643c19005accf3": "Amazonia: Man and Culture in a Counterfeit Paradise", + "5725c95f38643c19005accf4": "0.52/sq mi", + "5725c95f38643c19005accf5": "agriculture", + "5725c95f38643c19005accf6": "anthropological", + "5725c95f38643c19005accf7": "5 million", + "572847dd4b864d19001648bc": "the Amazon rainforest was only ever sparsely populated, as it was impossible to sustain a large population through agriculture", + "572847dd4b864d19001648bd": "", + "572847dd4b864d19001648be": "0.2", + "572847dd4b864d19001648bf": "Amazonia: Man and Culture", + "5729eb34af94a219006aa6c9": "", + "5729eb34af94a219006aa6ca": "", + "5729eb34af94a219006aa6cb": "0.2", + "5729eb34af94a219006aa6cc": "5 million", + "5729eb34af94a219006aa6cd": "200,000", + "5a0c77e3f5590b0018dab414": "", + "5a0c77e3f5590b0018dab415": "", + "5a0c77e3f5590b0018dab416": "", + "5a0c77e3f5590b0018dab417": "", + "5a0c77e3f5590b0018dab418": "", + "5725cbb289a1e219009abed2": "Francisco de Orellana", + "5725cbb289a1e219009abed3": "1540s", + "5725cbb289a1e219009abed4": "smallpox", + "5725cbb289a1e219009abed5": "between AD 0\u20131250", + "5725cbb289a1e219009abed6": "AD 0\u20131250", + "5729edd56aef051400155112": "Francisco de Orellana", + "5729edd56aef051400155113": "1542", + "5729edd56aef051400155114": "AD 0\u20131250", + "5729edd56aef051400155115": "Ondemar Dias", + "5729edd56aef051400155116": "11,000", + "5a0c7b88f5590b0018dab41e": "", + "5a0c7b88f5590b0018dab41f": "", + "5a0c7b88f5590b0018dab420": "", + "5a0c7b88f5590b0018dab421": "", + "5a0c7b88f5590b0018dab422": "", + "5725cf3238643c19005acd61": "black earth", + "5725cf3238643c19005acd62": "large areas", + "5725cf3238643c19005acd63": "agriculture and silviculture", + "5725cf3238643c19005acd64": "Xingu", + "5725cf3238643c19005acd65": "Michael Heckenberger and colleagues of the University of Florida", + "5729ef266aef05140015511c": "fertile", + "5729ef266aef05140015511d": "agriculture", + "5729ef266aef05140015511e": "Xingu", + "5729ef266aef05140015511f": "Michael Heckenberger and colleagues of the University of Florida", + "5729ef266aef051400155120": "roads, bridges and large plazas", + "5a0c7cb3f5590b0018dab428": "", + "5a0c7cb3f5590b0018dab429": "", + "5a0c7cb3f5590b0018dab42a": "", + "5a0c7cb3f5590b0018dab42b": "", + "5a0c7cb3f5590b0018dab42c": "", + "5725d16aec44d21400f3d61b": "2.5 million", + "5725d16aec44d21400f3d61c": "One in five", + "5725d16aec44d21400f3d61d": "40,000", + "5725d16aec44d21400f3d61e": "one in five", + "5725d16aec44d21400f3d61f": "128,843", + "5729f0db6aef051400155126": "2.5 million", + "5729f0db6aef051400155127": "427", + "5729f0db6aef051400155128": "40,000", + "5729f0db6aef051400155129": "378", + "5729f0db6aef05140015512a": "One in five", + "5a0c7d74f5590b0018dab432": "", + "5a0c7d74f5590b0018dab433": "", + "5a0c7d74f5590b0018dab434": "Brazil", + "5a0c7d74f5590b0018dab435": "one in five", + "5726722bdd62a815002e8528": "62", + "5726722bdd62a815002e8529": "16,000", + "5726722bdd62a815002e852a": "90,790", + "5726722bdd62a815002e852b": "356 \u00b1 47 tonnes per hectare", + "5726722bdd62a815002e852c": "438,000", + "5729f2646aef051400155130": "", + "5729f2646aef051400155131": "1,100", + "5729f2646aef051400155132": "90,790", + "5729f2646aef051400155133": "356 \u00b1 47 tonnes", + "5729f2646aef051400155134": "438,000", + "5a0c7edcf5590b0018dab43a": "", + "5a0c7edcf5590b0018dab43b": "", + "5a0c7edcf5590b0018dab43c": "90,790 tonnes", + "5a0c7edcf5590b0018dab43d": "", + "5a0c7edcf5590b0018dab43e": "", + "5729f3831d0469140077967b": "electric eels", + "5729f3831d0469140077967c": "black caiman", + "5729f3831d0469140077967d": "piranha", + "5729f3831d0469140077967e": "lipophilic alkaloid toxins", + "5729f3831d0469140077967f": "Vampire", + "5a0c7fb2f5590b0018dab444": "electric eels", + "5a0c7fb2f5590b0018dab445": "", + "5a0c7fb2f5590b0018dab446": "", + "5a0c7fb2f5590b0018dab447": "", + "5a0c7fb2f5590b0018dab448": "", + "5729fd56af94a219006aa72f": "", + "5729fd56af94a219006aa730": "1960s", + "5729fd56af94a219006aa731": "", + "5729fd56af94a219006aa732": "loss of soil fertility and weed invasion", + "5729fd56af94a219006aa733": "Deforestation", + "5a0c807ff5590b0018dab44e": "", + "5a0c807ff5590b0018dab44f": "", + "5a0c807ff5590b0018dab450": "", + "5a0c807ff5590b0018dab451": "", + "5a0c807ff5590b0018dab452": "outer space", + "5729feaf6aef051400155188": "415,000 to 587,000", + "5729feaf6aef051400155189": "587,000", + "5729feaf6aef05140015518a": "livestock pasture", + "5729feaf6aef05140015518b": "second-largest", + "5729feaf6aef05140015518c": "Seventy percent", + "5a0c817df5590b0018dab458": "", + "5a0c817df5590b0018dab459": "", + "5a0c817df5590b0018dab45a": "", + "5a0c817df5590b0018dab45b": "", + "572a005f1d046914007796b7": "soy", + "572a005f1d046914007796b8": "increased settlement and deforestation", + "572a005f1d046914007796b9": "8,646", + "572a005f1d046914007796ba": "18%", + "572a005f1d046914007796bb": "declined significantly", + "5a0c8ba8f5590b0018dab460": "", + "5a0c8ba8f5590b0018dab461": "", + "5a0c8ba8f5590b0018dab462": "", + "5a0c8ba8f5590b0018dab463": "2004 and 2014", + "5a0c8ba8f5590b0018dab464": "transportation projects", + "572a020f6aef051400155198": "biodiversity", + "572a020f6aef051400155199": "destruction of the forest", + "572a020f6aef05140015519a": "carbon", + "572a020f6aef05140015519b": "10%", + "572a020f6aef05140015519c": "1.1 \u00d7 1011", + "5a0c9275f5590b0018dab46a": "", + "5a0c9275f5590b0018dab46b": "", + "5a0c9275f5590b0018dab46c": "", + "5a0c9275f5590b0018dab46d": "", + "572a03a06aef0514001551aa": "severely reduced rainfall and increased temperatures", + "572a03a06aef0514001551ab": "greenhouse gas", + "572a03a06aef0514001551ac": "2100", + "572a03a06aef0514001551ad": "21st century", + "572a03a06aef0514001551ae": "deforestation", + "5a0c93b9f5590b0018dab472": "Amazon rainforest", + "5a0c93b9f5590b0018dab473": "rainforest cover", + "5a0c93b9f5590b0018dab474": "", + "5a0c93b9f5590b0018dab475": "", + "5a0c93b9f5590b0018dab476": "", + "572a064a3f37b3190047865d": "indigenous", + "572a064a3f37b3190047865e": "community-based", + "572a064a3f37b3190047865f": "deforestation and ecocide", + "572a064a3f37b31900478660": "Urarina", + "572a064a3f37b31900478661": "indigenous lowland South American peoples", + "5a0c958bf5590b0018dab47c": "", + "5a0c958bf5590b0018dab47d": "", + "5a0c958bf5590b0018dab47e": "", + "5a0c958bf5590b0018dab47f": "", + "5a0c958bf5590b0018dab480": "community-based", + "572a07c11d046914007796d5": "remote sensing", + "572a07c11d046914007796d6": "Trio Tribe", + "572a07c11d046914007796d7": "southern Suriname", + "572a07c11d046914007796d8": "map out their ancestral lands to help strengthen their territorial claims", + "572a07c11d046914007796d9": "to protect their tribal lands from commercial interests", + "5a0c96fbf5590b0018dab486": "conservation of the Amazon", + "5a0c96fbf5590b0018dab487": "", + "5a0c96fbf5590b0018dab488": "", + "5a0c96fbf5590b0018dab489": "territorial claims", + "5a0c96fbf5590b0018dab48a": "members of the Trio Tribe", + "572a09abaf94a219006aa75b": "tree growth", + "572a09abaf94a219006aa75c": "carbon related", + "572a09abaf94a219006aa75d": "Tatiana Kuplich", + "572a09abaf94a219006aa75e": "2006", + "572a09abaf94a219006aa75f": "Synthetic aperture", + "5a0c9832f5590b0018dab490": "", + "5a0c9832f5590b0018dab491": "", + "5a0c9832f5590b0018dab492": "Synthetic aperture", + "5a0c9832f5590b0018dab493": "Synthetic aperture radar (SAR) and Thematic Mapper", + "5a0c9832f5590b0018dab494": "", + "572a0b101d046914007796e9": "2005", + "572a0b101d046914007796ea": "The Independent reported Woods Hole Research Center", + "572a0b101d046914007796eb": "Brazilian National Institute of Amazonian Research", + "572a0b101d046914007796ec": "deforestation on regional climate", + "572a0b101d046914007796ed": "", + "5a0c98fef5590b0018dab49a": "2005", + "5a0c98fef5590b0018dab49b": "The Independent reported Woods Hole Research Center", + "5a0c98fef5590b0018dab49c": "a \"tipping point\"", + "5a0c98fef5590b0018dab49d": "", + "5a0c98fef5590b0018dab49e": "the forest", + "572a0bebaf94a219006aa76f": "2010", + "572a0bebaf94a219006aa770": "1,160,000", + "572a0bebaf94a219006aa771": "three", + "572a0bebaf94a219006aa772": "2005", + "572a0bebaf94a219006aa773": "1.5 gigatons", + "5a0c99fcf5590b0018dab4a4": "", + "5a0c99fcf5590b0018dab4a5": "1.5 gigatons", + "5a0c99fcf5590b0018dab4a6": "", + "5a0c99fcf5590b0018dab4a7": "", + "5a0c99fcf5590b0018dab4a8": "", + "5725c0f289a1e219009abdf2": "a phylum of animals that live in marine waters worldwide", + "5725c0f289a1e219009abdf3": "combs\u2019 \u2013 groups of cilia", + "5725c0f289a1e219009abdf4": "water flow through the body cavity", + "5725c0f289a1e219009abdf5": "a few millimeters to 1.5 m (4 ft 11 in)", + "5725c0f289a1e219009abdf6": "\u2018combs", + "57263eaa38643c19005ad371": "comb jellies", + "57263eaa38643c19005ad372": "1.5 m (4 ft 11 in)", + "57263eaa38643c19005ad373": "water flow", + "57263eaa38643c19005ad374": "comb", + "57263eaa38643c19005ad375": "marine waters worldwide", + "5a8349a2e60761001a2eb509": "", + "5a8349a2e60761001a2eb50a": "\u2018combs", + "5a8349a2e60761001a2eb50b": "swimming", + "5a8349a2e60761001a2eb50c": "separate phyla", + "5a8349a2e60761001a2eb50d": "", + "5725c337271a42140099d163": "100\u2013150", + "5725c337271a42140099d164": "tentilla", + "5725c337271a42140099d165": "ten times their own weight", + "5725c337271a42140099d166": "", + "5725c337271a42140099d167": "large, stiffened cilia", + "5726400589a1e219009ac5ee": "ten times their own weight", + "5726400589a1e219009ac5ef": "tentilla", + "5726400589a1e219009ac5f0": "large, stiffened cilia", + "5726400589a1e219009ac5f1": "sticky cells", + "5726400589a1e219009ac5f2": "", + "5a834af4e60761001a2eb51b": "", + "5a834af4e60761001a2eb51c": "", + "5a834af4e60761001a2eb51d": "", + "5a834af5e60761001a2eb51e": "25", + "5a834af5e60761001a2eb51f": "", + "5725c57a89a1e219009abe5e": "a single animal can produce both eggs and sperm", + "5725c57a89a1e219009abe5f": "produce both eggs and sperm", + "5725c57a89a1e219009abe60": "sequential hermaphrodites", + "5725c57a89a1e219009abe61": "platyctenids", + "5725c57a89a1e219009abe62": "", + "5726415bec44d21400f3dcd1": "a single animal can produce both eggs and sperm", + "5726415bec44d21400f3dcd2": "can produce both eggs and sperm", + "5726415bec44d21400f3dcd3": "the eggs and sperm mature at different times", + "5726415bec44d21400f3dcd4": "platyctenids", + "5726415bec44d21400f3dcd5": "beroids", + "5a834caae60761001a2eb539": "", + "5a834caae60761001a2eb53a": "", + "5a834caae60761001a2eb53b": "", + "5a834caae60761001a2eb53c": "reproduction", + "5a834caae60761001a2eb53d": "", + "5725c69738643c19005accb9": "other ctenophores", + "5725c69738643c19005accba": "Mnemiopsis", + "5725c69738643c19005accbb": "both fish larvae", + "5725c69738643c19005accbc": "bays", + "5726431d271a42140099d7f5": "bays", + "5726431d271a42140099d7f6": "planktonic plants", + "5726431d271a42140099d7f7": "Mnemiopsis", + "5726431d271a42140099d7f8": "", + "5726431d271a42140099d7f9": "over-fishing", + "5a834dbde60761001a2eb555": "", + "5a834dbde60761001a2eb556": "", + "5a834dbde60761001a2eb557": "", + "5a834dbde60761001a2eb558": "", + "5a834dbde60761001a2eb559": "", + "5725c91e38643c19005acceb": "66 million years ago", + "5725c91e38643c19005accec": "monophyletic", + "5725c91e38643c19005acced": "515 million years ago", + "5725c91e38643c19005accee": "", + "5726449f1125e71900ae1928": "515 million years ago", + "5726449f1125e71900ae1929": "Cretaceous\u2013Paleogene extinction", + "5726449f1125e71900ae192a": "monophyletic", + "5726449f1125e71900ae192b": "", + "5a8352ebe60761001a2eb57d": "early Cambrian", + "5a8352ebe60761001a2eb57e": "", + "5a8352ebe60761001a2eb57f": "", + "5a8352ebe60761001a2eb580": "", + "5a8352ebe60761001a2eb581": "", + "5725cb33271a42140099d1db": "cnidarians", + "5725cb33271a42140099d1dc": "having colloblasts", + "5725cb33271a42140099d1dd": "bilaterians", + "5725cb33271a42140099d1de": "Ctenophores", + "5725cb33271a42140099d1df": "colloblasts", + "572646655951b619008f6ebf": "cnidarians", + "572646655951b619008f6ec0": "colloblasts", + "572646655951b619008f6ec1": "colloblasts", + "572646655951b619008f6ec2": "ctenophores and cnidarians", + "572646655951b619008f6ec3": "bilaterians", + "5a835482e60761001a2eb597": "inter-cell connections", + "5a835482e60761001a2eb598": "sensory", + "5a835482e60761001a2eb599": "", + "5a835482e60761001a2eb59a": "", + "5a835482e60761001a2eb59b": "colloblasts", + "572647d0708984140094c14b": "mesoglea", + "572647d0708984140094c14c": "diploblastic", + "572647d0708984140094c14d": "ctenophores", + "572647d0708984140094c14e": "sponges", + "5a835778e60761001a2eb5d9": "", + "5a835778e60761001a2eb5da": "", + "5a835778e60761001a2eb5db": "", + "5a835778e60761001a2eb5dc": "", + "5a835778e60761001a2eb5dd": "", + "572648e8dd62a815002e8076": "cilia", + "572648e8dd62a815002e8077": "locomotion", + "572648e8dd62a815002e8078": "ctenes", + "572648e8dd62a815002e8079": "comb-bearing", + "5a8359c1e60761001a2eb5f3": "", + "5a8359c1e60761001a2eb5f4": "", + "5a8359c1e60761001a2eb5f5": "", + "5a8359c1e60761001a2eb5f6": "", + "5a8359c1e60761001a2eb5f7": "", + "57264a0ef1498d1400e8db40": "Pleurobrachia", + "57264a0ef1498d1400e8db41": "oceanic species", + "57264a0ef1498d1400e8db42": "to withstand waves and swirling sediment particles", + "57264a0ef1498d1400e8db43": "", + "5a835b42e60761001a2eb60d": "", + "5a835b42e60761001a2eb60e": "", + "5a835b42e60761001a2eb60f": "", + "5a835b42e60761001a2eb610": "", + "5a835b42e60761001a2eb611": "", + "57264b1ddd62a815002e80a0": "", + "57264b1ddd62a815002e80a1": "bioluminescence", + "57264b1ddd62a815002e80a2": "pharynx", + "57264b1ddd62a815002e80a3": "a system of internal canals", + "57264b1ddd62a815002e80a4": "the mouth and pharynx", + "5a836273e60761001a2eb63f": "", + "5a836273e60761001a2eb640": "", + "5a836273e60761001a2eb641": "", + "5a836273e60761001a2eb642": "", + "5a836273e60761001a2eb643": "", + "57264cfa708984140094c1c3": "swimming-plates", + "57264cfa708984140094c1c4": "ctenes\" or \"comb plates", + "57264cfa708984140094c1c5": "the extra compact filament is suspected to have a supporting function", + "57264cfa708984140094c1c6": "the direction in which the mouth is pointing", + "57264cfa708984140094c1c7": "2 millimeters", + "5a836496e60761001a2eb657": "", + "5a836496e60761001a2eb658": "", + "5a836496e60761001a2eb659": "", + "5a836496e60761001a2eb65a": "", + "5a836496e60761001a2eb65b": "", + "57264e66dd62a815002e811a": "", + "57264e66dd62a815002e811b": "mesoglea", + "57264e66dd62a815002e811c": "reduce its volume and increase its density", + "57264e66dd62a815002e811d": "", + "5a837038e60761001a2eb6f3": "", + "5a837038e60761001a2eb6f4": "", + "5a837038e60761001a2eb6f5": "", + "5a837038e60761001a2eb6f6": "", + "5a837038e60761001a2eb6f7": "to avoid sinking", + "572655e5f1498d1400e8dc5e": "aboral organ", + "572655e5f1498d1400e8dc5f": "at the opposite end from the mouth", + "572655e5f1498d1400e8dc60": "a transparent dome made of long, immobile cilia", + "572655e5f1498d1400e8dc61": "statocyst", + "572655e5f1498d1400e8dc62": "a balance sensor consisting of a statolith", + "5a8371dfe60761001a2eb725": "", + "5a8371dfe60761001a2eb726": "", + "5a8371dfe60761001a2eb727": "", + "5a8371dfe60761001a2eb728": "", + "5a8371dfe60761001a2eb729": "", + "57265746dd62a815002e8218": "sea gooseberry", + "57265746dd62a815002e8219": "a pair of long, slender tentacles", + "57265746dd62a815002e821a": "spherical", + "57265746dd62a815002e821b": "", + "57265746dd62a815002e821c": "at the narrow end", + "5a8373a7e60761001a2eb72f": "", + "5a8373a7e60761001a2eb730": "at the narrow end", + "5a8373a7e60761001a2eb731": "withdrawn", + "5a8373a7e60761001a2eb732": "wider", + "5a8373a7e60761001a2eb733": "", + "572658daf1498d1400e8dcac": "tentilla", + "572658daf1498d1400e8dcad": "specialized mushroom-shaped cells", + "572658daf1498d1400e8dcae": "they contain striated muscle", + "572658daf1498d1400e8dcaf": "three", + "572658daf1498d1400e8dcb0": "capturing prey", + "5a837549e60761001a2eb739": "", + "5a837549e60761001a2eb73a": "little tentacles", + "5a837549e60761001a2eb73b": "three", + "5a837549e60761001a2eb73c": "adhesive", + "5a837549e60761001a2eb73d": "", + "572659ea5951b619008f7051": "eight", + "572659ea5951b619008f7052": "near the mouth to the opposite end", + "572659ea5951b619008f7053": "evenly round the body", + "572659ea5951b619008f7054": "a ciliary groove", + "5a838553e60761001a2eb759": "", + "5a838553e60761001a2eb75a": "metachronal", + "5a838553e60761001a2eb75b": "evenly round the body", + "5a838553e60761001a2eb75c": "", + "5a838553e60761001a2eb75d": "", + "57265aaf5951b619008f706b": "lobes", + "57265aaf5951b619008f706c": "gelatinous projections edged with cilia that produce water currents that help direct microscopic prey toward the mouth", + "57265aaf5951b619008f706d": "four", + "57265aaf5951b619008f706e": "produce water currents that help direct microscopic prey toward the mouth", + "57265aaf5951b619008f706f": "suspended planktonic prey", + "5a838676e60761001a2eb763": "", + "5a838676e60761001a2eb764": "", + "5a838676e60761001a2eb765": "", + "5a838676e60761001a2eb766": "", + "5a838676e60761001a2eb767": "", + "57265c10f1498d1400e8dd36": "clapping their lobes", + "57265c10f1498d1400e8dd37": "the jet of expelled water drives them backwards very quickly", + "57265c10f1498d1400e8dd38": "nerves", + "57265c10f1498d1400e8dd39": "", + "5a83878de60761001a2eb777": "", + "5a83878de60761001a2eb778": "", + "5a83878de60761001a2eb779": "extensions", + "5a83878de60761001a2eb77a": "", + "5a83878de60761001a2eb77b": "", + "57265d86f1498d1400e8dd50": "Nuda", + "57265d86f1498d1400e8dd51": "The Beroida", + "57265d86f1498d1400e8dd52": "\"zip\" the mouth shut when the animal is not feeding", + "57265d86f1498d1400e8dd53": "", + "57265d86f1498d1400e8dd54": "large pharynx", + "5a83894de60761001a2eb789": "", + "5a83894de60761001a2eb78a": "", + "5a83894de60761001a2eb78b": "", + "5a83894de60761001a2eb78c": "", + "5a83894de60761001a2eb78d": "", + "57265e97708984140094c3c3": "Cestida", + "57265e97708984140094c3c4": "belt animals", + "57265e97708984140094c3c5": "by undulating their bodies as well as by the beating of their comb-rows", + "57265e97708984140094c3c6": "Cestum veneris", + "57265e97708984140094c3c7": "Velamen parallelum", + "5a838a2ee60761001a2eb793": "", + "5a838a2ee60761001a2eb794": "", + "5a838a2ee60761001a2eb795": "", + "5a838a2ee60761001a2eb796": "", + "5a838a2ee60761001a2eb797": "middle of opposite edges of the ribbon", + "572681c1dd62a815002e8796": "a pair of tentilla-bearing tentacles", + "572681c1dd62a815002e8797": "a muscular \"foot\"", + "572681c1dd62a815002e8798": "comb-rows", + "572681c1dd62a815002e8799": "rocks, algae, or the body surfaces of other invertebrates", + "5a838b42e60761001a2eb7a7": "", + "5a838b42e60761001a2eb7a8": "", + "5a838b42e60761001a2eb7a9": "", + "5a838b42e60761001a2eb7aa": "comb-rows", + "5a838b42e60761001a2eb7ab": "", + "572683075951b619008f7513": "via pores in the epidermis", + "572683075951b619008f7514": "internal fertilization and keep the eggs in brood chambers until they hatch", + "572683075951b619008f7515": "Mnemiopsis", + "572683075951b619008f7516": "in the parts of the internal canal network under the comb rows", + "572683075951b619008f7517": "external", + "5a838db9e60761001a2eb7b9": "", + "5a838db9e60761001a2eb7ba": "", + "5a838db9e60761001a2eb7bb": "", + "5a838db9e60761001a2eb7bc": "", + "5a838db9e60761001a2eb7bd": "", + "572684365951b619008f753f": "tentacles and tentacle sheaths", + "572684365951b619008f7540": "among the plankton", + "572684365951b619008f7541": "", + "572684365951b619008f7542": "true larvae", + "572684365951b619008f7543": "Beroe", + "5a838f74e60761001a2eb7cf": "", + "5a838f74e60761001a2eb7d0": "", + "5a838f74e60761001a2eb7d1": "lack tentacles and tentacle sheaths", + "5a838f74e60761001a2eb7d2": "plankton", + "5a838f74e60761001a2eb7d3": "plankton", + "572686fc708984140094c8e5": "they produce secretions (ink) that luminesce at much the same wavelengths as their bodies", + "572686fc708984140094c8e6": "When some species", + "572686fc708984140094c8e7": "ink", + "572686fc708984140094c8e8": "Juveniles", + "5a8391c7e60761001a2eb7d9": "", + "5a8391c7e60761001a2eb7da": "", + "5a8391c7e60761001a2eb7db": "", + "5a8391c7e60761001a2eb7dc": "", + "5a8391c7e60761001a2eb7dd": "", + "5726887e708984140094c917": "parasitic", + "5726887e708984140094c918": "jellyfish", + "5726887e708984140094c919": "incorporate their prey's nematocysts (stinging cells) into their own tentacles instead of colloblasts", + "5726887e708984140094c91a": "smaller, weaker swimmers", + "5726887e708984140094c91b": "Lampea", + "5a839654e60761001a2eb7f1": "", + "5a839654e60761001a2eb7f2": "", + "5a839654e60761001a2eb7f3": "", + "5a839654e60761001a2eb7f4": "", + "5a839654e60761001a2eb7f5": "strong swimmers such as adult copepods", + "57268a37f1498d1400e8e33c": "their low ratio of organic matter to salt and water", + "57268a37f1498d1400e8e33d": "keta", + "57268a37f1498d1400e8e33e": "other ctenophores", + "57268a37f1498d1400e8e33f": "the Red Sea", + "57268a37f1498d1400e8e340": "ctenophores", + "5a8397d0e60761001a2eb7fb": "", + "5a8397d0e60761001a2eb7fc": "", + "5a8397d0e60761001a2eb7fd": "", + "5a8397d0e60761001a2eb7fe": "", + "5a8397d0e60761001a2eb7ff": "", + "57268c01dd62a815002e8912": "Western Atlantic ctenophore Mnemiopsis leidyi", + "57268c01dd62a815002e8913": "via the ballast tanks of ships", + "57268c01dd62a815002e8914": "late 1980s", + "57268c01dd62a815002e8915": "by the accidental introduction of the Mnemiopsis-eating North American ctenophore Beroe ovata", + "57268c01dd62a815002e8916": "significantly slowed the animal's metabolism", + "5a8398bbe60761001a2eb805": "", + "5a8398bbe60761001a2eb806": "", + "5a8398bbe60761001a2eb807": "", + "5a8398bbe60761001a2eb808": "", + "5a8398bbe60761001a2eb809": "", + "57268da7f1498d1400e8e39c": "soft, gelatinous bodies", + "57268da7f1498d1400e8e39d": "a comb jelly", + "57268da7f1498d1400e8e39e": "mid-Cambrian period", + "57268da7f1498d1400e8e39f": "Three", + "57268da7f1498d1400e8e3a0": "tentacles", + "5a839ccfe60761001a2eb81f": "", + "5a839ccfe60761001a2eb820": "", + "5a839ccfe60761001a2eb821": "", + "5a839ccfe60761001a2eb822": "", + "5a839ccfe60761001a2eb823": "", + "57268f05dd62a815002e8990": "515 million years ago", + "57268f05dd62a815002e8991": "sessile frond-like fossil Stromatoveris", + "57268f05dd62a815002e8992": "Stromatoveris", + "57268f05dd62a815002e8993": "sessile", + "57268f05dd62a815002e8994": "Ediacaran period", + "5a83a59be60761001a2eb84b": "", + "5a83a59be60761001a2eb84c": "", + "5a83a59be60761001a2eb84d": "", + "5a83a59be60761001a2eb84e": "", + "5a83a59be60761001a2eb84f": "", + "57269016708984140094ca41": "the Bilateria", + "57269016708984140094ca42": "", + "5a83a80ae60761001a2eb855": "", + "5a83a80ae60761001a2eb856": "", + "5a83a80ae60761001a2eb857": "", + "5a83a80ae60761001a2eb858": "", + "5a83a80ae60761001a2eb859": "", + "572691bedd62a815002e89dc": "beroids", + "572691bedd62a815002e89dd": "monophyletic", + "572691bedd62a815002e89de": "65.5 million years ago", + "572691bedd62a815002e89df": "Richard Harbison", + "5a83acb4e60761001a2eb85f": "", + "5a83acb4e60761001a2eb860": "", + "5a83acb4e60761001a2eb861": "", + "5a83acb4e60761001a2eb862": "", + "5a83acb4e60761001a2eb863": "", + "5725ce4d38643c19005acd4d": "Fresno", + "5725ce4d38643c19005acd4e": "220 miles", + "5725ce4d38643c19005acd4f": "ash tree", + "5725ce4d38643c19005acd50": "an ash leaf", + "5725ce4d38643c19005acd51": "ash tree", + "5a7b054521c2de001afe9cce": "", + "5a7b054521c2de001afe9ccf": "", + "5a7b054521c2de001afe9cd0": "", + "5a7b054521c2de001afe9cd1": "", + "5a7b054521c2de001afe9cd2": "Sacramento", + "5725cfd0271a42140099d225": "1872", + "5725cfd0271a42140099d226": "the convenience of the railroad and worried about flooding", + "5725cfd0271a42140099d227": "1885", + "5725cfd0271a42140099d228": "47", + "5725cfd0271a42140099d229": "the Central Pacific Railroad", + "5a7b05cd21c2de001afe9cd8": "1872", + "5a7b05cd21c2de001afe9cd9": "", + "5a7b05cd21c2de001afe9cda": "", + "5a7b05cd21c2de001afe9cdb": "1931", + "5a7b05cd21c2de001afe9cdc": "the new community", + "5725d183271a42140099d23d": "2.7%", + "5725d183271a42140099d23e": "Chinatown", + "5725d183271a42140099d23f": "Pinedale", + "5725d183271a42140099d240": "Fresno Fairgrounds", + "5725d183271a42140099d241": "assembly center", + "5a7b064b21c2de001afe9ce2": "", + "5a7b064b21c2de001afe9ce3": "3.3%", + "5a7b064b21c2de001afe9ce4": "", + "5a7b064b21c2de001afe9ce5": "", + "5a7b064b21c2de001afe9ce6": "", + "5725d34aec44d21400f3d639": "BankAmericard", + "5725d34aec44d21400f3d63a": "BankAmericard", + "5725d34aec44d21400f3d63b": "revolve a balance", + "5725d34aec44d21400f3d63c": "1976", + "5725d34aec44d21400f3d63d": "Visa Inc", + "5a7b070121c2de001afe9cec": "", + "5a7b070121c2de001afe9ced": "", + "5a7b070121c2de001afe9cee": "", + "5a7b070121c2de001afe9cef": "1958", + "5a7b070121c2de001afe9cf0": "", + "5725d42a89a1e219009abf58": "Bill Aken", + "5725d42a89a1e219009abf59": "Bob Gallion", + "5725d42a89a1e219009abf5a": "", + "5725d42a89a1e219009abf5b": "", + "5725d42a89a1e219009abf5c": "", + "5a7b079b21c2de001afe9cf6": "", + "5a7b079b21c2de001afe9cf7": "Mexican", + "5a7b079b21c2de001afe9cf8": "", + "5a7b079b21c2de001afe9cf9": "", + "5a7b079b21c2de001afe9cfa": "Bill Aken", + "5725d662ec44d21400f3d687": "three", + "5725d662ec44d21400f3d688": "Roeding Park", + "5725d662ec44d21400f3d689": "Kearney Park", + "5725d662ec44d21400f3d68a": "Woodward Park", + "5725d662ec44d21400f3d68b": "Kearney Park", + "5a7b086921c2de001afe9d00": "", + "5a7b086921c2de001afe9d01": "", + "5a7b086921c2de001afe9d02": "", + "5a7b086921c2de001afe9d03": "", + "5a7b086921c2de001afe9d04": "southwest", + "5725d7e438643c19005acdf9": "1880s and World War II", + "5725d7e438643c19005acdfa": "Fresno County Courthouse", + "5725d7e438643c19005acdfb": "", + "5725d7e438643c19005acdfc": "Hughes Hotel", + "5a7b093b21c2de001afe9d0a": "1880s and World War II", + "5a7b093b21c2de001afe9d0b": "", + "5a7b093b21c2de001afe9d0c": "", + "5a7b093b21c2de001afe9d0d": "San Joaquin Light & Power Building", + "5a7b093b21c2de001afe9d0e": "San Joaquin Light & Power Building", + "5725daa8ec44d21400f3d6b3": "1964", + "5725daa8ec44d21400f3d6b4": "Fulton Mall", + "5725daa8ec44d21400f3d6b5": "Pierre-Auguste Renoir", + "5725daa8ec44d21400f3d6b6": "near their current locations", + "5725daa8ec44d21400f3d6b7": "wide sidewalks", + "5a7b0e2221c2de001afe9d14": "1964", + "5a7b0e2221c2de001afe9d15": "", + "5a7b0e2221c2de001afe9d16": "Fulton Mall", + "5a7b0e2221c2de001afe9d17": "", + "5a7b0e2221c2de001afe9d18": "east", + "5725db98ec44d21400f3d6c5": "Fresno's far southeast side", + "5725db98ec44d21400f3d6c6": "Kings Canyon Avenue and Clovis Avenue", + "5725db98ec44d21400f3d6c7": "1950s", + "5725db98ec44d21400f3d6c8": "Fresno", + "5725db98ec44d21400f3d6c9": "William P. Bell", + "5a7b0ec521c2de001afe9d1e": "William P. Bell", + "5a7b0ec521c2de001afe9d1f": "", + "5a7b0ec521c2de001afe9d20": "Chestnut Avenue", + "5a7b0ec521c2de001afe9d21": "", + "5a7b0ec521c2de001afe9d22": "", + "5725dd7d89a1e219009abfea": "Tower Theatre", + "5725dd7d89a1e219009abfeb": "1939", + "5725dd7d89a1e219009abfec": "water tower", + "5725dd7d89a1e219009abfed": "Fresno Normal School", + "5725dd7d89a1e219009abfee": "one-half mile south", + "5a7b0fae21c2de001afe9d28": "", + "5a7b0fae21c2de001afe9d29": "", + "5a7b0fae21c2de001afe9d2a": "", + "5a7b0fae21c2de001afe9d2b": "", + "5a7b0fae21c2de001afe9d2c": "", + "5725e1c4271a42140099d2d7": "late 1970s", + "5725e1c4271a42140099d2d8": "second and third run movies, along with classic films", + "5725e1c4271a42140099d2d9": "1978", + "5725e1c4271a42140099d2da": "Fresno", + "5725e1c4271a42140099d2db": "Evita and The Wiz", + "5a7b103b21c2de001afe9d32": "", + "5a7b103b21c2de001afe9d33": "", + "5a7b103b21c2de001afe9d34": "", + "5a7b103b21c2de001afe9d35": "", + "5a7b103b21c2de001afe9d36": "Roger Rocka", + "5725e45689a1e219009ac048": "live theater", + "5725e45689a1e219009ac049": "a few hundred feet", + "5725e45689a1e219009ac04a": "the Tower District", + "5725e45689a1e219009ac04b": "the Tower District", + "5725e45689a1e219009ac04c": "Tower District", + "5a7b10e021c2de001afe9d3c": "", + "5a7b10e021c2de001afe9d3d": "", + "5a7b10e021c2de001afe9d3e": "", + "5a7b10e021c2de001afe9d3f": "", + "5725e748ec44d21400f3d733": "early twentieth century homes", + "5725e748ec44d21400f3d734": "Storybook houses", + "5725e748ec44d21400f3d735": "contrasts", + "5725e748ec44d21400f3d736": "recent decades", + "5a7b11bb21c2de001afe9d44": "", + "5a7b11bb21c2de001afe9d45": "", + "5a7b11bb21c2de001afe9d46": "", + "5a7b11bb21c2de001afe9d47": "north and east", + "5a7b11bb21c2de001afe9d48": "", + "5725ec8289a1e219009ac0ae": "Huntington Boulevard", + "5725ec8289a1e219009ac0af": "William Stranahan", + "5725ec8289a1e219009ac0b0": "1914", + "5725ec8289a1e219009ac0b1": "267", + "5725ec8289a1e219009ac0b2": "Fresno Traction Company", + "5a7b12a421c2de001afe9d4e": "", + "5a7b12a421c2de001afe9d4f": "", + "5a7b12a421c2de001afe9d50": "", + "5a7b12a421c2de001afe9d51": "Fresno Traction Company", + "5a7b12a421c2de001afe9d52": "", + "5725edfe38643c19005ace9f": "Southwest Fresno", + "5725edfe38643c19005acea0": "southwest", + "5725edfe38643c19005acea1": "African-American", + "5725edfe38643c19005acea2": "Hmong or Laotian", + "5725edfe38643c19005acea3": "", + "5a7b325021c2de001afe9da8": "41 freeway", + "5a7b325021c2de001afe9da9": "99 freeway", + "5a7b325021c2de001afe9daa": "", + "5a7b325021c2de001afe9dab": "", + "5a7b325021c2de001afe9dac": "", + "5725f00938643c19005aced7": "M. Theo Kearney", + "5725f00938643c19005aced8": "palm trees", + "5725f00938643c19005aced9": "Fresno Street and Thorne Ave", + "5725f00938643c19005aceda": "Brookhaven", + "5725f00938643c19005acedb": "", + "5a7b32e621c2de001afe9db2": "", + "5a7b32e621c2de001afe9db3": "20 mi", + "5a7b32e621c2de001afe9db4": "", + "5a7b32e621c2de001afe9db5": "", + "5a7b32e621c2de001afe9db6": "", + "5725f190ec44d21400f3d76f": "between the 1960s and 1990s", + "5725f190ec44d21400f3d770": "Fresno and B streets", + "5725f190ec44d21400f3d771": "Cargill Meat Solutions and Foster Farms", + "5725f190ec44d21400f3d772": "on the West Side", + "5725f190ec44d21400f3d773": "very little", + "5a7b33b821c2de001afe9dbc": "Fresno Housing Authority", + "5a7b33b821c2de001afe9dbd": "Fresno and B streets", + "5a7b33b821c2de001afe9dbe": "", + "5a7b33b821c2de001afe9dbf": "stench", + "5a7b33b821c2de001afe9dc0": "late 1990s", + "5725f2c838643c19005aceed": "Ralph Woodward", + "5725f2c838643c19005aceee": "300", + "5725f2c838643c19005aceef": "2,500 people", + "5725f2c838643c19005acef0": "22", + "5725f2c838643c19005acef1": "April through October, 6am to 10pm and November through March, 6am to 7pm", + "5a7b34fa21c2de001afe9dc6": "1968", + "5a7b34fa21c2de001afe9dc7": "300 acres", + "5a7b34fa21c2de001afe9dc8": "", + "5a7b34fa21c2de001afe9dc9": "2,500", + "5a7b34fa21c2de001afe9dca": "April through October", + "5725f46289a1e219009ac0fa": "1946", + "5725f46289a1e219009ac0fb": "William Smilie", + "5725f46289a1e219009ac0fc": "Sierra Sky Park", + "5725f46289a1e219009ac0fd": "automobiles", + "5725f46289a1e219009ac0fe": "there are now numerous such communities across the United States and around the world", + "5a7b359f21c2de001afe9dd0": "", + "5a7b359f21c2de001afe9dd1": "", + "5a7b359f21c2de001afe9dd2": "", + "5a7b359f21c2de001afe9dd3": "", + "5a7b359f21c2de001afe9dd4": "", + "5725f5b1271a42140099d371": "hot and dry", + "5725f5b1271a42140099d372": "July", + "5725f5b1271a42140099d373": "11.5 inches", + "5725f5b1271a42140099d374": "northwest", + "5725f5b1271a42140099d375": "December, January and February", + "5a7b37ce21c2de001afe9dda": "three or four", + "5a7b37ce21c2de001afe9ddb": "", + "5a7b37ce21c2de001afe9ddc": "southeastern", + "5a7b37ce21c2de001afe9ddd": "83.0 \u00b0F (28.3 \u00b0C)", + "5a7b37ce21c2de001afe9dde": "", + "5725f6e138643c19005acf19": "115 \u00b0F", + "5725f6e138643c19005acf1a": "January 6, 1913", + "5725f6e138643c19005acf1b": "1885", + "5725f6e138643c19005acf1c": "2.2 inches", + "5725f6e138643c19005acf1d": "3.55 inches", + "5a7b3b3121c2de001afe9dee": "", + "5a7b3b3121c2de001afe9def": "", + "5a7b3b3121c2de001afe9df0": "", + "5a7b3b3121c2de001afe9df1": "", + "5a7b3b3121c2de001afe9df2": "2.2 inches", + "5725f7cd38643c19005acf23": "494,665", + "5725f7cd38643c19005acf24": "", + "5725f7cd38643c19005acf25": "8,525", + "5725f7cd38643c19005acf26": "30.0%", + "5725f7cd38643c19005acf27": "4,404.5", + "5a7b3dd921c2de001afe9df8": "494,665", + "5a7b3dd921c2de001afe9df9": "8,525", + "5a7b3dd921c2de001afe9dfa": "1.2%", + "5a7b3dd921c2de001afe9dfb": "", + "5a7b3dd921c2de001afe9dfc": "72.6%", + "5725f8f5ec44d21400f3d7b1": "68,511", + "5725f8f5ec44d21400f3d7b2": "19.3%", + "5725f8f5ec44d21400f3d7b3": "1,388", + "5725f8f5ec44d21400f3d7b4": "3.62", + "5725f8f5ec44d21400f3d7b5": "3.07", + "5a7b3f0f21c2de001afe9e02": "43.3%", + "5a7b3f0f21c2de001afe9e03": "3.62", + "5a7b3f0f21c2de001afe9e04": "12,843", + "5a7b3f0f21c2de001afe9e05": "", + "5a7b3f0f21c2de001afe9e06": "12,344", + "5725fabc89a1e219009ac128": "427,652", + "5725fabc89a1e219009ac129": "149,025", + "5725fabc89a1e219009ac12a": "8.4%", + "5725fabc89a1e219009ac12b": "a third", + "5725fabc89a1e219009ac12c": "4,097.9 people per square mile", + "5a7b402121c2de001afe9e0c": "", + "5a7b402121c2de001afe9e0d": "97,915", + "5a7b402121c2de001afe9e0e": "39.9%", + "5a7b402121c2de001afe9e0f": "about a third", + "5a7b402121c2de001afe9e10": "about a third", + "5725fb8138643c19005acf3f": "To avoid interference with existing VHF television stations in the San Francisco Bay Area", + "5725fb8138643c19005acf40": "KMJ-TV", + "5725fb8138643c19005acf41": "June 1, 1953", + "5725fb8138643c19005acf42": "NBC affiliate KSEE", + "5725fb8138643c19005acf43": "KGPE", + "5a7b409721c2de001afe9e16": "", + "5a7b409721c2de001afe9e17": "", + "5a7b409721c2de001afe9e18": "", + "5a7b409721c2de001afe9e19": "NBC affiliate KSEE", + "5a7b409721c2de001afe9e1a": "KMPH", + "5725fcbe271a42140099d3ad": "State Route 99", + "5725fcbe271a42140099d3ae": "Sierra Freeway", + "5725fcbe271a42140099d3af": "Eisenhower Freeway", + "5725fcbe271a42140099d3b0": "west", + "5a7b44ae21c2de001afe9e20": "", + "5a7b44ae21c2de001afe9e21": "Clovis and Huntington Lake", + "5a7b44ae21c2de001afe9e22": "", + "5a7b44ae21c2de001afe9e23": "", + "5a7b44ae21c2de001afe9e24": "", + "5725fe63ec44d21400f3d7dd": "Fresno", + "5725fe63ec44d21400f3d7de": "1950s", + "5725fe63ec44d21400f3d7df": "Interstate 9", + "5725fe63ec44d21400f3d7e0": "rapidly raising population and traffic in cities along SR 99, as well as the desirability of Federal funding", + "5a7b456121c2de001afe9e2a": "", + "5a7b456121c2de001afe9e2b": "", + "5a7b456121c2de001afe9e2c": "", + "5a7b456121c2de001afe9e2d": "", + "5a7b456121c2de001afe9e2e": "", + "5725ff8238643c19005acf49": "Amtrak San Joaquins", + "5725ff8238643c19005acf4a": "Downtown Fresno", + "5725ff8238643c19005acf4b": "Burlington Northern Santa Fe Railway and Union Pacific Railroad", + "5725ff8238643c19005acf4c": "San Joaquin Valley Railroad", + "5725ff8238643c19005acf4d": "Fresno", + "5a7b485921c2de001afe9e52": "", + "5a7b485921c2de001afe9e53": "", + "5a7b485921c2de001afe9e54": "", + "5a7b485921c2de001afe9e55": "", + "5a7b485921c2de001afe9e56": "", + "5725d34089a1e219009abf50": "Distributed Adaptive Message Block Switching", + "5725d34089a1e219009abf51": "to provide a fault-tolerant, efficient routing method for telecommunication messages", + "5725d34089a1e219009abf52": "the theretofore established principles of pre-allocation of network bandwidth", + "5725d34089a1e219009abf53": "coining the modern name packet switching", + "572632ceec44d21400f3dc2f": "Distributed Adaptive Message Block Switching", + "572632ceec44d21400f3dc30": "to provide a fault-tolerant, efficient routing method for telecommunication messages", + "572632ceec44d21400f3dc31": "Donald Davies", + "5a5504e1134fea001a0e17f8": "Distributed Adaptive Message Block Switching", + "5a5504e1134fea001a0e17f9": "provide a fault-tolerant, efficient routing method for telecommunication messages", + "5a5504e1134fea001a0e17fa": "", + "5a5504e1134fea001a0e17fb": "", + "5a5504e1134fea001a0e17fc": "", + "5a5645196349e2001acdccfc": "", + "5a5645196349e2001acdccfd": "", + "5a5645196349e2001acdccfe": "", + "5a5645196349e2001acdccff": "", + "5a5645196349e2001acdcd00": "", + "5a605197eae51e001ab14d0b": "", + "5a605197eae51e001ab14d0c": "funded by the US Department of Defense", + "5a605197eae51e001ab14d0d": "", + "5a605197eae51e001ab14d0e": "", + "5a605197eae51e001ab14d0f": "", + "5a667457846392001a1e1c2d": "", + "5a667457846392001a1e1c2e": "", + "5a667457846392001a1e1c2f": "", + "5a667457846392001a1e1c30": "", + "5a667457846392001a1e1c31": "development of telecommunications in the Bell System", + "5725d52f89a1e219009abf78": "circuit switching", + "5725d52f89a1e219009abf79": "a fee per unit of connection time", + "5725d52f89a1e219009abf7a": "packet switching may be characterized by a fee per unit of information transmitted", + "572634a789a1e219009ac56c": "circuit switching, a method which pre-allocates dedicated network bandwidth specifically for each communication session", + "572634a789a1e219009ac56d": "each having a constant bit rate and latency between nodes", + "572634a789a1e219009ac56e": "circuit switching is characterized by a fee per unit of connection time", + "572634a789a1e219009ac56f": "a fee per unit of information transmitted", + "5a55068b134fea001a0e180c": "a method which pre-allocates dedicated network bandwidth specifically for each communication session", + "5a55068b134fea001a0e180d": "", + "5a55068b134fea001a0e180e": "fee per unit", + "5a55068b134fea001a0e180f": "", + "5a55068b134fea001a0e1810": "", + "5a56496b6349e2001acdcd06": "", + "5a56496b6349e2001acdcd07": "constant", + "5a56496b6349e2001acdcd08": "fee per unit of information transmitted", + "5a56496b6349e2001acdcd09": "", + "5a56496b6349e2001acdcd0a": "", + "5a60556eeae51e001ab14d15": "", + "5a60556eeae51e001ab14d16": "", + "5a60556eeae51e001ab14d17": "", + "5a60556eeae51e001ab14d18": "", + "5a667761846392001a1e1c37": "", + "5a667761846392001a1e1c38": "", + "5a667761846392001a1e1c39": "", + "5a667761846392001a1e1c3a": "each having a constant bit rate and latency between nodes", + "5726219489a1e219009ac2d0": "the packets may be delivered according to a multiple access scheme", + "5726356938643c19005ad2ff": "Packet mode communication may be implemented with or without intermediate forwarding nodes", + "5726356938643c19005ad300": "Packets are normally forwarded by intermediate network nodes asynchronously using first-in, first-out buffering", + "5726356938643c19005ad301": "the packets may be delivered according to a multiple access scheme", + "5a5507df134fea001a0e181e": "Packet mode", + "5a5507df134fea001a0e181f": "multiple access scheme", + "5a5507df134fea001a0e1820": "shared physical medium", + "5a5507df134fea001a0e1821": "packet switches or routers", + "5a5507df134fea001a0e1822": "according to a multiple access scheme", + "5a564b1e6349e2001acdcd10": "", + "5a564b1e6349e2001acdcd11": "", + "5a564b1e6349e2001acdcd12": "", + "5a564b1e6349e2001acdcd13": "", + "5a564b1e6349e2001acdcd14": "", + "5a6057f0eae51e001ab14d1d": "", + "5a6057f0eae51e001ab14d1e": "may be forwarded according to some scheduling discipline", + "5a6057f0eae51e001ab14d1f": "", + "5a6057f0eae51e001ab14d20": "guaranteed quality of service", + "5a6057f0eae51e001ab14d21": "", + "5a66797c846392001a1e1c49": "", + "5a66797c846392001a1e1c4a": "using first-in, first-out buffering", + "5a66797c846392001a1e1c4b": "", + "5a66797c846392001a1e1c4c": "", + "5a66797c846392001a1e1c4d": "", + "5726249538643c19005ad07f": "distributed adaptive message block switching", + "5726249538643c19005ad080": "", + "5726249538643c19005ad081": "use of a decentralized network with multiple paths between any two points", + "5726249538643c19005ad082": "by store and forward switching", + "57263677ec44d21400f3dc49": "distributed adaptive message block switching", + "57263677ec44d21400f3dc4a": "Report P-2626 described a general architecture for a large-scale, distributed, survivable communications network", + "57263677ec44d21400f3dc4b": "The work focuses on three key ideas: use of a decentralized network with multiple paths between any two points", + "57263677ec44d21400f3dc4c": "store and forward switching", + "5a5508f5134fea001a0e1828": "", + "5a5508f5134fea001a0e1829": "", + "5a5508f5134fea001a0e182a": "three", + "5a5508f5134fea001a0e182b": "", + "5a5508f5134fea001a0e182c": "", + "5a564c956349e2001acdcd1a": "Baran", + "5a564c956349e2001acdcd1b": "", + "5a564c956349e2001acdcd1c": "", + "5a564c956349e2001acdcd1d": "", + "5a564c956349e2001acdcd1e": "", + "5a6059ace9e1cc001a33cd34": "", + "5a6059ace9e1cc001a33cd35": "", + "5a6059ace9e1cc001a33cd36": "", + "5a6059ace9e1cc001a33cd37": "", + "5a6059ace9e1cc001a33cd38": "", + "5a667dae846392001a1e1c53": "", + "5a667dae846392001a1e1c54": "by store and forward switching", + "5a667dae846392001a1e1c55": "", + "5a667dae846392001a1e1c56": "distributed adaptive message block switching", + "5a667dae846392001a1e1c57": "decentralized network with multiple paths between any two points", + "572629c6271a42140099d6a3": "Starting in 1965, Donald Davies at the National Physical Laboratory, UK, independently developed the same message routing methodology", + "572629c6271a42140099d6a4": "packet switching", + "572629c6271a42140099d6a5": "a nationwide network in the UK", + "572629c6271a42140099d6a6": "suggested it for use in the ARPANET", + "5726378238643c19005ad313": "Donald Davies", + "5726378238643c19005ad314": "packet switching", + "5726378238643c19005ad315": "suggested it for use in the ARPANET", + "5a5509e8134fea001a0e183a": "", + "5a5509e8134fea001a0e183c": "", + "5a5509e8134fea001a0e183d": "", + "5a5509e8134fea001a0e183e": "Baran's work", + "5a605b5ee9e1cc001a33cd3e": "Starting in 1965, Donald Davies at the National Physical Laboratory, UK, independently developed the same message routing methodology as developed by Baran.", + "5a605b5ee9e1cc001a33cd3f": "Starting in 1965, Donald Davies at the National Physical Laboratory, UK, independently", + "5a605b5ee9e1cc001a33cd40": "", + "5a605b5ee9e1cc001a33cd41": "Starting in 1965, Donald Davies at the National Physical Laboratory, UK, independently", + "5a605b5ee9e1cc001a33cd42": "", + "5a667f50846392001a1e1c67": "", + "5a667f50846392001a1e1c68": "the ARPANET", + "5a667f50846392001a1e1c69": "", + "5a667f50846392001a1e1c6a": "", + "5a667f50846392001a1e1c6b": "", + "5726385e271a42140099d797": "", + "5726385e271a42140099d798": "The packets are routed individually, sometimes resulting in different paths and out-of-order delivery", + "5726385e271a42140099d799": "Each packet is labeled with a destination address, source address, and port numbers", + "5726385e271a42140099d79a": "the original message/data is reassembled in the correct order, based on the packet sequence number", + "5a550b52134fea001a0e1844": "packets are routed individually", + "5a550b52134fea001a0e1845": "sequence number of the packet", + "5a550b52134fea001a0e1846": "", + "5a550b52134fea001a0e1847": "At the destination", + "5a550b52134fea001a0e1848": "a virtual circuit or byte stream", + "5a605cdce9e1cc001a33cd48": "", + "5a605cdce9e1cc001a33cd49": "via different routes", + "5a605cdce9e1cc001a33cd4a": "Each packet is dispatched and may go via different routes", + "5a605cdce9e1cc001a33cd4c": "Each packet is dispatched", + "5a668172f038b7001ab0bef8": "", + "5a668172f038b7001ab0bef9": "", + "5a668172f038b7001ab0befa": "to help the packet find its way to its destination", + "5a668172f038b7001ab0befb": "", + "5726398589a1e219009ac588": "Connection-oriented transmission requires a setup phase in each involved node before any packet is transferred to establish the parameters of communication", + "5726398589a1e219009ac589": "The packets include a connection identifier rather than address information", + "5726398589a1e219009ac58a": "", + "5726398589a1e219009ac58b": "The packet header can be small", + "5a550c52134fea001a0e1856": "when the route to the destination is discovered and an entry is added to the switching table in each network node through which the connection passes", + "5a550c52134fea001a0e1857": "", + "5a550c52134fea001a0e1858": "", + "5a550c52134fea001a0e1859": "", + "5a550c52134fea001a0e185a": "", + "5a605eaae9e1cc001a33cd52": "", + "5a605eaae9e1cc001a33cd53": "", + "5a605eaae9e1cc001a33cd54": "", + "5a605eaae9e1cc001a33cd55": "Address information is only transferred to each node during the connection set-up phase", + "5a605eaae9e1cc001a33cd56": "", + "5a66850bf038b7001ab0bf3c": "", + "5a66850bf038b7001ab0bf3d": "", + "5a66850bf038b7001ab0bf3e": "", + "5a66850bf038b7001ab0bf3f": "", + "57263b1638643c19005ad333": "a handshake between the communicating parties before any user packets are transmitted", + "57263b1638643c19005ad334": "connection-oriented operations", + "57263b1638643c19005ad335": "Internet Protocol", + "57263b1638643c19005ad336": "A typical configuration is to run IP over ATM or a version of MPLS", + "5a550e6f134fea001a0e187e": "connection-oriented operations", + "5a550e6f134fea001a0e187f": "", + "5a550e6f134fea001a0e1880": "", + "5a550e6f134fea001a0e1881": "the lower three layers of the OSI Model", + "5a550e6f134fea001a0e1882": "the UNI", + "5a668682f038b7001ab0bf4e": "", + "5a668682f038b7001ab0bf4f": "conventional HDLC-type link management procedures", + "5a668682f038b7001ab0bf50": "", + "5a668682f038b7001ab0bf51": "1980s and early 1990s", + "5a668682f038b7001ab0bf52": "", + "57263c78ec44d21400f3dc7b": "", + "57263c78ec44d21400f3dc7c": "", + "57263c78ec44d21400f3dc7d": "", + "57263c78ec44d21400f3dc7e": "The X.25 protocol suite", + "5a550f98134fea001a0e189c": "twenty", + "5a550f98134fea001a0e189d": "", + "5a550f98134fea001a0e189e": "", + "5a550f98134fea001a0e189f": "", + "5a550f98134fea001a0e18a0": "", + "5a6688fcf038b7001ab0bf6c": "", + "5a6688fcf038b7001ab0bf6d": "", + "5a6688fcf038b7001ab0bf6e": "", + "5a6688fcf038b7001ab0bf6f": "", + "57263cfcec44d21400f3dc8d": "AppleTalk was a proprietary suite of networking protocols", + "57263cfcec44d21400f3dc8e": "AppleTalk included features that allowed local area networks to be established ad hoc without the requirement for a centralized router or server", + "57263cfcec44d21400f3dc8f": "", + "57263cfcec44d21400f3dc90": "plug-n-play system", + "5a55106f134fea001a0e18ae": "AppleTalk", + "5a55106f134fea001a0e18af": "", + "5a55106f134fea001a0e18b0": "The AppleTalk system automatically assigned addresses, updated the distributed namespace, and configured any required inter-network routing", + "5a55106f134fea001a0e18b1": "", + "5a55106f134fea001a0e18b2": "It was the primary protocol used by Apple devices through the 1980s and 90s", + "5a668b1df038b7001ab0bf88": "", + "5a668b1df038b7001ab0bf89": "", + "5a668b1df038b7001ab0bf8a": "plug-n-play", + "5a668b1df038b7001ab0bf8b": "AppleTalk", + "57263dcd89a1e219009ac5a2": "", + "57263dcd89a1e219009ac5a3": "The CYCLADES packet switching network", + "57263dcd89a1e219009ac5a4": "It was the first network to make the hosts responsible for reliable delivery of data", + "57263dcd89a1e219009ac5a5": "ARPANET architecture", + "5a55114d134fea001a0e18c2": "The CYCLADES packet switching network", + "5a55114d134fea001a0e18c3": "It was the first network to make the hosts responsible for reliable delivery of data", + "5a55114d134fea001a0e18c4": "", + "5a55114d134fea001a0e18c5": "", + "5a55114d134fea001a0e18c6": "alternatives to the early ARPANET design", + "5a668c1af038b7001ab0bfa4": "", + "5a668c1af038b7001ab0bfa5": "", + "5a668c1af038b7001ab0bfa6": "", + "5a668c1af038b7001ab0bfa7": "unreliable datagrams and associated end-to-end protocol mechanisms", + "57263ea0271a42140099d7c3": "a suite of network protocols created by Digital Equipment Corporation, originally released in 1975 in order to connect two PDP-11 minicomputers", + "57263ea0271a42140099d7c4": "to connect two PDP-11 minicomputers", + "57263ea0271a42140099d7c5": "", + "57263ea0271a42140099d7c6": "open standards with published specifications", + "5a551230134fea001a0e18cc": "", + "5a551230134fea001a0e18cd": "", + "5a551230134fea001a0e18ce": "", + "5a551230134fea001a0e18cf": "network protocols", + "5a551230134fea001a0e18d0": "", + "5a668d25f038b7001ab0bfac": "", + "5a668d25f038b7001ab0bfad": "", + "5a668d25f038b7001ab0bfae": "", + "5a668d25f038b7001ab0bfaf": "Digital Equipment Corporation", + "5a668d25f038b7001ab0bfb0": "", + "57263fd138643c19005ad37b": "a data network based on this voice-phone network", + "57263fd138643c19005ad37c": "computer service bureaus", + "57263fd138643c19005ad37d": "the centers were computer service bureaus, offering batch processing services", + "57263fd138643c19005ad37e": "He decided that a time-sharing system, based on Kemney's work at Dartmouth", + "5a551328134fea001a0e18d6": "", + "5a551328134fea001a0e18d7": "", + "5a551328134fea001a0e18d8": "computer time-sharing service", + "5a551328134fea001a0e18d9": "", + "5a551328134fea001a0e18da": "", + "5a668e55f038b7001ab0bfcb": "", + "5a668e55f038b7001ab0bfcc": "Dartmouth", + "5a668e55f038b7001ab0bfcd": "", + "5726414e271a42140099d7e5": "to explore computer networking between three of Michigan's public universities as a means to help the state's educational and economic development", + "5726414e271a42140099d7e6": "connections to the CDC mainframe at Michigan State University in East Lansing completed the triad", + "5726414e271a42140099d7e7": "All of this set the stage for Merit's role in the NSFNET project", + "5a551492134fea001a0e18e0": "computer networking between three of Michigan's public universities", + "5a551492134fea001a0e18e1": "Ann Arbor and Wayne State University in Detroit", + "5a551492134fea001a0e18e2": "Michigan Educational Research Information Triad", + "5a551492134fea001a0e18e3": "NSFNET project", + "5a551492134fea001a0e18e4": "", + "5a668fc9f038b7001ab0bfe6": "", + "5a668fc9f038b7001ab0bfe7": "1966", + "5a668fc9f038b7001ab0bfe8": "", + "5a668fc9f038b7001ab0bfe9": "", + "5a668fc9f038b7001ab0bfea": "", + "57264228ec44d21400f3dcf5": "Telenet was the first FCC-licensed public data network in the United States", + "57264228ec44d21400f3dcf6": "It was founded by former ARPA IPTO director Larry Roberts", + "57264228ec44d21400f3dcf7": "It was founded by former ARPA IPTO director Larry Roberts as a means of making ARPANET technology public", + "57264228ec44d21400f3dcf8": "", + "57264228ec44d21400f3dcf9": "", + "5a55157f134fea001a0e18ea": "Larry Roberts", + "5a55157f134fea001a0e18eb": "making ARPANET technology public", + "5a55157f134fea001a0e18ec": "", + "5a55157f134fea001a0e18ed": "", + "5a55157f134fea001a0e18ee": "this was incompatible with their future", + "5a6690d6f038b7001ab0bff0": "", + "5a6690d6f038b7001ab0bff1": "", + "5a6690d6f038b7001ab0bff2": "", + "5a6690d6f038b7001ab0bff3": "", + "5726431aec44d21400f3dd13": "an international data communications network", + "5726431aec44d21400f3dd14": "Users typically connected via dial-up connections or dedicated async connections", + "5726431aec44d21400f3dd15": "Users typically connected via dial-up connections or dedicated async connections", + "5726431aec44d21400f3dd16": "", + "5726431aec44d21400f3dd17": "", + "5a55167b134fea001a0e18fe": "virtual call packet switched technology", + "5a55167b134fea001a0e18ff": "to reach locations not on the private network", + "5a55167b134fea001a0e1900": "Mr. Tyme. Another employee", + "5a55167b134fea001a0e1901": "Users", + "5a55167b134fea001a0e1902": "thousands of large companies, educational institutions, and government agencies", + "5a6694dbf038b7001ab0c002": "", + "5a6694dbf038b7001ab0c003": "", + "5a6694dbf038b7001ab0c004": "", + "5a6694dbf038b7001ab0c005": "", + "5a6694dbf038b7001ab0c006": "", + "572643de5951261400b5195a": "There were two kinds", + "572643de5951261400b5195b": "Bell Northern Research", + "572643de5951261400b5195c": "", + "5a551a65134fea001a0e191c": "", + "5a551a65134fea001a0e191d": "DATAPAC clones", + "5a551a65134fea001a0e191e": "", + "5a551a65134fea001a0e191f": "", + "5a551a65134fea001a0e1920": "", + "5a6695e8f038b7001ab0c016": "", + "5a6695e8f038b7001ab0c017": "Bell Canada (a common carrier) and Northern Telecom", + "5a6695e8f038b7001ab0c018": "", + "5a6695e8f038b7001ab0c019": "", + "5a6695e8f038b7001ab0c01a": "interconnection of national X.25 networks", + "5726446a89cfff1900a8404d": "AUSTPAC was an Australian public X.25 network operated by Telstra", + "5726446a89cfff1900a8404e": "supporting applications such as on-line betting, financial applications", + "5726446a89cfff1900a8404f": "Access can be via a dial-up terminal to a PAD, or, by linking a permanent X.25 node to the network", + "5a551d87134fea001a0e1944": "", + "5a551d87134fea001a0e1945": "AUSTPAC", + "5a551d87134fea001a0e1946": "", + "5a551d87134fea001a0e1947": "academic institutions", + "5a551d87134fea001a0e1948": "remote terminal access to academic institutions", + "5a6696d0f038b7001ab0c020": "", + "5a6696d0f038b7001ab0c021": "terminal access to academic institutions", + "5a6696d0f038b7001ab0c022": "", + "5a6696d0f038b7001ab0c023": "", + "57264586f1498d1400e8dac6": "Datanet 1 was the public switched data network operated by the Dutch PTT Telecom", + "57264586f1498d1400e8dac7": "Strictly speaking Datanet 1 only referred to the network and the connected users via leased lines", + "57264586f1498d1400e8dac8": "", + "57264586f1498d1400e8dac9": "this use of the name was incorrect all these services were managed by the same people within one department of KPN contributed to the confusion.", + "5a552252134fea001a0e1962": "", + "5a552252134fea001a0e1963": "public PAD service Telepad", + "5a552252134fea001a0e1964": "Datanet 1 only referred to the network and the connected users via leased lines", + "5a552252134fea001a0e1965": "", + "5a552252134fea001a0e1966": "the same people within one department of KPN", + "5a669800f038b7001ab0c03c": "", + "5a669800f038b7001ab0c03d": "", + "5a669800f038b7001ab0c03e": "", + "5a669800f038b7001ab0c03f": "", + "5726462b708984140094c117": "The Computer Science Network", + "5726462b708984140094c118": "to extend networking benefits", + "5726462b708984140094c119": "", + "5a55234d134fea001a0e1974": "", + "5a55234d134fea001a0e1975": "The Computer Science Network", + "5a55234d134fea001a0e1976": "", + "5a55234d134fea001a0e1977": "", + "5a55234d134fea001a0e1978": "ARPANET", + "5a669a2cf038b7001ab0c044": "", + "5a669a2cf038b7001ab0c045": "to extend networking benefits", + "5a669a2cf038b7001ab0c046": "", + "5a669a2cf038b7001ab0c047": "", + "5a669a2cf038b7001ab0c048": "", + "5726472bdd62a815002e8042": "Internet2 is a not-for-profit United States computer networking consortium led by members from the research and education communities, industry, and government", + "5726472bdd62a815002e8043": "Qwest", + "5726472bdd62a815002e8044": "Abilene", + "5726472bdd62a815002e8045": "Qwest", + "5726472bdd62a815002e8046": "", + "5a55242b134fea001a0e197e": "", + "5a55242b134fea001a0e197f": "", + "5a55242b134fea001a0e1980": "", + "5a55242b134fea001a0e1981": "", + "5a55242b134fea001a0e1982": "", + "5a669b3df038b7001ab0c04e": "Abilene", + "5a669b3df038b7001ab0c04f": "", + "5a669b3df038b7001ab0c050": "", + "5a669b3df038b7001ab0c051": "National LambdaRail", + "572647e2dd62a815002e805c": "The National Science Foundation Network", + "572647e2dd62a815002e805d": "advanced research and education networking in the United States", + "572647e2dd62a815002e805e": "Initially created to link researchers to the nation's NSF-funded supercomputing centers", + "5a552578134fea001a0e1990": "", + "5a552578134fea001a0e1991": "", + "5a552578134fea001a0e1992": "link researchers to the nation's NSF-funded supercomputing centers", + "5a552578134fea001a0e1993": "Internet backbone", + "5a552578134fea001a0e1994": "", + "5a669ca9f038b7001ab0c056": "advanced research and education networking", + "5a669ca9f038b7001ab0c057": "a major part of the Internet backbone", + "5a669ca9f038b7001ab0c058": "", + "5a669ca9f038b7001ab0c059": "to link researchers to the nation's NSF-funded supercomputing centers", + "572648d1708984140094c15d": "Very high-speed Backbone Network Service", + "572648d1708984140094c15e": "The Very high-speed Backbone Network Service", + "572648d1708984140094c15f": "The network was engineered and operated by MCI Telecommunications", + "572648d1708984140094c160": "", + "572648d1708984140094c161": "The vBNS installed one of the first ever production OC-48c (2.5 Gbit/s) IP links in February 1999", + "5a55319c134fea001a0e19ba": "", + "5a55319c134fea001a0e19bb": "MCI Telecommunications", + "5a55319c134fea001a0e19bc": "", + "5a55319c134fea001a0e19bd": "", + "5a55319c134fea001a0e19be": "", + "5a669d5cf038b7001ab0c05e": "", + "5a669d5cf038b7001ab0c05f": "", + "5a669d5cf038b7001ab0c060": "", + "5a669d5cf038b7001ab0c061": "", + "5a669d5cf038b7001ab0c062": "", + "57264684708984140094c123": "Central Asia", + "57264684708984140094c124": "Spreading throughout the Mediterranean and Europe, the Black Death is estimated to have killed 30\u201360% of Europe's total population", + "57264684708984140094c125": "30\u201360%", + "57264684708984140094c126": "17th century", + "57264684708984140094c127": "The plague recurred occasionally in Europe until the 19th century", + "5a2eb84ba83784001a7d241f": "", + "5a2eb84ba83784001a7d2420": "reaching Crimea by 1343", + "5a2eb84ba83784001a7d2421": "", + "5a2eb84ba83784001a7d2422": "", + "5a2eb84ba83784001a7d2423": "", + "572647935951b619008f6ec9": "plague disease", + "572647935951b619008f6eca": "1338\u201339", + "572647935951b619008f6ecb": "China", + "572647935951b619008f6ecc": "1331", + "572647935951b619008f6ecd": "25 million", + "5a2eb95ca83784001a7d2429": "", + "5a2eb95ca83784001a7d242a": "13th century", + "5a2eb95ca83784001a7d242b": "", + "5a2eb95ca83784001a7d242c": "", + "5a2eb95ca83784001a7d242d": "", + "57264845f1498d1400e8db0a": "Genoese traders", + "57264845f1498d1400e8db0b": "Mongol army", + "57264845f1498d1400e8db0c": "infected corpses", + "57264845f1498d1400e8db0d": "Sicily and the south of Europe", + "57264845f1498d1400e8db0e": "", + "5a2eba17a83784001a7d2433": "", + "5a2eba17a83784001a7d2434": "", + "5a2eba17a83784001a7d2435": "", + "5a2eba17a83784001a7d2436": "", + "5a2eba17a83784001a7d2437": "Jani Beg", + "572648ed5951b619008f6f03": "northwest", + "572648ed5951b619008f6f04": "", + "572648ed5951b619008f6f05": "", + "572648ed5951b619008f6f06": "Germany and Scandinavia", + "572648ed5951b619008f6f07": "1349", + "5a2ebaada83784001a7d243d": "June 1348", + "5a2ebaada83784001a7d243e": "", + "5a2ebaada83784001a7d243f": "", + "5a2ebaada83784001a7d2440": "", + "5a2ebaada83784001a7d2441": "", + "57264991f1498d1400e8db2e": "depopulation and permanent change in both economic and social structures", + "57264991f1498d1400e8db2f": "autumn 1347", + "57264991f1498d1400e8db30": "through the port's trade with Constantinople, and ports on the Black Sea", + "57264991f1498d1400e8db31": "the north", + "5a2ebb5fa83784001a7d2447": "", + "5a2ebb5fa83784001a7d2448": "the north", + "5a2ebb5fa83784001a7d2449": "1348\u201349", + "5a2ebb5fa83784001a7d244a": "", + "5a2ebb5fa83784001a7d244b": "", + "57264a74708984140094c18b": "Gasquet", + "57264a74708984140094c18c": "atra mors", + "57264a74708984140094c18d": "Gasquet", + "57264a74708984140094c18e": "1823", + "57264a74708984140094c18f": "Germany", + "5a2ec431a83784001a7d2451": "", + "5a2ec431a83784001a7d2452": "1823", + "5a2ec431a83784001a7d2453": "", + "5a2ec431a83784001a7d2454": "", + "5a2ec431a83784001a7d2455": "", + "57264b3edd62a815002e80aa": "", + "57264b3edd62a815002e80ab": "the king of France", + "57264b3edd62a815002e80ac": "Miasma theory", + "57264b3edd62a815002e80ad": "the Miasma theory", + "5a2ec55da83784001a7d245b": "", + "5a2ec55da83784001a7d245c": "bad air", + "5a2ec55da83784001a7d245d": "", + "5a2ec55da83784001a7d245e": "", + "57264c42dd62a815002e80c6": "Yersinia pestis", + "57264c42dd62a815002e80c7": "1894", + "57264c42dd62a815002e80c8": "Alexandre Yersin", + "57264c42dd62a815002e80c9": "", + "57264c42dd62a815002e80ca": "two populations of rodents", + "5a2ec77ba83784001a7d2463": "1865", + "5a2ec77ba83784001a7d2464": "", + "5a2ec77ba83784001a7d2465": "", + "5a2ec77ba83784001a7d2466": "", + "5a2ec77ba83784001a7d2467": "Alexandre Yersin", + "57264cc6dd62a815002e80e4": "Francis Aidan Gasquet", + "57264cc6dd62a815002e80e5": "some form of the ordinary Eastern or bubonic plague", + "57264cc6dd62a815002e80e6": "1908", + "57264cc6dd62a815002e80e7": "", + "57264cc6dd62a815002e80e8": "Justinian plague", + "5a2ec82fa83784001a7d246d": "", + "5a2ec82fa83784001a7d246e": "", + "5a2ec82fa83784001a7d246f": "Great Pestilence", + "5a2ec82fa83784001a7d2470": "", + "57264d58f1498d1400e8db7a": "30\u201375%", + "57264d58f1498d1400e8db7b": "", + "57264d58f1498d1400e8db7c": "80 percent", + "57264d58f1498d1400e8db7d": "90 to 95 percent", + "57264d58f1498d1400e8db7e": "sputum", + "5a2ec98aa83784001a7d2477": "red", + "5a2ec98aa83784001a7d2478": "38\u201341 \u00b0C", + "5a2ec98aa83784001a7d2479": "38\u201341 \u00b0C", + "5a2ec98aa83784001a7d247a": "eight days", + "5a2ec98aa83784001a7d247b": "eight days", + "57264e2f708984140094c1e1": "October 2010", + "57264e2f708984140094c1e2": "Yersinia pestis in the Black Death", + "57264e2f708984140094c1e3": "with Polymerase Chain Reaction (PCR) techniques", + "57264e2f708984140094c1e4": "mass graves in northern, central and southern Europe", + "57264e2f708984140094c1e5": "Y. pestis was the causative agent of the epidemic plague that devastated Europe during the Middle Ages", + "5a2eca47a83784001a7d2481": "2010", + "5a2eca47a83784001a7d2482": "", + "5a2eca47a83784001a7d2483": "", + "5a2eca47a83784001a7d2484": "", + "5a2eca47a83784001a7d2485": "", + "57264f18f1498d1400e8dbae": "genetic branches", + "57264f18f1498d1400e8dbaf": "Y. p. orientalis and Y. p. medievalis", + "57264f18f1498d1400e8dbb0": "may have entered Europe in two waves", + "57264f18f1498d1400e8dbb1": "November 1347", + "57264f18f1498d1400e8dbb2": "1349", + "5a2ecb43a83784001a7d248b": "", + "5a2ecb43a83784001a7d248c": "", + "5a2ecb43a83784001a7d248d": "", + "5a2ecb43a83784001a7d248e": "", + "5a2ecb43a83784001a7d248f": "", + "57264fe65951b619008f6fa1": "confirmed and amended", + "57264fe65951b619008f6fa2": "", + "57264fe65951b619008f6fa3": "may no longer exist", + "57264fe65951b619008f6fa4": "", + "5a2ecbe9a83784001a7d2495": "", + "5a2ecbe9a83784001a7d2496": "", + "5a2ecbe9a83784001a7d2497": "", + "5a2ecbe9a83784001a7d2498": "", + "5726509bdd62a815002e815a": "J. F. D. Shrewsbury", + "5726509bdd62a815002e815b": "the reported rates of mortality in rural areas during the 14th-century pandemic were inconsistent with the modern bubonic plague", + "5726509bdd62a815002e815c": "contemporary accounts were exaggerations", + "5726509bdd62a815002e815d": "the first major work to challenge the bubonic plague theory", + "5726509bdd62a815002e815e": "Samuel K. Cohn, Jr.", + "5a2eccc9a83784001a7d249f": "Graham Twigg", + "5a2eccc9a83784001a7d24a0": "", + "5a2eccc9a83784001a7d24a1": "", + "5a2eccc9a83784001a7d24a2": "", + "5a2eccc9a83784001a7d24a3": "", + "5726516a708984140094c223": "an epidemiological account", + "5726516a708984140094c224": "lack of reliable statistics", + "5726516a708984140094c225": "over 100%", + "5726516a708984140094c226": "the clergy", + "5726516a708984140094c227": "between the time of publication of the Domesday Book and the year 1377", + "5a2ecd6da83784001a7d24a9": "", + "5a2ecd6da83784001a7d24aa": "", + "5a2ecd6da83784001a7d24ab": "", + "5a2ecd6da83784001a7d24ac": "", + "57265285708984140094c25b": "the DNA results may be flawed and might not have been repeated elsewhere, despite extensive samples from other mass graves", + "57265285708984140094c25c": "marginal", + "57265285708984140094c25d": "temperatures that are too cold in northern Europe for the survival of fleas", + "57265285708984140094c25e": "", + "57265285708984140094c25f": "5 to 15", + "5a2eced7a83784001a7d24b1": "", + "5a2eced7a83784001a7d24b2": "", + "5a2eced7a83784001a7d24b3": "", + "5a2eced7a83784001a7d24b4": "", + "5a2eced7a83784001a7d24b5": "", + "5726534d708984140094c26d": "", + "5726534d708984140094c26e": "it may have been a combination of anthrax and other pandemics", + "5726534d708984140094c26f": "typhus, smallpox and respiratory infections", + "5726534d708984140094c270": "blood poisoning", + "5726534d708984140094c271": "25", + "5a2ecfb1a83784001a7d24c5": "", + "5a2ecfb1a83784001a7d24c6": "", + "5a2ecfb1a83784001a7d24c7": "", + "5a2ecfb1a83784001a7d24c8": "", + "5a2ecfb1a83784001a7d24c9": "", + "5726542ff1498d1400e8dc28": "", + "5726542ff1498d1400e8dc29": "Half", + "5726542ff1498d1400e8dc2a": "pre-planning and Christian burials", + "5726542ff1498d1400e8dc2b": "50%", + "5726542ff1498d1400e8dc2c": "", + "5a2ed0a0a83784001a7d24cf": "40%", + "5a2ed0a0a83784001a7d24d0": "Bremen", + "5a2ed0a0a83784001a7d24d1": "", + "5a2ed0a0a83784001a7d24d2": "", + "5a2ed0a0a83784001a7d24d3": "", + "572654e2708984140094c2b7": "14th to 17th centuries", + "572654e2708984140094c2b8": "", + "572654e2708984140094c2b9": "almost a million", + "5a2ed136a83784001a7d24d9": "", + "5a2ed136a83784001a7d24da": "", + "5a2ed136a83784001a7d24db": "", + "5a2ed136a83784001a7d24dc": "", + "5a2ed136a83784001a7d24dd": "", + "5726559edd62a815002e81c8": "propose a range of preincident population figures", + "5726559edd62a815002e81c9": "1350", + "5726559edd62a815002e81ca": "", + "5726559edd62a815002e81cb": "1665", + "5a2ed246a83784001a7d24e3": "", + "5a2ed246a83784001a7d24e4": "", + "5a2ed246a83784001a7d24e5": "", + "5a2ed246a83784001a7d24e6": "", + "5a2ed246a83784001a7d24e7": "", + "57265642f1498d1400e8dc68": "40,000", + "57265642f1498d1400e8dc69": "Russia", + "57265642f1498d1400e8dc6a": "22", + "57265642f1498d1400e8dc6b": "", + "57265642f1498d1400e8dc6c": "1654", + "5a2ed354a83784001a7d24ed": "30", + "5a2ed354a83784001a7d24ee": "", + "5a2ed354a83784001a7d24ef": "", + "5a2ed354a83784001a7d24f0": "", + "5a2ed354a83784001a7d24f1": "", + "57265700dd62a815002e820e": "1.7 million", + "57265700dd62a815002e820f": "300,000", + "57265700dd62a815002e8210": "", + "57265700dd62a815002e8211": "Sweden v. Russia and allies", + "57265700dd62a815002e8212": "1720", + "5a2ed42fa83784001a7d24f7": "", + "5a2ed42fa83784001a7d24f8": "", + "5a2ed42fa83784001a7d24f9": "", + "5a2ed42fa83784001a7d24fa": "a third", + "5a2ed42fa83784001a7d24fb": "", + "5726577f708984140094c301": "between 1500 and 1850", + "5726577f708984140094c302": "30 to 50 thousand", + "5726577f708984140094c303": "until the second quarter of the 19th century", + "5726577f708984140094c304": "two-thirds", + "5a2ed525a83784001a7d2501": "", + "5a2ed525a83784001a7d2502": "", + "5a2ed525a83784001a7d2503": "", + "5a2ed525a83784001a7d2504": "", + "5a2ed525a83784001a7d2505": "", + "572657d9dd62a815002e8230": "melt", + "572657d9dd62a815002e8231": "metamorphic rock", + "572657d9dd62a815002e8232": "a new magma", + "572657d9dd62a815002e8233": "igneous, sedimentary, and metamorphic", + "572657d9dd62a815002e8234": "heat and pressure", + "5a57c667770dc0001aeefd66": "", + "5a57c667770dc0001aeefd67": "", + "5a57c667770dc0001aeefd68": "", + "5a57c667770dc0001aeefd69": "", + "5a57c667770dc0001aeefd6a": "", + "5a58cfd63e1742001a15ce32": "", + "5a58cfd63e1742001a15ce33": "", + "5a58cfd63e1742001a15ce34": "", + "5a58cfd63e1742001a15ce35": "", + "5a58cfd63e1742001a15ce36": "heat and pressure that change the mineral content", + "57265d08708984140094c397": "seafloor spreading", + "57265d08708984140094c398": "crust and rigid uppermost portion of the upper mantle", + "57265d08708984140094c399": "asthenosphere", + "57265d08708984140094c39a": "the convection of the mantle", + "57265d08708984140094c39b": "1960s", + "5a57ca90770dc0001aeefd70": "", + "5a57ca90770dc0001aeefd71": "", + "5a57ca90770dc0001aeefd72": "", + "5a57ca90770dc0001aeefd73": "", + "5a57ca90770dc0001aeefd74": "", + "5a58d33e3e1742001a15ce3c": "", + "5a58d33e3e1742001a15ce3d": "", + "5a58d33e3e1742001a15ce3e": "", + "5a58d33e3e1742001a15ce3f": "1960s", + "5a58d33e3e1742001a15ce40": "", + "57265f605951b619008f70db": "divergent boundaries", + "57265f605951b619008f70dc": "convergent boundaries", + "57265f605951b619008f70dd": "Transform", + "57265f605951b619008f70de": "Alfred Wegener", + "57265f605951b619008f70df": "convecting", + "5a57cc97770dc0001aeefd84": "widespread powerful earthquakes", + "5a57cc97770dc0001aeefd86": "divergent boundaries", + "5a57cc97770dc0001aeefd87": "", + "5a57cc97770dc0001aeefd88": "", + "5a58db973e1742001a15ce4e": "", + "5a58db973e1742001a15ce4f": "", + "5a58db973e1742001a15ce50": "", + "5a58db973e1742001a15ce51": "Alfred Wegener's theory of continental drift", + "5a58db973e1742001a15ce52": "", + "57266193dd62a815002e832a": "seismic waves", + "57266193dd62a815002e832b": "", + "57266193dd62a815002e832c": "a crust and lithosphere", + "57266193dd62a815002e832d": "mantle below", + "57266193dd62a815002e832e": "wave speeds", + "5a57cf7a770dc0001aeefda2": "", + "5a57cf7a770dc0001aeefda3": "", + "5a57cf7a770dc0001aeefda4": "", + "5a57cf7a770dc0001aeefda5": "", + "5a57cf7a770dc0001aeefda6": "", + "5a58dd513e1742001a15ce61": "liquid", + "5a58dd513e1742001a15ce62": "", + "5a58dd513e1742001a15ce63": "", + "572663a9f1498d1400e8ddf2": "", + "572663a9f1498d1400e8ddf4": "Quaternary", + "572663a9f1498d1400e8ddf5": "Holocene", + "572663a9f1498d1400e8ddf6": "Quaternary", + "5a57d364770dc0001aeefdc8": "the most recent era", + "5a57d364770dc0001aeefdc9": "", + "5a57d364770dc0001aeefdca": "", + "5a57d364770dc0001aeefdcb": "", + "5a57d364770dc0001aeefdcc": "", + "5a58e3833e1742001a15ce82": "", + "5a58e3833e1742001a15ce83": "", + "5a58e3833e1742001a15ce84": "", + "5a58e3833e1742001a15ce85": "", + "5a58e3833e1742001a15ce86": "", + "572665ff708984140094c4c3": "The principle of cross-cutting relationships", + "572665ff708984140094c4c4": "older", + "572665ff708984140094c4c5": "the key bed", + "572665ff708984140094c4c6": "", + "5a57d668770dc0001aeefde6": "", + "5a57d668770dc0001aeefde7": "", + "5a57d668770dc0001aeefde8": "", + "5a57d668770dc0001aeefde9": "", + "5a57d668770dc0001aeefdea": "", + "5a58e9133e1742001a15cea6": "", + "5a58e9133e1742001a15cea7": "", + "5a58e9133e1742001a15cea8": "", + "5a58e9133e1742001a15cea9": "", + "5a58e9133e1742001a15ceaa": "", + "572667e2f1498d1400e8de90": "", + "572667e2f1498d1400e8de91": "magma or lava flows", + "572667e2f1498d1400e8de92": "clasts", + "572667e2f1498d1400e8de93": "The principle of inclusions and components", + "572667e2f1498d1400e8de94": "gravel", + "5a57eee0770dc0001aeefed8": "", + "5a57eee0770dc0001aeefed9": "", + "5a57eee0770dc0001aeefeda": "", + "5a57eee0770dc0001aeefedb": "", + "5a57eee0770dc0001aeefedc": "", + "5a58f69e3e1742001a15cede": "", + "5a58f69e3e1742001a15cedf": "", + "5a58f69e3e1742001a15cee0": "", + "5a58f69e3e1742001a15cee1": "", + "5a58f69e3e1742001a15cee2": "", + "572669a9dd62a815002e8416": "The principle of faunal succession", + "572669a9dd62a815002e8417": "William Smith", + "572669a9dd62a815002e8418": "complex", + "572669a9dd62a815002e8419": "organisms", + "572669a9dd62a815002e841a": "", + "5a57f0ea770dc0001aeefee2": "", + "5a57f0ea770dc0001aeefee3": "", + "5a57f0ea770dc0001aeefee4": "", + "5a57f0ea770dc0001aeefee5": "", + "5a57f0ea770dc0001aeefee6": "fossilization", + "5a58feb63e1742001a15cf2e": "", + "5a58feb63e1742001a15cf2f": "William Smith", + "5a58feb63e1742001a15cf30": "uncertainties of fossilization", + "5a58feb63e1742001a15cf31": "organisms exist at the same time period throughout the world", + "5a58feb63e1742001a15cf32": "", + "57266c015951b619008f7237": "beginning of the 20th century", + "57266c015951b619008f7238": "stratigraphic", + "57266c015951b619008f7239": "new absolute ages", + "57266c015951b619008f723a": "one another", + "57266c015951b619008f723b": "fossil sequences", + "5a57f487770dc0001aeefefc": "ability to obtain accurate absolute dates to geologic events using radioactive isotopes and other methods", + "5a57f487770dc0001aeefefd": "geologic time", + "5a57f487770dc0001aeefefe": "", + "5a57f487770dc0001aeefeff": "", + "5a57f487770dc0001aeeff00": "", + "5a59002d3e1742001a15cf38": "", + "5a59002d3e1742001a15cf39": "", + "5a59002d3e1742001a15cf3a": "", + "5a59002d3e1742001a15cf3b": "new absolute ages", + "5a59002d3e1742001a15cf3c": "", + "57266e72f1498d1400e8df8c": "Thermochemical", + "57266e72f1498d1400e8df8d": "closure temperature", + "57266e72f1498d1400e8df8e": "isotope ratios of radioactive elements", + "57266e72f1498d1400e8df8f": "Dating of lava and volcanic ash layers found within a stratigraphic sequence", + "5a57f717770dc0001aeeff06": "", + "5a57f717770dc0001aeeff07": "", + "5a57f717770dc0001aeeff08": "", + "5a57f717770dc0001aeeff09": "", + "5a57f717770dc0001aeeff0a": "", + "5a5904ed3e1742001a15cf42": "", + "5a5904ed3e1742001a15cf43": "", + "5a5904ed3e1742001a15cf44": "", + "5a5904ed3e1742001a15cf45": "", + "5a5904ed3e1742001a15cf46": "", + "5726701add62a815002e84c8": "horizontal", + "5726701add62a815002e84c9": "shallow crust", + "5726701add62a815002e84ca": "antiforms", + "5726701add62a815002e84cb": "synforms", + "5726701add62a815002e84cc": "anticlines and synclines", + "5a57fb62770dc0001aeeff10": "", + "5a57fb62770dc0001aeeff11": "", + "5a57fb62770dc0001aeeff12": "", + "5a57fb62770dc0001aeeff13": "", + "5a57fb62770dc0001aeeff14": "thrust faults form", + "5a5909b13e1742001a15cf4c": "", + "5a5909b13e1742001a15cf4d": "principle of superposition", + "5a5909b13e1742001a15cf4e": "plastically, and fold", + "5a5909b13e1742001a15cf4f": "", + "5a5909b13e1742001a15cf50": "antiforms", + "572671a5f1498d1400e8dfe4": "Extension", + "572671a5f1498d1400e8dfe5": "boudins", + "572671a5f1498d1400e8dfe6": "Maria Fold and Thrust Belt", + "572671a5f1498d1400e8dfe7": "metamorphosed", + "572671a5f1498d1400e8dfe8": "normal faulting and through the ductile stretching and thinning", + "5a57fe29770dc0001aeeff1a": "", + "5a57fe29770dc0001aeeff1b": "", + "5a57fe29770dc0001aeeff1c": "", + "5a57fe29770dc0001aeeff1d": "", + "5a57fe29770dc0001aeeff1e": "", + "5a590de93e1742001a15cf56": "", + "5a590de93e1742001a15cf57": "", + "5a590de93e1742001a15cf58": "", + "5a590de93e1742001a15cf59": "Maria Fold and Thrust Belt", + "5a590de93e1742001a15cf5a": "", + "572673f5708984140094c69b": "Dikes", + "572673f5708984140094c69c": "in large numbers in areas that are being actively deformed", + "572673f5708984140094c69d": "topographic", + "572673f5708984140094c69e": "Continual motion along the fault", + "572673f5708984140094c69f": "Deformational events", + "5a580070770dc0001aeeff36": "", + "5a580070770dc0001aeeff37": "", + "5a580070770dc0001aeeff38": "", + "5a580070770dc0001aeeff39": "", + "5a580070770dc0001aeeff3a": "accommodation space", + "5a590efb3e1742001a15cf60": "", + "5a590efb3e1742001a15cf61": "material on the rock unit that is increasing in elevation to be eroded by hillslopes and channels", + "5a590efb3e1742001a15cf62": "", + "5a590efb3e1742001a15cf63": "volcanism", + "5a590efb3e1742001a15cf64": "", + "57267640f1498d1400e8e074": "layered basaltic lava flows", + "57267640f1498d1400e8e075": "Acasta gneiss of the Slave craton in northwestern Canada", + "57267640f1498d1400e8e076": "sedimentary", + "57267640f1498d1400e8e077": "Cambrian time", + "57267640f1498d1400e8e078": "northwestern Canada", + "5a580429770dc0001aeeff46": "", + "5a580429770dc0001aeeff47": "", + "5a580429770dc0001aeeff48": "metamorphosed", + "5a580429770dc0001aeeff49": "", + "5a580429770dc0001aeeff4a": "", + "5a5915043e1742001a15cf6a": "", + "5a5915043e1742001a15cf6b": "metamorphosed, faulted, foliated, and folded", + "5a5915043e1742001a15cf6c": "", + "5a5915043e1742001a15cf6d": "basaltic lava flows", + "5a5915043e1742001a15cf6e": "", + "572677e7708984140094c723": "the study of rocks", + "572677e7708984140094c724": "the study of sedimentary layers", + "572677e7708984140094c725": "the study of positions of rock units and their deformation", + "572677e7708984140094c726": "soils, rivers, landscapes, and glaciers", + "5a5808ef770dc0001aeeff66": "", + "5a5808ef770dc0001aeeff67": "", + "5a5808ef770dc0001aeeff68": "geophysical methods", + "5a5808ef770dc0001aeeff69": "", + "5a5808ef770dc0001aeeff6a": "", + "5a5915cd3e1742001a15cf74": "", + "5a5915cd3e1742001a15cf75": "", + "5a5915cd3e1742001a15cf76": "past and current life", + "5a5915cd3e1742001a15cf77": "", + "5a5915cd3e1742001a15cf78": "", + "57267947f1498d1400e8e0ec": "identifying rocks", + "57267947f1498d1400e8e0ed": "", + "57267947f1498d1400e8e0ee": "the geochemical evolution of rock units", + "57267947f1498d1400e8e0ef": "the laboratory", + "57267947f1498d1400e8e0f0": "", + "5a580ab1770dc0001aeeff78": "", + "5a580ab1770dc0001aeeff79": "", + "5a580ab1770dc0001aeeff7a": "", + "5a580ab1770dc0001aeeff7b": "", + "5a580ab1770dc0001aeeff7c": "", + "5a5918ff3e1742001a15cf7e": "", + "5a5918ff3e1742001a15cf7f": "", + "5a5918ff3e1742001a15cf80": "", + "5a5918ff3e1742001a15cf81": "optical microscopy and by using an electron microprobe", + "5a5918ff3e1742001a15cf82": "", + "57267b3c5951b619008f7423": "perform high temperature and pressure physical experiments", + "57267b3c5951b619008f7424": "perform high temperature and pressure physical experiments", + "57267b3c5951b619008f7425": "metamorphic processes and the conditions of crystallization of igneous rocks", + "5a580d05770dc0001aeeff96": "", + "5a580d05770dc0001aeeff97": "", + "5a580d05770dc0001aeeff98": "", + "5a580d05770dc0001aeeff99": "", + "5a580d05770dc0001aeeff9a": "", + "5a591a5f3e1742001a15cf88": "", + "5a591a5f3e1742001a15cf89": "", + "5a591a5f3e1742001a15cf8a": "", + "5a591a5f3e1742001a15cf8b": "", + "57267d52708984140094c7d9": "Structural", + "57267d52708984140094c7da": "microscopic analysis of oriented thin sections of geologic samples", + "57267d52708984140094c7db": "plot and combine", + "57267d52708984140094c7dc": "analog and numerical", + "5a5810c4770dc0001aeeffb8": "", + "5a5810c4770dc0001aeeffb9": "", + "5a5810c4770dc0001aeeffba": "", + "5a5810c4770dc0001aeeffbb": "strain", + "5a5810c4770dc0001aeeffbc": "", + "5a591f773e1742001a15cfa4": "", + "5a591f773e1742001a15cfa5": "", + "5a591f773e1742001a15cfa6": "history", + "5a591f773e1742001a15cfa7": "", + "5a591f773e1742001a15cfa8": "", + "57267ebfdd62a815002e872c": "orogenic wedges", + "57267ebfdd62a815002e872d": "orogenic wedges", + "57267ebfdd62a815002e872e": "sand", + "57267ebfdd62a815002e872f": "all angles remain the same", + "57267ebfdd62a815002e8730": "Numerical models", + "5a5812f9770dc0001aeeffd0": "", + "5a5812f9770dc0001aeeffd1": "more sophisticated", + "5a5812f9770dc0001aeeffd2": "", + "5a5812f9770dc0001aeeffd3": "", + "5a5812f9770dc0001aeeffd4": "", + "5a5920963e1742001a15cfae": "", + "5a5920963e1742001a15cfaf": "", + "5a5920963e1742001a15cfb0": "", + "5a5920963e1742001a15cfb1": "", + "5a5920963e1742001a15cfb2": "", + "57268066708984140094c821": "stratigraphers", + "57268066708984140094c822": "geophysical", + "57268066708984140094c823": "logs", + "57268066708984140094c824": "computer programs", + "57268066708984140094c825": "water, coal, and hydrocarbon", + "5a581597770dc0001aeeffe2": "", + "5a581597770dc0001aeeffe3": "", + "5a581597770dc0001aeeffe4": "", + "5a581597770dc0001aeeffe5": "", + "5a581597770dc0001aeeffe6": "", + "5a5929d33e1742001a15cfc2": "", + "5a5929d33e1742001a15cfc3": "", + "5a5929d33e1742001a15cfc4": "", + "5a5929d33e1742001a15cfc5": "", + "5a5929d33e1742001a15cfc6": "", + "57268220f1498d1400e8e216": "biostratigraphers", + "57268220f1498d1400e8e217": "Geochronologists", + "57268220f1498d1400e8e218": "to provide better absolute bounds on the timing and rates of deposition", + "57268220f1498d1400e8e219": "Magnetic stratigraphers", + "5a5817e3770dc0001aeeffec": "", + "5a5817e3770dc0001aeeffed": "", + "5a5817e3770dc0001aeeffee": "", + "5a5817e3770dc0001aeeffef": "", + "5a5817e3770dc0001aeefff0": "", + "5a592b593e1742001a15cfcc": "", + "5a592b593e1742001a15cfcd": "", + "5a592b593e1742001a15cfce": "", + "5a592b593e1742001a15cfcf": "", + "5a592b593e1742001a15cfd0": "", + "572683f95951b619008f7525": "Persia", + "572683f95951b619008f7526": "Abu al-Rayhan al-Biruni", + "572683f95951b619008f7527": "polymath Shen Kuo", + "572683f95951b619008f7528": "Ibn Sina", + "572683f95951b619008f7529": "fossil animal shells", + "5a581adb770dc0001aeefff6": "", + "5a581adb770dc0001aeefff7": "", + "5a581adb770dc0001aeefff8": "Greek and Indian scientific literature", + "5a581adb770dc0001aeefff9": "", + "5a581adb770dc0001aeefffa": "erosion of the mountains and by deposition of silt", + "5a592c9d3e1742001a15cfd6": "", + "5a592c9d3e1742001a15cfd7": "polymath", + "5a592c9d3e1742001a15cfd8": "", + "5a592c9d3e1742001a15cfd9": "the geology of India", + "5a592c9d3e1742001a15cfda": "", + "57268527708984140094c8bf": "James Hutton", + "57268527708984140094c8c0": "Theory of the Earth", + "57268527708984140094c8c1": "1795", + "57268527708984140094c8c2": "the Earth must be much older", + "5a581bda770dc0001aef0000": "", + "5a581bda770dc0001aef0001": "", + "5a581bda770dc0001aef0002": "", + "5a581bda770dc0001aef0003": "", + "5a581bda770dc0001aef0004": "to allow enough time for mountains to be eroded", + "5a592d703e1742001a15cfea": "", + "5a592d703e1742001a15cfeb": "", + "5a592d703e1742001a15cfec": "to allow enough time for mountains to be eroded", + "5a592d703e1742001a15cfed": "James Hutton", + "5a592d703e1742001a15cfee": "", + "572686ac5951b619008f75a9": "William Maclure", + "572686ac5951b619008f75aa": "1809", + "572686ac5951b619008f75ab": "1809", + "572686ac5951b619008f75ac": "the American Philosophical Society", + "572686ac5951b619008f75ad": "Observations on the Geology of the United States explanatory of a Geological Map", + "5a581e5d770dc0001aef000a": "", + "5a581e5d770dc0001aef000b": "", + "5a581e5d770dc0001aef000c": "", + "5a581e5d770dc0001aef000d": "", + "5a581e5d770dc0001aef000e": "", + "5a592e733e1742001a15cff4": "1809", + "5a592e733e1742001a15cff5": "", + "5a592e733e1742001a15cff6": "", + "5a592e733e1742001a15cff7": "1807", + "5a592e733e1742001a15cff8": "", + "57268882f1498d1400e8e306": "Principles of Geology", + "57268882f1498d1400e8e307": "uniformitarianism", + "57268882f1498d1400e8e308": "uniformitarianism", + "57268882f1498d1400e8e309": "catastrophism", + "57268882f1498d1400e8e30a": "Charles Darwin", + "5a582cfa770dc0001aef0014": "", + "5a582cfa770dc0001aef0015": "doctrine of uniformitarianism", + "5a582cfa770dc0001aef0016": "", + "5a582cfa770dc0001aef0017": "", + "5a582cfa770dc0001aef0018": "", + "5a592f3f3e1742001a15cffe": "", + "5a592f3f3e1742001a15cfff": "", + "5a592f3f3e1742001a15d000": "", + "5a592f3f3e1742001a15d001": "Charles Darwin", + "5a592f3f3e1742001a15d002": "", + "5726d8bd708984140094d35b": "pharma", + "5726d8bd708984140094d35c": "tobacco and patent medicines", + "5726d8bd708984140094d35d": "sorcery or even poison", + "5726d8bd708984140094d35e": "outdated or only approproriate", + "5726d8bd708984140094d35f": "herbs not listed", + "5a6cb5c14eec6b001a80a624": "", + "5a6cb5c14eec6b001a80a625": "", + "5a6cb5c14eec6b001a80a626": "", + "5a6cb5c14eec6b001a80a628": "", + "5726d9935951b619008f7fed": "healthcare", + "5726d9935951b619008f7fee": "optimal", + "5726d9935951b619008f7fef": "optimisation", + "5726d9935951b619008f7ff0": "optimisation of a drug treatment", + "5726d9935951b619008f7ff1": "", + "5a6cb66c4eec6b001a80a62e": "", + "5a6cb66c4eec6b001a80a62f": "", + "5a6cb66c4eec6b001a80a630": "", + "5a6cb66c4eec6b001a80a631": "", + "5a6cb66c4eec6b001a80a632": "", + "5726da89dd62a815002e92b2": "other senior pharmacy technicians", + "5726da89dd62a815002e92b3": "General Pharmaceutical Council", + "5726da89dd62a815002e92b4": "regulates the practice of pharmacists and pharmacy technicians", + "5726da89dd62a815002e92b5": "health care", + "5726da89dd62a815002e92b6": "manage the pharmacy department and specialised areas in pharmacy practice", + "5a6cb7ce4eec6b001a80a638": "", + "5a6cb7ce4eec6b001a80a639": "", + "5a6cb7ce4eec6b001a80a63a": "", + "5a6cb7ce4eec6b001a80a63b": "", + "5726db5add62a815002e92d4": "Diocles of Carystus", + "5726db5add62a815002e92d5": "writing a five volume book", + "5726db5add62a815002e92d6": "De Materia Medica", + "5726db5add62a815002e92d7": "materia medica", + "5726db5add62a815002e92d8": "middle eastern scientists", + "5a6cb89e4eec6b001a80a640": "", + "5a6cb89e4eec6b001a80a641": "", + "5a6cb89e4eec6b001a80a642": "", + "5a6cb89e4eec6b001a80a643": "", + "5a6cb89e4eec6b001a80a644": "", + "5726dcbddd62a815002e9320": "highly respected", + "5726dcbddd62a815002e9321": "Taih\u014d Code", + "5726dcbddd62a815002e9322": "pre-Heian Imperial court", + "5726dcbddd62a815002e9323": "", + "5726dcbddd62a815002e9324": "ranked above", + "5a6cba504eec6b001a80a64a": "", + "5a6cba504eec6b001a80a64b": "", + "5a6cba504eec6b001a80a64c": "In the Imperial household", + "5a6cba504eec6b001a80a64d": "", + "5726ddf6f1498d1400e8ee04": "botany and chemistry", + "5726ddf6f1498d1400e8ee05": "Muhammad ibn Zakar\u012bya R\u0101zi", + "5726ddf6f1498d1400e8ee06": "Abu al-Qasim al-Zahrawi", + "5726ddf6f1498d1400e8ee07": "sodium carbonate and potassium carbonate", + "5726ddf6f1498d1400e8ee08": "", + "5a6cbba74eec6b001a80a652": "", + "5a6cbba74eec6b001a80a653": "", + "5a6cbba74eec6b001a80a654": "", + "5a6cbba74eec6b001a80a655": "", + "5a6cbba74eec6b001a80a656": "", + "5726deed5951b619008f80c5": "at least 1422", + "5726deed5951b619008f80c6": "Florence, Italy", + "5726deed5951b619008f80c7": "a museum", + "5726deed5951b619008f80c8": "old prescription books and antique drugs", + "5726deed5951b619008f80c9": "1221", + "5a6cdddf4eec6b001a80a65c": "", + "5a6cdddf4eec6b001a80a65d": "", + "5a6cdddf4eec6b001a80a65e": "", + "5a6cdddf4eec6b001a80a65f": "", + "5726e08e5951b619008f810f": "pharmacy legislation", + "5726e08e5951b619008f8110": "", + "5726e08e5951b619008f8111": "automation", + "5726e08e5951b619008f8112": "patients' prescriptions and patient safety issues", + "5726e08e5951b619008f8113": "requirements for storage conditions, compulsory texts, equipment, etc.", + "5a6ce1054eec6b001a80a664": "", + "5a6ce1054eec6b001a80a665": "", + "5a6ce1054eec6b001a80a666": "", + "5a6ce1054eec6b001a80a667": "", + "5a6ce1054eec6b001a80a668": "", + "5726e179dd62a815002e93ae": "pharmacy practice residency", + "5726e179dd62a815002e93af": "various disciplines of pharmacy", + "5726e179dd62a815002e93b0": "patient compliance", + "5726e179dd62a815002e93b1": "practicing in hospitals", + "5a6ce1ca4eec6b001a80a66e": "", + "5a6ce1ca4eec6b001a80a66f": "", + "5a6ce1ca4eec6b001a80a670": "", + "5a6ce1ca4eec6b001a80a671": "", + "5726e313f1498d1400e8eeb2": "within the premises of the hospital", + "5726e313f1498d1400e8eeb3": "unit-dose, or a single dose of medicine", + "5726e313f1498d1400e8eeb4": "high risk preparations", + "5726e313f1498d1400e8eeb5": "high cost of medications", + "5726e313f1498d1400e8eeb6": "more specialized medications", + "5a6ce2ec4eec6b001a80a676": "", + "5a6ce2ec4eec6b001a80a677": "", + "5a6ce2ec4eec6b001a80a678": "", + "5a6ce2ec4eec6b001a80a679": "", + "5a6ce2ec4eec6b001a80a67a": "", + "5726e3c4dd62a815002e9404": "direct patient care services that optimizes the use of medication and promotes health, wellness, and disease prevention", + "5726e3c4dd62a815002e9405": "inside hospitals and clinics", + "5726e3c4dd62a815002e9406": "physicians and other healthcare professionals", + "5726e3c4dd62a815002e9407": "patient care rounds drug product selection", + "5726e3c4dd62a815002e9408": "all health care settings", + "5a6ce4164eec6b001a80a680": "", + "5a6ce4164eec6b001a80a681": "", + "5a6ce4164eec6b001a80a682": "", + "5a6ce4164eec6b001a80a683": "", + "5726e5c95951b619008f81cb": "creating a comprehensive drug therapy plan for patient-specific problems", + "5726e5c95951b619008f81cc": "an evaluation of the appropriateness of the drug therapy", + "5726e5c95951b619008f81cd": "drug choice, dose, route, frequency, and duration of therapy", + "5726e5c95951b619008f81ce": "potential drug interactions, adverse drug reactions", + "5a6ce4fa4eec6b001a80a688": "", + "5a6ce4fa4eec6b001a80a689": "", + "5a6ce4fa4eec6b001a80a68a": "", + "5a6ce4fa4eec6b001a80a68b": "", + "5726e985dd62a815002e94da": "full independent prescribing authority", + "5726e985dd62a815002e94db": "North Carolina and New Mexico", + "5726e985dd62a815002e94dc": "2011", + "5726e985dd62a815002e94dd": "Board Certified Ambulatory Care Pharmacist", + "5726e985dd62a815002e94de": "VA, the Indian Health Service, and NIH", + "5a6ce55e4eec6b001a80a690": "", + "5a6ce55e4eec6b001a80a691": "", + "5a6ce55e4eec6b001a80a692": "", + "5a6ce55e4eec6b001a80a693": "", + "5a6ce55e4eec6b001a80a694": "", + "5726ea985951b619008f8261": "medication regimen review", + "5726ea985951b619008f8262": "nursing homes", + "5726ea985951b619008f8263": "Omnicare, Kindred Healthcare and PharMerica", + "5726ea985951b619008f8264": "many elderly people are now taking numerous medications but continue to live outside of institutional settings", + "5726ea985951b619008f8265": "employ consultant pharmacists and/or provide consulting services", + "5a6ce6164eec6b001a80a69a": "", + "5a6ce6164eec6b001a80a69b": "", + "5a6ce6164eec6b001a80a69c": "", + "5a6ce6164eec6b001a80a69d": "many elderly people are now taking numerous medications but continue to live outside of institutional settings", + "5a6ce6164eec6b001a80a69e": "", + "5726eb4b5951b619008f826b": "about the year 2000", + "5726eb4b5951b619008f826c": "brick-and-mortar community pharmacies", + "5726eb4b5951b619008f826d": "online pharmacies", + "5726eb4b5951b619008f826e": "", + "5726eb4b5951b619008f826f": "the method by which the medications are requested and received", + "5a6ce6b54eec6b001a80a6a4": "", + "5a6ce6b54eec6b001a80a6a5": "", + "5a6ce6b54eec6b001a80a6a6": "", + "5a6ce6b54eec6b001a80a6a7": "", + "5a6ce6b54eec6b001a80a6a8": "", + "5726ed6cf1498d1400e8f00c": "to avoid the \"inconvenience\" of visiting a doctor", + "5726ed6cf1498d1400e8f00d": "", + "5726ed6cf1498d1400e8f00e": "potentially dangerous", + "5726ed6cf1498d1400e8f00f": "sell prescription drugs without requiring a prescription", + "5726ed6cf1498d1400e8f010": "sell prescription drugs and require a valid prescription", + "5a6ce7444eec6b001a80a6ae": "", + "5a6ce7444eec6b001a80a6af": "", + "5a6ce7444eec6b001a80a6b0": "valid prescription", + "5a6ce7444eec6b001a80a6b1": "", + "5726edecdd62a815002e957f": "it must be issued for a legitimate medical purpose by a licensed practitioner acting in the course of legitimate doctor-patient relationship", + "5726ef73f1498d1400e8f05e": "ease with which people, youth in particular, can obtain controlled substances", + "5726ef73f1498d1400e8f05f": "", + "5726ef73f1498d1400e8f060": "ensure that the prescription is valid", + "5726ef73f1498d1400e8f061": "individual state laws", + "5726ef73f1498d1400e8f062": "Vicodin", + "5a6ce8ea4eec6b001a80a6b6": "", + "5a6ce8ea4eec6b001a80a6b7": "", + "5a6ce8ea4eec6b001a80a6b8": "", + "5a6ce8ea4eec6b001a80a6b9": "", + "5a6ce8ea4eec6b001a80a6ba": "", + "5726f0e35951b619008f82f7": "reduce consumer costs", + "5726f0e35951b619008f82f8": "Canada", + "5726f0e35951b619008f82f9": "international drug suppliers", + "5726f0e35951b619008f82fa": "There is no known case of any U.S. citizens buying Canadian drugs for personal use with a prescription, who has ever been charged by authorities.", + "5726f0e35951b619008f82fb": "legalize importation of medications", + "5a6ce9ab4eec6b001a80a6c0": "", + "5a6ce9ab4eec6b001a80a6c1": "", + "5a6ce9ab4eec6b001a80a6c2": "", + "5a6ce9ab4eec6b001a80a6c3": "", + "5726f2375951b619008f830f": "pharmacy practice science and applied information science", + "5726f2375951b619008f8310": "information technology departments", + "5726f2375951b619008f8311": "national and international patient information projects and health system interoperability goals", + "5726f2375951b619008f8312": "many practice areas of pharmacy", + "5726f2375951b619008f8313": "quickly", + "5a6ceb164eec6b001a80a6c8": "", + "5a6ceb164eec6b001a80a6c9": "", + "5a6ceb164eec6b001a80a6ca": "", + "5a6ceb164eec6b001a80a6cb": "", + "5726f36cdd62a815002e95fe": "Specialty pharmacies", + "5726f36cdd62a815002e95ff": "19 of 28", + "5726f36cdd62a815002e9600": "chronic and complex", + "5726f36cdd62a815002e9601": "high cost injectable, oral, infused, or inhaled", + "5726f36cdd62a815002e9602": "lab monitoring, adherence counseling", + "5a6ceb7a4eec6b001a80a6d0": "", + "5a6ceb7a4eec6b001a80a6d1": "", + "5a6ceb7a4eec6b001a80a6d2": "", + "5a6ceb7a4eec6b001a80a6d3": "", + "5726f48df1498d1400e8f0da": "separately", + "5726f48df1498d1400e8f0db": "pharmacists", + "5726f48df1498d1400e8f0dc": "American Medical Association (AMA) Code of Ethics", + "5726f48df1498d1400e8f0dd": "7 to 10 percent", + "5726f48df1498d1400e8f0de": "", + "5a6cecdb4eec6b001a80a6d8": "", + "5a6cecdb4eec6b001a80a6d9": "", + "5a6cecdb4eec6b001a80a6db": "", + "5726f635dd62a815002e9656": "rural areas in the United Kingdom", + "5726f635dd62a815002e9657": "Austria", + "5726f635dd62a815002e9658": "1.6 kilometres", + "5726f635dd62a815002e9659": "1.6 kilometres", + "5a6ced7d4eec6b001a80a6e0": "", + "5a6ced7d4eec6b001a80a6e1": "", + "5a6ced7d4eec6b001a80a6e2": "", + "5a6ced7d4eec6b001a80a6e3": "", + "5726f7715951b619008f838d": "high risk of a conflict of interest and/or the avoidance of absolute powers", + "5726f7715951b619008f838e": "financial self-interest", + "5726f7715951b619008f838f": "", + "5726f7715951b619008f8390": "directly conflicts with the patient's interest in obtaining cost-effective medication", + "5726f7715951b619008f8391": "he or she can then sell more medications to the patient", + "5a6cee244eec6b001a80a6e8": "", + "5a6cee244eec6b001a80a6e9": "", + "5a6cee244eec6b001a80a6ea": "", + "5a6cee244eec6b001a80a6eb": "", + "5a6cee244eec6b001a80a6ec": "", + "5726f868dd62a815002e9684": "more integral within the health care system", + "5726f868dd62a815002e9685": "compensated for their patient care skills", + "5726f868dd62a815002e9686": "clinical services that pharmacists can provide for their patients", + "5726f868dd62a815002e9687": "prescription, non-prescription, and herbals", + "5726f868dd62a815002e9688": "increased patient health outcomes", + "5a6ceec84eec6b001a80a6f2": "", + "5a6ceec84eec6b001a80a6f3": "", + "5a6ceec84eec6b001a80a6f4": "", + "5a6ceec84eec6b001a80a6f5": "", + "5a6ceec84eec6b001a80a6f6": "", + "5726f96ddd62a815002e9698": "Alberta and British Columbia", + "5726f96ddd62a815002e9699": "the Australian Government", + "5726f96ddd62a815002e969a": "medicine use reviews", + "5726f96ddd62a815002e969b": "pharmaceutical care or clinical pharmacy", + "5726f96ddd62a815002e969c": "Doctor of Pharmacy", + "5a6cef5a4eec6b001a80a6fc": "", + "5a6cef5a4eec6b001a80a6fd": "", + "5a6cef5a4eec6b001a80a6fe": "", + "5a6cef5a4eec6b001a80a6ff": "", + "5a6cef5a4eec6b001a80a700": "", + "5726fa525951b619008f83f7": "mortar and pestle and the \u211e (recipere) character", + "5726fa525951b619008f83f8": "The show globe", + "5726fa525951b619008f83f9": "Netherlands", + "5726fa525951b619008f83fa": "Germany and Austria", + "5726fa525951b619008f83fb": "France, Argentina, the United Kingdom, Belgium, Ireland, Italy, Spain, and India", + "5a6cefd64eec6b001a80a706": "", + "5a6cefd64eec6b001a80a707": "", + "5a6cefd64eec6b001a80a708": "", + "5a6cefd64eec6b001a80a709": "", + "5a6cefd64eec6b001a80a70a": "", + "57271c235951b619008f860b": "Civil disobedience", + "57271c235951b619008f860c": "fight against apartheid", + "57271c235951b619008f860d": "the Singing Revolution", + "57271c235951b619008f860e": "Ukraine", + "57271c235951b619008f860f": "Georgia", + "5728d4c03acd2414000dff9f": "Egyptians", + "5728d4c03acd2414000dffa0": "Egyptians", + "5728d4c03acd2414000dffa1": "unfair laws", + "5728d4c03acd2414000dffa2": "unfair laws", + "5728d4c03acd2414000dffa3": "the Singing Revolution", + "5a66413dc2b11c001a425ec7": "", + "5a66413dc2b11c001a425ec8": "to oust their communist governments", + "5a66413dc2b11c001a425ec9": "", + "5a66413dc2b11c001a425eca": "", + "5a66413dc2b11c001a425ecb": "Czechoslovakia", + "57271f125951b619008f8635": "Antigone", + "57271f125951b619008f8636": "", + "57271f125951b619008f8637": "Creon", + "57271f125951b619008f8638": "Antigone", + "57271f125951b619008f8639": "giving her brother Polynices a proper burial", + "5728d5793acd2414000dffb3": "Antigone", + "5728d5793acd2414000dffb4": "Sophocles", + "5728d5793acd2414000dffb5": "Creon", + "5728d5793acd2414000dffb6": "", + "5728d5793acd2414000dffb7": "Antigone, one of the daughters of former King of Thebes, Oedipus, defies Creon", + "5a664314c2b11c001a425ed9": "", + "5a664314c2b11c001a425eda": "", + "5a664314c2b11c001a425edb": "Creon", + "5a664314c2b11c001a425edc": "trying to stop her from giving her brother Polynices a proper burial", + "5a664314c2b11c001a425edd": "", + "5727213c708984140094da35": "Percy Shelley", + "5727213c708984140094da36": "nonviolent", + "5727213c708984140094da37": "Henry David Thoreau", + "5727213c708984140094da38": "Satyagraha", + "5727213c708984140094da39": "campaign for a free India", + "5728d63c4b864d1900164f18": "", + "5728d63c4b864d1900164f19": "", + "5728d63c4b864d1900164f1a": "nonviolent protest", + "5728d63c4b864d1900164f1b": "", + "5728d63c4b864d1900164f1c": "", + "5a664447c2b11c001a425eeb": "", + "5a664447c2b11c001a425eec": "", + "5a664447c2b11c001a425eed": "", + "5a664447c2b11c001a425eee": "the images of what he thought to be the unjust forms of authority of his time", + "5a664447c2b11c001a425eef": "", + "572726c9708984140094da7b": "muggers, arsonists, draft evaders, campaign hecklers, campus militants, anti-war demonstrators, juvenile delinquents and political assassins", + "572726c9708984140094da7c": "ambiguity", + "572726c9708984140094da7d": "debased", + "572726c9708984140094da7e": "Marshall Cohen", + "5728d6f02ca10214002da90e": "become utterly debased", + "5728d6f02ca10214002da90f": "Marshall Cohen", + "5728d6f02ca10214002da910": "debased", + "5728d6f02ca10214002da911": "ambiguity", + "5728d6f02ca10214002da912": "ambiguity", + "5a664612c2b11c001a425f09": "", + "5a664612c2b11c001a425f0a": "", + "5a664612c2b11c001a425f0b": "", + "5a664612c2b11c001a425f0c": "", + "5a664612c2b11c001a425f0d": "a federal official", + "572807802ca10214002d9bf8": "LeGrande", + "572807802ca10214002d9bf9": "", + "572807802ca10214002d9bfa": "", + "572807802ca10214002d9bfb": "semantical", + "572807802ca10214002d9bfc": "", + "5728d7c54b864d1900164f4c": "", + "5728d7c54b864d1900164f4d": "voluminous", + "5728d7c54b864d1900164f4e": "", + "5728d7c54b864d1900164f4f": "violent", + "5728d7c54b864d1900164f50": "violent", + "5a6647d2c2b11c001a425f1d": "", + "5a6647d2c2b11c001a425f1e": "", + "5a6647d2c2b11c001a425f1f": "", + "5a6647d2c2b11c001a425f20": "", + "5a6647d2c2b11c001a425f21": "", + "57280f974b864d1900164370": "civil disobedience", + "57280f974b864d1900164371": "private citizen", + "57280f974b864d1900164372": "relation to the state and its laws", + "57280f974b864d1900164373": "", + "57280f974b864d1900164374": "", + "5728d9403acd2414000e001b": "a citizen's relation to the state and its laws", + "5728d9403acd2414000e001c": "", + "5728d9403acd2414000e001d": "private citizen", + "5728d9403acd2414000e001e": "private citizen", + "5728d9403acd2414000e001f": "", + "5a665002846392001a1e1ab3": "two equally sovereign branches of government", + "5a665002846392001a1e1ab4": "the state and its laws", + "5a665002846392001a1e1ab5": "", + "5a665002846392001a1e1ab6": "", + "5a665002846392001a1e1ab7": "", + "572812e74b864d19001643ce": "Thoreau", + "572812e74b864d19001643cf": "Resign", + "572812e74b864d19001643d0": "", + "572812e74b864d19001643d1": "Resign", + "572812e74b864d19001643d2": "a postman or tax collector", + "5728dafe3acd2414000e005d": "The individual", + "5728dafe3acd2414000e005e": "individuals act, only individuals", + "5728dafe3acd2414000e005f": "", + "5728dafe3acd2414000e0060": "Resign", + "5728dafe3acd2414000e0061": "it is not necessarily right", + "5a665142846392001a1e1abd": "", + "5a665142846392001a1e1abe": "", + "5a665142846392001a1e1abf": "", + "5a665142846392001a1e1ac0": "", + "5a665142846392001a1e1ac1": "", + "5728151b4b864d1900164428": "governmental entities", + "5728151b4b864d1900164429": "trade unions, banks, and private universities", + "5728151b4b864d190016442a": "non-governmental agencies", + "5728151b4b864d190016442b": "", + "5728dc2d3acd2414000e007f": "civil disobedience is only justified against governmental entities", + "5728dc2d3acd2414000e0080": "", + "5728dc2d3acd2414000e0081": "", + "5728dc2d3acd2414000e0083": "", + "5a665338846392001a1e1ac7": "Brownlee", + "5a665338846392001a1e1ac8": "", + "5a665338846392001a1e1ac9": "", + "5a665338846392001a1e1aca": "breaches of law", + "5a665338846392001a1e1acb": "", + "572818f54b864d190016446c": "civil disobedience", + "572818f54b864d190016446d": "lawbreaking", + "572818f54b864d190016446e": "", + "572818f54b864d190016446f": "Book of Exodus", + "572818f54b864d1900164470": "Shiphrah and Puah", + "5728dddc2ca10214002da9d2": "", + "5728dddc2ca10214002da9d3": "rules that conflict with morality", + "5728dddc2ca10214002da9d4": "assisting in fabricating evidence or committing perjury", + "5728dddc2ca10214002da9d5": "", + "5728dddc2ca10214002da9d6": "Book of Exodus", + "5a665549846392001a1e1ad5": "", + "5a665549846392001a1e1ad6": "", + "5a665549846392001a1e1ad7": "", + "5a665549846392001a1e1ad8": "", + "5a665549846392001a1e1ad9": "", + "57281c594b864d19001644a2": "non-violent", + "57281c594b864d19001644a3": "Black's Law", + "57281c594b864d19001644a4": "rebellion", + "57281c594b864d19001644a5": "", + "57281c594b864d19001644a6": "non-violent", + "5728df634b864d1900164fe2": "", + "5728df634b864d1900164fe3": "", + "5728df634b864d1900164fe4": "refusal to submit to arrest", + "5728df634b864d1900164fe6": "", + "5a665747846392001a1e1ae9": "refraining from violence", + "5a665747846392001a1e1aea": "", + "5a665747846392001a1e1aeb": "", + "5a665747846392001a1e1aec": "", + "5a665747846392001a1e1aed": "rebellion is much more destructive", + "5728202c4b864d19001644ec": "Revolutionary civil disobedience", + "5728202c4b864d19001644ed": "Hungarians", + "5728202c4b864d19001644ee": "Ferenc De\u00e1k", + "5728202c4b864d19001644ef": "", + "5728202c4b864d19001644f0": "", + "5728e07e3acd2414000e00e9": "Non-revolutionary", + "5728e07e3acd2414000e00ea": "they are judged \"wrong\" by an individual conscience", + "5728e07e3acd2414000e00eb": "", + "5728e07e3acd2414000e00ec": "", + "5728e07e3acd2414000e00ed": "", + "5a665870846392001a1e1af3": "a government", + "5a665870846392001a1e1af4": "", + "5a665870846392001a1e1af5": "", + "5a665870846392001a1e1af6": "", + "5a665870846392001a1e1af7": "", + "572822233acd2414000df555": "during the Roman Empire", + "572822233acd2414000df556": "Unarmed Jews gathered in the streets", + "572822233acd2414000df557": "his arrest was not covered in any newspapers in the days, weeks and months after it happened. The tax collector who arrested him rose to higher political office", + "572822233acd2414000df558": "higher political office", + "572822233acd2414000df559": "after the end of the Mexican War", + "5728e3c33acd2414000e0131": "the Roman Empire", + "5728e3c33acd2414000e0132": "to prevent the installation of pagan images in the Temple in Jerusalem", + "5728e3c33acd2414000e0133": "jail solidarity", + "5728e3c33acd2414000e0134": "jail solidarity", + "5728e3c33acd2414000e0135": "", + "5a6659d3846392001a1e1b0d": "", + "5a6659d3846392001a1e1b0e": "", + "5a6659d3846392001a1e1b0f": "bail", + "5a6659d3846392001a1e1b10": "", + "5a6659d3846392001a1e1b11": "", + "572825a92ca10214002d9efe": "illegal acts", + "572825a92ca10214002d9eff": "propaganda", + "572825a92ca10214002d9f00": "illegal medical cannabis dispensaries and Voice in the Wilderness", + "572825a92ca10214002d9f01": "738 days", + "572825a92ca10214002d9f02": "successfully preventing it from being cut down", + "5728e5224b864d1900165032": "a harassment", + "5728e5224b864d1900165033": "trespassing at a nuclear-missile installation", + "5728e5224b864d1900165034": "a harassment", + "5728e5224b864d1900165035": "", + "5728e5224b864d1900165036": "Julia Butterfly Hill", + "5a665b56846392001a1e1b1d": "", + "5a665b56846392001a1e1b1e": "", + "5a665b56846392001a1e1b1f": "", + "5a665b56846392001a1e1b20": "", + "5a665b56846392001a1e1b21": "", + "5728284e3acd2414000df5cd": "sending an email to the Lebanon, New Hampshire city councilors stating, \"Wise up or die.\"", + "5728284e3acd2414000df5ce": "Wise up or die", + "5728284e3acd2414000df5cf": "forbidden speech", + "5728284e3acd2414000df5d0": "1978 Supreme Court case of FCC v. Pacifica Foundation", + "5728284e3acd2414000df5d1": "", + "5728e5f43acd2414000e0171": "", + "5728e5f43acd2414000e0172": "Threatening government officials", + "5728e5f43acd2414000e0173": "Threatening government officials", + "5728e5f43acd2414000e0174": "engaging in the forbidden speech", + "5a666b43846392001a1e1c0f": "", + "5a666b43846392001a1e1c10": "", + "5a666b43846392001a1e1c11": "", + "5a666b43846392001a1e1c12": "FCC v. Pacifica Foundation", + "5a666b43846392001a1e1c13": "Threatening government officials", + "57282dfb4b864d1900164668": "more difficult for a system to function", + "57282dfb4b864d1900164669": "padlocking the gates", + "57282dfb4b864d190016466a": "padlocking the gates and using sickles to deflate one of the large domes covering two satellite dishes", + "57282dfb4b864d190016466b": "moral dialogue", + "57282dfb4b864d190016466c": "", + "5728e715ff5b5019007da914": "civil", + "5728e715ff5b5019007da916": "illegal boycotts", + "5728e715ff5b5019007da917": "engage in moral dialogue", + "5728e715ff5b5019007da918": "", + "5a6681d1f038b7001ab0bf00": "", + "5a6681d1f038b7001ab0bf01": "", + "5a6681d1f038b7001ab0bf02": "padlocking the gates", + "5a6681d1f038b7001ab0bf03": "limited coercion", + "5a6681d1f038b7001ab0bf04": "", + "5728e8212ca10214002daa6c": "criminal", + "5728e8212ca10214002daa6d": "", + "5728e8212ca10214002daa6e": "", + "5728e8212ca10214002daa6f": "", + "5728e8212ca10214002daa70": "fear of seeming rude", + "5a6683d5f038b7001ab0bf1e": "", + "5a6683d5f038b7001ab0bf1f": "", + "5a6683d5f038b7001ab0bf20": "", + "5a6683d5f038b7001ab0bf21": "", + "5a6683d5f038b7001ab0bf22": "", + "5728eb1a3acd2414000e01c5": "", + "5728eb1a3acd2414000e01c6": "", + "5728eb1a3acd2414000e01c7": "", + "5728eb1a3acd2414000e01c8": "anarchists", + "5728eb1a3acd2414000e01c9": "a violation of criminal law that does not infringe the rights of others", + "5a668632f038b7001ab0bf44": "", + "5a668632f038b7001ab0bf45": "", + "5a668632f038b7001ab0bf46": "legitimacy of any government", + "5a668632f038b7001ab0bf47": "", + "5a668632f038b7001ab0bf48": "", + "5728ebcb3acd2414000e01d9": "whether or not to plead guilty", + "5728ebcb3acd2414000e01da": "submit to the punishment prescribed by law", + "5728ebcb3acd2414000e01db": "illegally protesting nuclear power", + "5728ebcb3acd2414000e01dc": "Guilt implies wrong-doing", + "5728ebcb3acd2414000e01dd": "", + "5a66893ff038b7001ab0bf74": "", + "5a66893ff038b7001ab0bf75": "", + "5a66893ff038b7001ab0bf76": "", + "5a66893ff038b7001ab0bf77": "", + "5a66893ff038b7001ab0bf78": "not guilty", + "5728ec6a4b864d19001650aa": "Camp Mercury nuclear test site", + "5728ec6a4b864d19001650ab": "", + "5728ec6a4b864d19001650ac": "arrest", + "5728ec6a4b864d19001650ad": "nolo contendere", + "5728ec6a4b864d19001650ae": "suspended", + "5a668b33f038b7001ab0bf90": "", + "5a668b33f038b7001ab0bf91": "", + "5a668b33f038b7001ab0bf92": "13", + "5a668b33f038b7001ab0bf93": "", + "5a668b33f038b7001ab0bf94": "suspended sentences", + "5728ed94ff5b5019007da97c": "reminding their countrymen of injustice", + "5728ed94ff5b5019007da97d": "", + "5728ed94ff5b5019007da97e": "", + "5728ed94ff5b5019007da97f": "", + "5a668d4ef038b7001ab0bfc0": "", + "5a668d4ef038b7001ab0bfc1": "the spirit of protest should be maintained all the way", + "5a668d4ef038b7001ab0bfc2": "a guilty plea", + "5a668d4ef038b7001ab0bfc3": "", + "5a668d4ef038b7001ab0bfc4": "", + "5728eef92ca10214002daab0": "misdemeanor count", + "5728eef92ca10214002daab1": "plead guilty to one misdemeanor count", + "5728eef92ca10214002daab2": "solidarity tactics", + "5728eef92ca10214002daab3": "civil", + "5728eef92ca10214002daab4": "Mohandas Gandhi", + "5a668ef8f038b7001ab0bfdc": "plea bargain to civil disobedients", + "5a668ef8f038b7001ab0bfdd": "activists", + "5a668ef8f038b7001ab0bfde": "", + "5a668ef8f038b7001ab0bfdf": "", + "5a668ef8f038b7001ab0bfe0": "the defendants were offered an opportunity to plead guilty to one misdemeanor count and receive no jail time", + "5728f50baf94a219006a9e55": "make a defiant speech, or a speech explaining their actions, in allocution", + "5728f50baf94a219006a9e56": "explaining their actions", + "5728f50baf94a219006a9e57": "lack of remorse, an attempt to avoid responsibility for her actions, and even a likelihood of repeating her illegal actions", + "5728f50baf94a219006a9e58": "", + "5728f50baf94a219006a9e59": "allocution", + "5a66938ff038b7001ab0bff8": "", + "5a66938ff038b7001ab0bff9": "", + "5a66938ff038b7001ab0bffa": "", + "5a66938ff038b7001ab0bffb": "", + "5a66938ff038b7001ab0bffc": "the ones who are violating the greater law", + "5728facd4b864d1900165170": "to win an acquittal and avoid imprisonment or a fine", + "5728facd4b864d1900165171": "", + "5728facd4b864d1900165172": "seek jury nullification", + "5728facd4b864d1900165173": "", + "5728facd4b864d1900165174": "", + "5a66978af038b7001ab0c028": "", + "5a66978af038b7001ab0c029": "", + "5a66978af038b7001ab0c02a": "to win an acquittal and avoid imprisonment or a fine", + "5a66978af038b7001ab0c02b": "the judge need not allow defendants to openly seek jury nullification", + "5a66978af038b7001ab0c02c": "", + "5728fb6a1d04691400778ef5": "", + "5728fb6a1d04691400778ef6": "neither conscientious nor of social benefit", + "5728fb6a1d04691400778ef7": "breaking the law for self-gratification", + "5728fb6a1d04691400778ef8": "attempts to escape punishment by committing the crime covertly and avoiding attribution, or by denying having committed the crime, or by fleeing the jurisdiction", + "5728fb6a1d04691400778ef9": "", + "5a669ee5f038b7001ab0c068": "", + "5a669ee5f038b7001ab0c069": "", + "5a669ee5f038b7001ab0c06a": "", + "5a669ee5f038b7001ab0c06b": "must be punished", + "5a669ee5f038b7001ab0c06c": "", + "5728fc9e1d04691400778f11": "Indirect civil disobedience", + "5728fc9e1d04691400778f12": "direct civil disobedience", + "5728fc9e1d04691400778f13": "", + "5728fc9e1d04691400778f14": "necessity", + "5728fc9e1d04691400778f15": "", + "5a66a156f038b7001ab0c072": "breaking that law", + "5a66a156f038b7001ab0c073": "protesting the existence of a particular law by breaking that law", + "5a66a156f038b7001ab0c074": "Fully Informed Jury Association activists", + "5a66a156f038b7001ab0c075": "", + "5a66a156f038b7001ab0c076": "the leaflets will have to be given to the leafleter's own jury as evidence", + "5728fd3c3f37b31900477f2b": "", + "5728fd3c3f37b31900477f2d": "", + "5728fd3c3f37b31900477f2e": "", + "5728fd3c3f37b31900477f2f": "", + "5a66a55af038b7001ab0c07c": "", + "5a66a55af038b7001ab0c07d": "", + "5a66a55af038b7001ab0c07e": "", + "5a66a55af038b7001ab0c07f": "", + "5a66a55af038b7001ab0c080": "", + "57273a465951b619008f86ff": "Construction", + "57273a465951b619008f8700": "manufacturing", + "57273a465951b619008f8701": "six to nine percent", + "57273a465951b619008f8702": "planning,[citation needed] design, and financing", + "57273a465951b619008f8703": "a known client", + "5a234eef82b03a001a4aa76a": "", + "5a234eef82b03a001a4aa76b": "", + "5a234eef82b03a001a4aa76c": "", + "5a234eef82b03a001a4aa76d": "planning,[citation needed] design, and financing", + "5a25a709ef59cd001a623c0e": "", + "5a25a709ef59cd001a623c0f": "", + "5a25a709ef59cd001a623c10": "", + "5a25a709ef59cd001a623c11": "", + "5a25a709ef59cd001a623c12": "", + "57273cca708984140094db33": "An architect", + "57273cca708984140094db34": "An architect", + "57273cca708984140094db35": "effective planning", + "57273cca708984140094db36": "megaprojects", + "57273cca708984140094db37": "Those involved with the design and execution of the infrastructure in question", + "5a2350d582b03a001a4aa773": "", + "5a2350d582b03a001a4aa774": "", + "5a2350d582b03a001a4aa775": "megaprojects", + "5a2350d582b03a001a4aa776": "", + "5a25a8e9ef59cd001a623c20": "", + "5a25a8e9ef59cd001a623c21": "An architect", + "5a25a8e9ef59cd001a623c22": "", + "5a25a8e9ef59cd001a623c23": "", + "5a25a8e9ef59cd001a623c24": "effective planning", + "57273d8bf1498d1400e8f4fe": "buildings, infrastructure and industrial", + "57273d8bf1498d1400e8f4ff": "residential and non-residential (commercial/institutional)", + "57273d8bf1498d1400e8f500": "heavy/highway, heavy civil or heavy engineering", + "57273d8bf1498d1400e8f501": "Infrastructure", + "57273d8bf1498d1400e8f502": "Industrial", + "5a2352f782b03a001a4aa77b": "", + "5a2352f782b03a001a4aa77c": "", + "5a2352f782b03a001a4aa77d": "", + "5a2352f782b03a001a4aa77e": "", + "5a25ab1bef59cd001a623c32": "", + "5a25ab1bef59cd001a623c33": "", + "5a25ab1bef59cd001a623c34": "", + "5a25ab1bef59cd001a623c35": "", + "5a25ab1bef59cd001a623c36": "", + "57273e50dd62a815002e9a02": "a trade magazine for the construction industry", + "57273e50dd62a815002e9a03": "ENR", + "57273e50dd62a815002e9a04": "2014", + "57273e50dd62a815002e9a05": "transportation, sewer, hazardous waste and water", + "5a23548782b03a001a4aa783": "", + "5a23548782b03a001a4aa784": "", + "5a23548782b03a001a4aa785": "a list the largest global firms (Top-250, by amount of work they are doing outside their home country", + "5a23548782b03a001a4aa786": "", + "5a23548782b03a001a4aa787": "", + "5a25ade0ef59cd001a623c44": "", + "5a25ade0ef59cd001a623c45": "", + "5a25ade0ef59cd001a623c46": "", + "5a25ade0ef59cd001a623c47": "", + "5a25ade0ef59cd001a623c48": "2014", + "57273f27dd62a815002e9a0a": "building construction, heavy and civil engineering construction, and specialty trade contractors", + "57273f27dd62a815002e9a0b": "construction service firms", + "57273f27dd62a815002e9a0c": "The Standard Industrial Classification and the newer North American Industry Classification System", + "57273f27dd62a815002e9a0d": "firms engaged in managing construction projects without assuming direct financial responsibility for completion of the construction project", + "5a23565482b03a001a4aa78d": "building construction, heavy and civil engineering construction, and specialty trade contractors", + "5a23565482b03a001a4aa78e": "", + "5a23565482b03a001a4aa78f": "", + "5a23565482b03a001a4aa790": "", + "5a25b230ef59cd001a623c4e": "", + "5a25b230ef59cd001a623c4f": "", + "5a25b230ef59cd001a623c50": "building construction, heavy and civil engineering construction, and specialty trade contractors", + "5a25b230ef59cd001a623c51": "assuming direct financial responsibility for completion of the construction project", + "5a25b230ef59cd001a623c52": "", + "57274046dd62a815002e9a12": "Building construction", + "57274046dd62a815002e9a13": "small renovations", + "57274046dd62a815002e9a14": "the owner of the property", + "57274046dd62a815002e9a15": "structural collapse, cost overruns, and/or litigation", + "57274046dd62a815002e9a16": "make detailed plans and maintain careful oversight", + "5a2358cc82b03a001a4aa795": "small renovations", + "5a2358cc82b03a001a4aa796": "", + "5a2358cc82b03a001a4aa797": "", + "5a2358cc82b03a001a4aa798": "", + "5a25b668ef59cd001a623c76": "", + "5a25b668ef59cd001a623c77": "", + "5a25b668ef59cd001a623c78": "", + "5a25b668ef59cd001a623c79": "", + "5a25b668ef59cd001a623c7a": "", + "572742bd5951b619008f8785": "local building authority regulations and codes of practice", + "572742bd5951b619008f8786": "Materials readily available in the area", + "572742bd5951b619008f8787": "", + "572742bd5951b619008f8788": "Cost of construction on a per square meter (or per square foot) basis for houses", + "5a25bb0bef59cd001a623cb2": "", + "5a25bb0bef59cd001a623cb3": "", + "5a25bb0bef59cd001a623cb4": "", + "5a25bb0bef59cd001a623cb5": "", + "5a25bb0bef59cd001a623cb6": "", + "572744aff1498d1400e8f588": "3D printing technology", + "572744aff1498d1400e8f589": "20 hours", + "572744aff1498d1400e8f58a": "2014", + "572744aff1498d1400e8f58b": "2 metres (6 ft 7 in)", + "5a25bd5cef59cd001a623cc4": "", + "5a25bd5cef59cd001a623cc5": "", + "5a25bd5cef59cd001a623cc6": "", + "5a25bd5cef59cd001a623cc7": "", + "5a25bd5cef59cd001a623cc8": "", + "572745c6708984140094db99": "designs into reality", + "572745c6708984140094db9a": "plan the physical proceedings", + "572745c6708984140094db9b": "the property owner", + "572745c6708984140094db9c": "quantity surveyor", + "572745c6708984140094db9d": "the most cost efficient bidder", + "5a25c087ef59cd001a623cce": "", + "5a25c087ef59cd001a623ccf": "", + "5a25c087ef59cd001a623cd1": "", + "5a25c087ef59cd001a623cd2": "", + "57274e0d708984140094dbe5": "previously separated specialties", + "57274e0d708984140094dbe6": "entirely separate companies", + "57274e0d708984140094dbe7": "one-stop shopping", + "57274e0d708984140094dbe8": "design build", + "5a25c41def59cd001a623cd8": "", + "5a25c41def59cd001a623cd9": "experts from all related fields", + "5a25c41def59cd001a623cda": "", + "5a25c41def59cd001a623cdb": "", + "5a25c41def59cd001a623cdc": "", + "57274e975951b619008f87f9": "design-build, partnering and construction management", + "57274e975951b619008f87fa": "architects, interior designers, engineers and constructors", + "57274e975951b619008f87fb": "establishing relationships with other necessary participants", + "5a25d23bef59cd001a623ce2": "", + "5a25d23bef59cd001a623ce3": "Several project structures", + "5a25d23bef59cd001a623ce4": "architects, interior designers, engineers and constructors", + "5a25d23bef59cd001a623ce5": "", + "5a25d23bef59cd001a623ce6": "", + "57274f67708984140094dbf5": "preventable financial problems", + "57274f67708984140094dbf6": "builders ask for too little money to complete the project", + "57274f67708984140094dbf7": "when the present amount of funding cannot cover the current costs for labour and materials", + "57274f67708984140094dbf8": "Fraud", + "5a25d529ef59cd001a623cec": "", + "5a25d529ef59cd001a623ced": "", + "5a25d529ef59cd001a623cee": "", + "5a25d529ef59cd001a623cef": "Financial planning", + "5a25d529ef59cd001a623cf0": "", + "5727502f708984140094dc07": "Mortgage bankers, accountants, and cost engineers", + "5727502f708984140094dc08": "the mortgage banker", + "5727502f708984140094dc09": "Accountants act", + "5727502f708984140094dc0a": "Cost engineers and estimators", + "5727502f708984140094dc0b": "identified change orders or project changes that increased costs", + "5a25d89aef59cd001a623cf6": "the owner's equity in the property is the most obvious source of funding for a building project. Accountants act to study the expected monetary flow", + "5a25d89aef59cd001a623cf7": "Cost overruns with government projects have occurred when the contractor identified change orders or project changes that increased costs", + "5a25d89aef59cd001a623cf8": "the contractor identified change orders or project changes that increased costs", + "5a25d89aef59cd001a623cf9": "the mortgage banker", + "5a25d89aef59cd001a623cfa": "the owner's equity in the property", + "572750e8dd62a815002e9af0": "zoning and building code requirements", + "572750e8dd62a815002e9af1": "the owner", + "572750e8dd62a815002e9af2": "the desire to prevent things that are indisputably bad \u2013 bridge collapses or explosions", + "572750e8dd62a815002e9af3": "things that are a matter of custom or expectation", + "572750e8dd62a815002e9af4": "An attorney", + "5a25e0a9ef59cd001a623d00": "", + "5a25e0a9ef59cd001a623d01": "", + "5a25e0a9ef59cd001a623d02": "", + "5a25e0a9ef59cd001a623d03": "", + "5a25e0a9ef59cd001a623d04": "isolating businesses to a business district and residences to a residential district", + "572751b4708984140094dc1b": "A construction project", + "572751b4708984140094dc1c": "A contract", + "572751b4708984140094dc1d": "a delay costs money", + "572751b4708984140094dc1e": "that each side is capable of performing the obligations set out", + "572751b4708984140094dc1f": "poorly drafted contracts", + "5a25e4a2ef59cd001a623d0a": "", + "5a25e4a2ef59cd001a623d0b": "", + "5a25e4a2ef59cd001a623d0c": "", + "5a25e4a2ef59cd001a623d0d": "", + "5a25e4a2ef59cd001a623d0e": "", + "5727526cdd62a815002e9b0e": "relationship contracting", + "5727526cdd62a815002e9b0f": "Public-Private Partnering", + "5727526cdd62a815002e9b10": "Public-Private Partnering", + "5727526cdd62a815002e9b11": "co-operation", + "5a25e8d5ef59cd001a623d14": "", + "5a25e8d5ef59cd001a623d15": "", + "5a25e8d5ef59cd001a623d16": "", + "5a25e8d5ef59cd001a623d17": "", + "5a25e8d5ef59cd001a623d18": "highly competitive and adversarial practices", + "572753335951b619008f8853": "the architect or engineer", + "572753335951b619008f8854": "the architect or engineer", + "572753335951b619008f8855": "the architect's client and the main contractor", + "572753335951b619008f8856": "the main contractor", + "572753335951b619008f8857": "the building is ready to occupy", + "5a25eae4c93d92001a40033d": "", + "5a25eae4c93d92001a40033e": "", + "5a25eae4c93d92001a40033f": "", + "5a25eae4c93d92001a400340": "direct contractual links", + "5a25eae4c93d92001a400341": "", + "57275411dd62a815002e9b30": "The owner", + "57275411dd62a815002e9b31": "Several D&B contractors", + "57275411dd62a815002e9b32": "The owner", + "57275411dd62a815002e9b33": "a consortium of several contractors", + "57275411dd62a815002e9b34": "they design phase 2", + "5a25eed2c93d92001a400347": "", + "5a25eed2c93d92001a400348": "a list of requirements", + "5a25eed2c93d92001a400349": "building the first phase of the project", + "5a25eed2c93d92001a40034a": "", + "5a25eed2c93d92001a40034b": "the project is completely designed by the owner, then bid on, then completed", + "572754fff1498d1400e8f660": "contractors", + "572754fff1498d1400e8f661": "damage", + "572754fff1498d1400e8f662": "", + "572754fff1498d1400e8f663": "the municipal building inspector", + "572754fff1498d1400e8f664": "an occupancy permit", + "5a25f133c93d92001a400351": "an occupancy permit may be issued", + "5a25f133c93d92001a400352": "inspects the building periodically", + "5a25f133c93d92001a400353": "", + "5a25f133c93d92001a400354": "the construction adheres to the approved plans and the local building code", + "5a25f133c93d92001a400355": "the building periodically", + "572755b7708984140094dc4d": "$960 billion", + "572755b7708984140094dc4e": "$680 billion", + "572755b7708984140094dc4f": "667,000", + "572755b7708984140094dc50": "fewer than 10", + "572755b7708984140094dc51": "828,000", + "5a25f38dc93d92001a40035b": "", + "5a25f38dc93d92001a40035c": "", + "5a25f38dc93d92001a40035d": "", + "5a25f38dc93d92001a40035e": "", + "5a25f38dc93d92001a40035f": "", + "5727565ef1498d1400e8f674": "\u00a342,090", + "5727565ef1498d1400e8f675": "\u00a326,719", + "5727565ef1498d1400e8f676": "US/Canada", + "5a25f6a3c93d92001a400365": "\u00a342,090", + "5a25f6a3c93d92001a400366": "\u00a343,389 per annum", + "5a25f6a3c93d92001a400367": "$100,000", + "5a25f6a3c93d92001a400368": "", + "5a25f6a3c93d92001a400369": "", + "572756fe708984140094dc71": "Construction", + "572756fe708984140094dc72": "Falls", + "572756fe708984140094dc73": "electrocution, transportation accidents, and trench cave-ins", + "572756fe708984140094dc74": "Proper safety equipment such as harnesses and guardrails and procedures such as securing ladders and inspecting scaffolding", + "5a25fa34c93d92001a40036f": "", + "5a25fa34c93d92001a400370": "nearly three times that for all workers", + "5a25fa34c93d92001a400371": "", + "5a25fa34c93d92001a400372": "securing ladders and inspecting scaffolding", + "5a25fa34c93d92001a400373": "", + "572746addd62a815002e9a5e": "independent schools", + "572746addd62a815002e9a5f": "academic scholarship", + "572746addd62a815002e9a60": "charging their students tuition", + "572746addd62a815002e9a61": "to select their students and are funded in whole or in part by charging their students tuition", + "5a6787d4f038b7001ab0c27a": "", + "5a6787d4f038b7001ab0c27b": "", + "5a6787d4f038b7001ab0c27c": "", + "5a6787d4f038b7001ab0c27d": "", + "5a6787d4f038b7001ab0c27e": "", + "57274712708984140094dbad": "$45,000", + "57274712708984140094dbae": "tuition-free", + "57274712708984140094dbaf": "", + "57274712708984140094dbb0": "North America", + "5a678908f038b7001ab0c296": "", + "5a678908f038b7001ab0c297": "", + "5a678908f038b7001ab0c298": "", + "5a678908f038b7001ab0c299": "tuition-free", + "5a678908f038b7001ab0c29a": "", + "5727478cf1498d1400e8f59a": "lower sixth", + "5727478cf1498d1400e8f59b": "upper sixth", + "5727478cf1498d1400e8f59c": "prep schools", + "5727478cf1498d1400e8f59d": "peer tuitions", + "5727478cf1498d1400e8f59e": "the best teachers", + "5a678aa6f038b7001ab0c2a0": "", + "5a678aa6f038b7001ab0c2a1": "", + "5a678aa6f038b7001ab0c2a3": "", + "5a678aa6f038b7001ab0c2a4": "", + "5727482bf1498d1400e8f5a4": "Roman Catholic", + "5727482bf1498d1400e8f5a5": "Orthodox Christians", + "5727482bf1498d1400e8f5a6": "academic subjects", + "5a678dcef038b7001ab0c2ba": "", + "5a678dcef038b7001ab0c2bc": "", + "5a678dcef038b7001ab0c2bd": "", + "5a678dcef038b7001ab0c2be": "", + "5727490bdd62a815002e9a82": "", + "5727490bdd62a815002e9a83": "compulsory blazer", + "5727490bdd62a815002e9a84": "more expensive", + "5a678f35f038b7001ab0c2c4": "", + "5a678f35f038b7001ab0c2c5": "", + "5a678f35f038b7001ab0c2c6": "", + "5a678f35f038b7001ab0c2c7": "", + "5a678f35f038b7001ab0c2c8": "", + "57274971708984140094dbbb": "", + "57274971708984140094dbbc": "Catholic", + "57274971708984140094dbbd": "Sydney", + "57274971708984140094dbbe": "girls", + "5a6790dbf038b7001ab0c2ce": "", + "5a6790dbf038b7001ab0c2cf": "", + "5a6790dbf038b7001ab0c2d0": "", + "5a6790dbf038b7001ab0c2d1": "", + "5a6790dbf038b7001ab0c2d2": "", + "57274a1edd62a815002e9a9a": "Article 7, Paragraph 4", + "57274a1edd62a815002e9a9b": "second Gleichschaltung", + "57274a1edd62a815002e9a9c": "", + "57274a1edd62a815002e9a9d": "11.1%", + "57274a1edd62a815002e9a9e": "", + "5a6792f1f038b7001ab0c2ea": "", + "5a6792f1f038b7001ab0c2eb": "", + "5a6792f1f038b7001ab0c2ec": "to protect these schools from a second Gleichschaltung or similar event in the future", + "5a6792f1f038b7001ab0c2ed": "", + "5a6792f1f038b7001ab0c2ee": "", + "57274a8ff1498d1400e8f5bc": "Sonderungsverbot", + "57274a8ff1498d1400e8f5bd": "", + "57274a8ff1498d1400e8f5be": "", + "5a67978ef038b7001ab0c306": "", + "5a67978ef038b7001ab0c307": "", + "5a67978ef038b7001ab0c308": "", + "5a67978ef038b7001ab0c309": "", + "5a67978ef038b7001ab0c30a": "", + "57274b35f1498d1400e8f5d4": "Erg\u00e4nzungsschulen", + "57274b35f1498d1400e8f5d5": "vocational schools", + "57274b35f1498d1400e8f5d6": "by charging their students tuition fees", + "57274b35f1498d1400e8f5d7": "religious groups", + "5a67986af038b7001ab0c310": "", + "5a67986af038b7001ab0c311": "", + "5a67986af038b7001ab0c312": "", + "5a67986af038b7001ab0c313": "", + "5a67986af038b7001ab0c314": "", + "57274beff1498d1400e8f5e4": "unaided independent school", + "57274beff1498d1400e8f5e5": "CBSE", + "57274beff1498d1400e8f5e6": "30", + "57274beff1498d1400e8f5e7": "union government", + "5a6799adf038b7001ab0c31a": "", + "5a6799adf038b7001ab0c31b": "", + "5a6799adf038b7001ab0c31c": "", + "5a6799adf038b7001ab0c31d": "", + "5a6799adf038b7001ab0c31e": "", + "57274ca8dd62a815002e9aa4": "societies", + "57274ca8dd62a815002e9aa5": "India", + "57274ca8dd62a815002e9aa6": "Status of Education Report", + "57274ca8dd62a815002e9aa7": "evaluates learning levels in rural India", + "57274ca8dd62a815002e9aa8": "English", + "5a679cc7f038b7001ab0c344": "", + "5a679cc7f038b7001ab0c345": "", + "5a679cc7f038b7001ab0c346": "", + "5a679cc7f038b7001ab0c347": "poorer academic achievement in government schools", + "5a679cc7f038b7001ab0c348": "", + "57274d1cdd62a815002e9aae": "scoil phr\u00edobh\u00e1ideach", + "57274d1cdd62a815002e9aaf": "double as boarding schools", + "57274d1cdd62a815002e9ab0": "\u20ac5,000", + "57274d1cdd62a815002e9ab1": "Society of Jesus", + "57274d1cdd62a815002e9ab2": "\u20ac25,000 per year", + "5a679db8f038b7001ab0c34e": "scoil phr\u00edobh\u00e1ideach", + "5a679db8f038b7001ab0c34f": "relatively low", + "5a679db8f038b7001ab0c350": "relatively low", + "5a679db8f038b7001ab0c351": "", + "5a679db8f038b7001ab0c352": "", + "57274d9bf1498d1400e8f5f6": "1957", + "57274d9bf1498d1400e8f5f7": "Chinese", + "57274d9bf1498d1400e8f5f8": "English", + "57274d9bf1498d1400e8f5f9": "", + "57274d9bf1498d1400e8f5fa": "Over 60", + "5a679f83f038b7001ab0c364": "", + "5a679f83f038b7001ab0c365": "", + "5a679f83f038b7001ab0c366": "the government instructed all schools to surrender their properties and be assimilated into the National School system", + "5a679f83f038b7001ab0c367": "National Type\" schools", + "5a679f83f038b7001ab0c368": "the schools", + "57274e145951b619008f87e7": "aided", + "57274e145951b619008f87e8": "fully funded by private parties", + "57274e145951b619008f87e9": "Kathmandu", + "57274e145951b619008f87ea": "English", + "57274e145951b619008f87eb": "Nepali", + "5a67a1e3f038b7001ab0c388": "middle-class families", + "5a67a1e3f038b7001ab0c389": "middle-class", + "5a67a1e3f038b7001ab0c38a": "neighbourhood nursery schools", + "5a67a1e3f038b7001ab0c38b": "Galaxy Public School", + "5a67a1e3f038b7001ab0c38c": "private parties", + "57274eca5951b619008f87ff": "88", + "57274eca5951b619008f8800": "28,000", + "57274eca5951b619008f8801": "3.7%", + "57274eca5951b619008f8802": "Catholic", + "57274eca5951b619008f8803": "Auckland", + "5a67a2c7f038b7001ab0c3a2": "", + "5a67a2c7f038b7001ab0c3a3": "", + "5a67a2c7f038b7001ab0c3a4": "", + "5a67a2c7f038b7001ab0c3a5": "", + "5a67a2c7f038b7001ab0c3a6": "", + "57274f49f1498d1400e8f61e": "Anglican", + "57274f49f1498d1400e8f61f": "Wellington", + "57274f49f1498d1400e8f620": "Presbyterian", + "57274f49f1498d1400e8f621": "Christchurch", + "57274f49f1498d1400e8f622": "", + "5a67a492f038b7001ab0c3c4": "", + "5a67a492f038b7001ab0c3c5": "", + "5a67a492f038b7001ab0c3c6": "Society of St Pius X", + "5a67a492f038b7001ab0c3c7": "", + "5a67a492f038b7001ab0c3c8": "", + "5727500f708984140094dbfd": "7.5%", + "5727500f708984140094dbfe": "32%", + "5727500f708984140094dbff": "80%", + "5727500f708984140094dc00": "August 1992", + "5727500f708984140094dc01": "natural science", + "5a67a5d9f038b7001ab0c3dc": "", + "5a67a5d9f038b7001ab0c3de": "Per unit costs", + "5a67a5d9f038b7001ab0c3df": "", + "5a67a5d9f038b7001ab0c3e0": "", + "572750df5951b619008f882f": "The Education Service Contracting scheme", + "572750df5951b619008f8830": "Tuition Fee Supplement", + "572750df5951b619008f8831": "Private Education Student Financial Assistance", + "5a67a898f038b7001ab0c3f4": "", + "5a67a898f038b7001ab0c3f5": "enrollment overflows", + "5a67a898f038b7001ab0c3f6": "wish to pursue college/technical education", + "5a67a898f038b7001ab0c3f7": "The Education Service Contracting scheme of the government", + "5a67a898f038b7001ab0c3f8": "", + "5727515f708984140094dc11": "The South African Schools Act of 1996", + "5727515f708984140094dc12": "1996", + "5727515f708984140094dc13": "state-controlled) and \"independent\"", + "5727515f708984140094dc14": "traditional private schools", + "5727515f708984140094dc15": "nineteenth", + "5a67aa48f038b7001ab0c3fe": "", + "5a67aa48f038b7001ab0c3ff": "", + "5a67aa48f038b7001ab0c400": "traditional private schools and schools which are privately governed", + "5a67aa48f038b7001ab0c401": "nineteenth", + "5a67aa48f038b7001ab0c402": "", + "57275409708984140094dc35": "private schools", + "57275409708984140094dc36": "formerly model C schools tend to set much higher school fees than other public schools", + "57275409708984140094dc37": "higher school fees than other public schools", + "5a67b759f038b7001ab0c43a": "Model C", + "5a67b759f038b7001ab0c43b": "the legal form of \"Model C\"", + "5a67b759f038b7001ab0c43c": "", + "5a67b759f038b7001ab0c43d": "", + "5a67b759f038b7001ab0c43e": "", + "572754dd708984140094dc3b": "Over 10%", + "572754dd708984140094dc3c": "10,000", + "572754dd708984140094dc3d": "700", + "572754dd708984140094dc3e": "The Knowledge School", + "572754dd708984140094dc3f": "school voucher", + "5a67b94bf038b7001ab0c444": "", + "5a67b94bf038b7001ab0c445": "", + "5a67b94bf038b7001ab0c446": "", + "5a67b94bf038b7001ab0c447": "", + "5a67b94bf038b7001ab0c448": "", + "572756265951b619008f886d": "13", + "572756265951b619008f886e": "public schools", + "572756265951b619008f886f": "9", + "572756265951b619008f8870": "13", + "572756265951b619008f8871": "under \u00a33,000 to \u00a321,000 and above per year", + "5a67d87ef038b7001ab0c48a": "", + "5a67d87ef038b7001ab0c48b": "", + "5a67d87ef038b7001ab0c48c": "", + "5a67d87ef038b7001ab0c48d": "single-sex", + "5a67d87ef038b7001ab0c48e": "", + "572757bef1498d1400e8f690": "Brown v. Board of Education of Topeka", + "572757bef1498d1400e8f691": "segregation academies", + "572757bef1498d1400e8f692": "South", + "572757bef1498d1400e8f693": "white", + "572757bef1498d1400e8f694": "African-American", + "5a67dae18476ee001a58a738": "", + "5a67dae18476ee001a58a739": "", + "5a67dae18476ee001a58a73a": "", + "5a67dae18476ee001a58a73b": "", + "5a67dae18476ee001a58a73c": "", + "572758e0f1498d1400e8f6ae": "religious organizations or private individuals", + "572758e0f1498d1400e8f6af": "First Amendment", + "572758e0f1498d1400e8f6b0": "Blaine Amendments", + "572758e0f1498d1400e8f6b1": "charter", + "5a67dedd8476ee001a58a74c": "", + "5a67dedd8476ee001a58a74d": "", + "5a67dedd8476ee001a58a74e": "", + "5a67dedd8476ee001a58a74f": "", + "5a67dedd8476ee001a58a750": "", + "572759665951b619008f8883": "Massachusetts", + "572759665951b619008f8884": "1852", + "572759665951b619008f8885": "1972", + "572759665951b619008f8886": "268 U.S. 510", + "572759665951b619008f8887": "", + "5a67e29c8476ee001a58a756": "", + "5a67e29d8476ee001a58a757": "Massachusetts", + "5a67e29d8476ee001a58a758": "states may set standards for educational accomplishment", + "5a67e29d8476ee001a58a759": "", + "5a67e29d8476ee001a58a75a": "", + "572759dbdd62a815002e9b94": "$40,000", + "572759dbdd62a815002e9b95": "$50,000", + "572759dbdd62a815002e9b96": "Groton School", + "572759dbdd62a815002e9b97": "", + "5a67e5278476ee001a58a760": "", + "5a67e5278476ee001a58a761": "throughout the country", + "5a67e5278476ee001a58a762": "", + "5a67e5278476ee001a58a763": "New York City", + "5a67e5278476ee001a58a764": "", + "5727aa413acd2414000de921": "John Harvard", + "5727aa413acd2414000de922": "1977", + "5727aa413acd2414000de923": "James Bryant Conant", + "5727aa413acd2414000de924": "Association of American Universities", + "5727aa413acd2414000de925": "Charles W. Eliot", + "5a81ee4b31013a001a334f9d": "", + "5a81ee4b31013a001a334f9e": "Congregationalist and Unitarian clergy", + "5a81ee4b31013a001a334f9f": "18th century", + "5a81ee4b31013a001a334fa0": "", + "5a81ee4b31013a001a334fa1": "Charles W. Eliot", + "5727aeac3acd2414000de987": "Harvard Library", + "5727aeac3acd2414000de988": "79", + "5727aeac3acd2414000de989": "18 million", + "5727aeac3acd2414000de98a": "eight", + "5727aeac3acd2414000de98b": "150", + "5a81f28431013a001a334fb1": "", + "5a81f28431013a001a334fb2": "", + "5a81f28431013a001a334fb3": "", + "5a81f28431013a001a334fb4": "eight", + "5a81f28431013a001a334fb5": "62", + "5727aec03acd2414000de991": "Cambridge", + "5727aec03acd2414000de992": "$37.6 billion", + "5727aec03acd2414000de993": "Charles River", + "5727aec03acd2414000de994": "eleven", + "5727aec03acd2414000de995": "Harvard Yard", + "5a81f0f031013a001a334fa7": "$37.6 billion", + "5a81f0f031013a001a334fa8": "eleven", + "5a81f0f031013a001a334fa9": "", + "5a81f0f031013a001a334faa": "Allston neighborhood of Boston", + "5a81f0f031013a001a334fab": "eleven", + "5727afa82ca10214002d93c2": "1636", + "5727afa82ca10214002d93c3": "Great and General Court of the Massachusetts Bay Colony", + "5727afa82ca10214002d93c4": "1638", + "5727afa82ca10214002d93c5": "1639", + "5727afa82ca10214002d93c6": "1650", + "5a81f84e31013a001a335007": "", + "5a81f84e31013a001a335008": "", + "5a81f84e31013a001a335009": "", + "5a81f84e31013a001a33500a": "", + "5a81f84e31013a001a33500b": "", + "5727b0892ca10214002d93e8": "Puritan", + "5727b0892ca10214002d93e9": "English university model", + "5727b0892ca10214002d93ea": "It was never affiliated with any particular denomination", + "5a82001531013a001a3350a1": "", + "5a82001531013a001a3350a2": "", + "5a82001531013a001a3350a3": "to advance learning and perpetuate it to posterity", + "5a82001531013a001a3350a4": "clergymen", + "5a82001531013a001a3350a5": "", + "5727b8df3acd2414000dea99": "1804", + "5727b8df3acd2414000dea9a": "Samuel Webber", + "5727b8df3acd2414000dea9b": "1805", + "5a82025a31013a001a3350b5": "", + "5a82025a31013a001a3350b6": "", + "5a82025a31013a001a3350b7": "", + "5a82025a31013a001a3350b8": "", + "5a82025a31013a001a3350b9": "", + "5727c0402ca10214002d9564": "Louis Agassiz", + "5727c0402ca10214002d9565": "intuition", + "5727c0402ca10214002d9566": "Thomas Reid and Dugald Stewart", + "5a8203d431013a001a3350bf": "", + "5a8203d431013a001a3350c0": "", + "5a8203d431013a001a3350c1": "", + "5a8203d431013a001a3350c2": "", + "5a8203d431013a001a3350c3": "", + "5727c3b02ca10214002d95ba": "Charles W. 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Haydon Burns", + "57281ab63acd2414000df497": "World War II", + "5a1c883cb4fb5d0018714670": "", + "5a1c883cb4fb5d0018714671": "", + "5a1c883cb4fb5d0018714672": "55.1%", + "5a1c883cb4fb5d0018714673": "", + "5a1c883cb4fb5d0018714674": "white flight", + "57281bb84b864d190016449a": "tax base", + "57281bb84b864d190016449b": "unincorporated suburbs", + "57281bb84b864d190016449c": "funding education, sanitation, and traffic control", + "57281bb84b864d190016449d": "Voters outside the city limits", + "5a1c88d2b4fb5d001871467a": "", + "5a1c88d2b4fb5d001871467b": "", + "5a1c88d2b4fb5d001871467c": "", + "5a1c88d2b4fb5d001871467d": "", + "57281d494b864d19001644be": "through the traditional old boy network", + "57281d494b864d19001644bf": "11", + "57281d494b864d19001644c0": "Jacksonville Consolidation", + "57281d494b864d19001644c1": "all 15 of Duval County's public high schools lost their accreditation", + "5a1c8971b4fb5d0018714682": "through the traditional old boy network", + "5a1c8971b4fb5d0018714683": "11", + "5a1c8971b4fb5d0018714684": "", + "5a1c8971b4fb5d0018714685": "", + "5a1c8971b4fb5d0018714686": "", + "57281edd3acd2414000df4eb": "voters approved the plan", + "57281edd3acd2414000df4ec": "Hans Tanzler", + "57281edd3acd2414000df4ed": "Consolidated City", + "57281edd3acd2414000df4ee": "The Better Jacksonville Plan", + "57281edd3acd2414000df4ef": "half-penny sales tax", + "5a1c8a1eb4fb5d0018714696": "", + "5a1c8a1eb4fb5d0018714697": "", + "5a1c8a1eb4fb5d0018714698": "", + "5a1c8a1eb4fb5d0018714699": "", + "572820512ca10214002d9e72": "86.66%", + "572820512ca10214002d9e73": "St. Johns River", + "572820512ca10214002d9e74": "Trout River", + "572820512ca10214002d9e75": "13.34%", + "572820512ca10214002d9e76": "Baldwin", + "5a1c8aedb4fb5d00187146a0": "", + "5a1c8aedb4fb5d00187146a1": "", + "5a1c8aedb4fb5d00187146a2": "", + "5a1c8aedb4fb5d00187146a3": "", + "5a1c8aedb4fb5d00187146a4": "Baldwin", + "572821274b864d1900164510": "The tallest building in Downtown Jacksonville's skyline", + "572821274b864d1900164511": "the Barnett Center", + "572821274b864d1900164512": "617 ft", + "572821274b864d1900164513": "28", + "572821274b864d1900164514": "distinctive flared base", + "5a1c8bb4b4fb5d00187146aa": "", + "5a1c8bb4b4fb5d00187146ac": "", + "5a1c8bb4b4fb5d00187146ad": "", + "5a1c8bb4b4fb5d00187146ae": "", + "5728223cff5b5019007d9dc4": "humid subtropical", + "5728223cff5b5019007d9dc5": "May through September", + "5728223cff5b5019007d9dc6": "mild", + "5728223cff5b5019007d9dc7": "low latitude", + "5a1c8c34b4fb5d00187146b4": "", + "5a1c8c34b4fb5d00187146b5": "", + "5a1c8c34b4fb5d00187146b6": "", + "5a1c8c34b4fb5d00187146b7": "low latitude and coastal location", + "57282358ff5b5019007d9dde": "104 \u00b0F", + "57282358ff5b5019007d9ddf": "thunderstorms", + "57282358ff5b5019007d9de0": "extremely high humidity", + "57282358ff5b5019007d9de1": "", + "5a1c8d0bb4fb5d00187146bc": "104 \u00b0F", + "5a1c8d0bb4fb5d00187146bd": "", + "5a1c8d0bb4fb5d00187146be": "", + "5a1c8d0bb4fb5d00187146bf": "", + "572824f13acd2414000df58f": "Hurricane Dora", + "572824f13acd2414000df590": "110 mph (180 km/h)", + "572824f13acd2414000df591": "Beryl", + "572824f13acd2414000df592": "Saffir-Simpson Scale", + "572824f13acd2414000df593": "2008", + "5a1c8e0bb4fb5d00187146c4": "", + "5a1c8e0bb4fb5d00187146c5": "110 mph (180 km/h)", + "5a1c8e0bb4fb5d00187146c6": "Fay", + "5a1c8e0bb4fb5d00187146c7": "", + "5a1c8e0bb4fb5d00187146c8": "", + "572826634b864d19001645be": "Arab", + "572826634b864d19001645bf": "821,784", + "572826634b864d19001645c0": "largest", + "572826634b864d19001645c1": "Filipino", + "5a1c8ea7b4fb5d00187146ce": "", + "5a1c8ea7b4fb5d00187146cf": "", + "5a1c8ea7b4fb5d00187146d0": "", + "5a1c8ea7b4fb5d00187146d1": "", + "5a1c8ea7b4fb5d00187146d2": "", + "572827fc3acd2414000df5bb": "7.9%", + "572827fc3acd2414000df5bc": "23.9%", + "572827fc3acd2414000df5bd": "females", + "572827fc3acd2414000df5be": "91.3", + "5a1c8f54b4fb5d00187146d8": "2010", + "5a1c8f54b4fb5d00187146d9": "10.9%", + "5a1c8f54b4fb5d00187146da": "91.3", + "5a1c8f54b4fb5d00187146db": "the average family size was 3.21", + "5a1c8f54b4fb5d00187146dc": "43.8%", + "5727e6cbff5b5019007d97ee": "40%", + "5727e6cbff5b5019007d97ef": "3.5 billion", + "5727e6cbff5b5019007d97f0": "$759,900", + "5727e6cbff5b5019007d97f1": "using net wealth", + "5727e6cbff5b5019007d97f2": "there are more poor people in the United States and Western Europe than in China", + "5729d36b1d04691400779607": "40%", + "5729d36b1d04691400779608": "financial assets", + "5729d36b1d04691400779609": "nearly $41 trillion", + "5729d36b1d0469140077960a": "more than half", + "5729d36b1d0469140077960b": "due to a greater tendency to take on debts", + "5ad242e5d7d075001a4289a4": "", + "5ad242e5d7d075001a4289a5": "", + "5ad242e5d7d075001a4289a6": "$759,900", + "5ad242e5d7d075001a4289a7": "", + "5ad242e5d7d075001a4289a8": "", + "5727e8424b864d1900163fc0": "400", + "5727e8424b864d1900163fc1": "New York Times", + "5727e8424b864d1900163fc2": "more wealth than half of all Americans combined", + "5727e8424b864d1900163fc3": "", + "5729d44b1d04691400779611": "wealth", + "5729d44b1d04691400779612": "the \"richest 1 percent", + "5729d44b1d04691400779613": "Inherited wealth", + "5729d44b1d04691400779614": "over 60 percent", + "5729d44b1d04691400779615": "Institute for Policy Studies", + "5ad2434fd7d075001a4289d6": "", + "5ad2434fd7d075001a4289d7": "", + "5ad2434fd7d075001a4289d8": "", + "5ad2434fd7d075001a4289d9": "", + "5ad2434fd7d075001a4289da": "", + "5727e9523acd2414000def95": "", + "5727e9523acd2414000def96": "productivity gap between highly-paid professions and lower-paid professions", + "5727e9523acd2414000def97": "", + "5727e9523acd2414000def98": "inequality", + "5727e9523acd2414000def99": "", + "5729d51d3f37b3190047858f": "differences in value added by labor, capital and land", + "5729d51d3f37b31900478590": "value added", + "5729d51d3f37b31900478591": "wages and profits", + "5729d51d3f37b31900478592": "worker, capitalist/business owner, landlord", + "5729d51d3f37b31900478593": "productivity gap", + "5ad243a7d7d075001a428a06": "", + "5ad243a7d7d075001a428a07": "", + "5ad243a7d7d075001a428a08": "", + "5ad243a7d7d075001a428a09": "", + "5ad243a7d7d075001a428a0a": "", + "5727ea45ff5b5019007d986e": "", + "5727ea45ff5b5019007d986f": "", + "5727ea45ff5b5019007d9870": "increasing unemployment", + "5727ea45ff5b5019007d9871": "rising levels of property income", + "5729d609af94a219006aa661": "labor inputs", + "5729d609af94a219006aa662": "to reduce costs and maximize profits", + "5729d609af94a219006aa663": "Marxian analysis", + "5729d609af94a219006aa664": "productivity", + "5729d609af94a219006aa665": "stagnant", + "5ad2442bd7d075001a428a3c": "", + "5ad2442bd7d075001a428a3d": "", + "5ad2442bd7d075001a428a3e": "", + "5ad2442bd7d075001a428a3f": "downward pressure", + "5ad2442bd7d075001a428a40": "", + "5727ec062ca10214002d99b6": "", + "5727ec062ca10214002d99b7": "", + "5727ec062ca10214002d99b8": "", + "5727ec062ca10214002d99b9": "by offering a higher wage the best of their labor", + "5727ec062ca10214002d99ba": "unfair", + "5729d878af94a219006aa66b": "the market", + "5729d878af94a219006aa66c": "prices", + "5729d878af94a219006aa66d": "wages", + "5729d878af94a219006aa66e": "markets", + "5729d878af94a219006aa66f": "high levels of inequality", + "5ad2461ad7d075001a428ad2": "", + "5ad2461ad7d075001a428ad3": "", + "5ad2461ad7d075001a428ad4": "", + "5ad2461ad7d075001a428ad5": "", + "5ad2461ad7d075001a428ad6": "", + "5727ed2e3acd2414000df001": "", + "5727ed2e3acd2414000df002": "low demand", + "5727ed2e3acd2414000df003": "high wages", + "5727ed2e3acd2414000df004": "collective bargaining, political influence, or corruption", + "5727ed2e3acd2414000df005": "", + "5729da0faf94a219006aa675": "a low wage", + "5729da0faf94a219006aa676": "Competition", + "5729da0faf94a219006aa677": "due to the expendable nature of the worker in relation to his or her particular job", + "5729da0faf94a219006aa678": "low wage", + "5729da0faf94a219006aa679": "", + "5ad2467ad7d075001a428af6": "", + "5ad2467ad7d075001a428af7": "", + "5ad2467ad7d075001a428af8": "high wages", + "5ad2467ad7d075001a428af9": "", + "5ad2467ad7d075001a428afa": "", + "5727ee372ca10214002d99ec": "entrepreneurship rates", + "5727ee372ca10214002d99ed": "self-employment", + "5727ee372ca10214002d99ee": "", + "5727ee372ca10214002d99ef": "", + "5727ee372ca10214002d99f0": "opportunity-based", + "5729de24af94a219006aa689": "higher economic inequality", + "5729de24af94a219006aa68a": "necessity", + "5729de24af94a219006aa68b": "Necessity-based", + "5729de24af94a219006aa68c": "achievement-oriented motivations", + "5729de24af94a219006aa68d": "positive", + "5ad2472bd7d075001a428b22": "", + "5ad2472bd7d075001a428b23": "", + "5ad2472bd7d075001a428b24": "", + "5ad2472bd7d075001a428b25": "", + "5ad2472bd7d075001a428b26": "", + "5727ef664b864d1900164060": "progressive tax", + "5727ef664b864d1900164061": "the level of the top tax rate", + "5727ef664b864d1900164062": "steeper tax progressivity applied to social spending", + "5727ef664b864d1900164063": "progressive tax system", + "5729e02f1d04691400779639": "the tax rate", + "5729e02f1d0469140077963a": "the level of the top tax rate", + "5729e02f1d0469140077963b": "steeper tax progressivity applied to social spending", + "5729e02f1d0469140077963c": "Gini index", + "5ad247b0d7d075001a428b42": "", + "5ad247b0d7d075001a428b43": "", + "5ad247b0d7d075001a428b44": "", + "5ad247b0d7d075001a428b45": "", + "5ad247b0d7d075001a428b46": "", + "5727f05b4b864d1900164068": "Education", + "5727f05b4b864d1900164069": "", + "5727f05b4b864d190016406a": "lower incomes", + "5727f05b4b864d190016406b": "the poor", + "5727f05b4b864d190016406c": "", + "5729e1101d04691400779641": "access to education", + "5729e1101d04691400779642": "high wages", + "5729e1101d04691400779643": "lower wages", + "5729e1101d04691400779644": "lower incomes", + "5729e1101d04691400779645": "education", + "5ad24840d7d075001a428b5c": "", + "5ad24840d7d075001a428b5d": "", + "5ad24840d7d075001a428b5e": "", + "5ad24840d7d075001a428b5f": "the poor", + "5ad24840d7d075001a428b60": "lower aggregate savings and investment", + "5727f16c3acd2414000df05b": "", + "5727f16c3acd2414000df05c": "$105 billion", + "5727f16c3acd2414000df05d": "boom-and-bust cycles", + "5727f16c3acd2414000df05e": "", + "5729e1e36aef0514001550ba": "2014", + "5729e1e36aef0514001550bb": "2008-2009 recession", + "5729e1e36aef0514001550bc": "increasing access to education", + "5729e1e36aef0514001550bd": "$105 billion", + "5729e1e36aef0514001550be": "boom-and-bust cycles", + "5ad248e0d7d075001a428b82": "", + "5ad248e0d7d075001a428b83": "$105 billion", + "5ad248e0d7d075001a428b84": "", + "5ad248e0d7d075001a428b85": "economists with the Standard & Poor's rating agency", + "5ad248e0d7d075001a428b86": "", + "5727f2714b864d1900164072": "1910\u20131940", + "5727f2714b864d1900164073": "decrease in the price of skilled labor", + "5727f2714b864d1900164074": "decrease in the price", + "5727f2714b864d1900164075": "", + "5727f2714b864d1900164076": "decrease in wages", + "5729e2b76aef0514001550ce": "1910\u20131940", + "5729e2b76aef0514001550cf": "decrease in the price of skilled labor", + "5729e2b76aef0514001550d0": "a stepping-stone to acquire college and advanced degrees", + "5729e2b76aef0514001550d1": "Education", + "5729e2b76aef0514001550d2": "gender inequality in education can result to low economic growth, and continued gender inequality", + "5ad24b96d7d075001a428bee": "", + "5ad24b96d7d075001a428bef": "decreased inequality", + "5ad24b96d7d075001a428bf0": "decreased inequality", + "5ad24b96d7d075001a428bf1": "", + "5ad24b96d7d075001a428bf2": "", + "5727f6723acd2414000df0e7": "", + "5727f6723acd2414000df0e8": "", + "5727f6723acd2414000df0e9": "", + "5727f6723acd2414000df0ea": "", + "5729e38daf94a219006aa69d": "economic inequality", + "5729e38daf94a219006aa69e": "social exclusion", + "5729e38daf94a219006aa69f": "the CEPR", + "5729e38daf94a219006aa6a0": "", + "5729e38daf94a219006aa6a1": "lower", + "5ad24e50d7d075001a428c3a": "union membership", + "5ad24e50d7d075001a428c3b": "all the continental European countries", + "5ad24e50d7d075001a428c3c": "", + "5ad24e50d7d075001a428c3d": "", + "5ad24e50d7d075001a428c3e": "", + "5727f7523acd2414000df10d": "Scandinavia", + "5727f7523acd2414000df10e": "high inequality", + "5727f7523acd2414000df10f": "", + "5727f7523acd2414000df110": "", + "5729e4291d04691400779651": "Sociologist", + "5729e4291d04691400779652": "University of Washington", + "5729e4291d04691400779653": "the decline of organized labor", + "5729e4291d04691400779654": "high", + "5729e4291d04691400779655": "weak labor movements and vice-versa", + "5ad24efad7d075001a428c74": "Scandinavia", + "5ad24efad7d075001a428c75": "", + "5ad24efad7d075001a428c76": "", + "5ad24efad7d075001a428c77": "", + "5ad24efad7d075001a428c78": "", + "5727fc37ff5b5019007d9a18": "", + "5727fc37ff5b5019007d9a19": "", + "5727fc37ff5b5019007d9a1a": "", + "5727fc37ff5b5019007d9a1b": "", + "5729f1283f37b319004785d7": "global to a domestic scale", + "5729f1283f37b319004785d8": "low-skilled workers", + "5729f1283f37b319004785d9": "trade liberalisation", + "5729f1283f37b319004785da": "minor", + "5729f1283f37b319004785db": "machine labor", + "5ad24fb7d7d075001a428c92": "", + "5ad24fb7d7d075001a428c93": "technological innovation", + "5ad24fb7d7d075001a428c94": "", + "5ad24fb7d7d075001a428c95": "", + "5727fd123acd2414000df185": "53%", + "5727fd123acd2414000df186": "", + "5727fd123acd2414000df187": "there is still a difference in earnings between women and men", + "5727fd123acd2414000df188": "males", + "5729f1c13f37b319004785e7": "Gender pay gap", + "5729f1c13f37b319004785e8": "males", + "5729f1c13f37b319004785e9": "women", + "5729f1c13f37b319004785ea": "Thomas Sowell", + "5729f1c13f37b319004785eb": "a difference", + "5ad258f3d7d075001a428de4": "", + "5ad258f3d7d075001a428de5": "", + "5ad258f3d7d075001a428de6": "", + "5ad258f3d7d075001a428de7": "", + "5ad258f3d7d075001a428de8": "", + "5727ff083acd2414000df1ab": "social welfare programs", + "5727ff083acd2414000df1ac": "lower", + "5727ff083acd2414000df1ad": "it acquires more capital", + "5727ff083acd2414000df1ae": "", + "5729f24baf94a219006aa6dd": "Economist", + "5729f24baf94a219006aa6de": "levels of economic inequality", + "5729f24baf94a219006aa6df": "more capital", + "5729f24baf94a219006aa6e0": "more wealth and income", + "5729f24baf94a219006aa6e1": "", + "5ad2594ed7d075001a428df8": "", + "5ad2594ed7d075001a428df9": "", + "5ad2594ed7d075001a428dfa": "", + "5ad2594ed7d075001a428dfb": "", + "5ad2594ed7d075001a428dfc": "", + "57287b322ca10214002da3be": "1910 to 1940 and thereafter", + "57287b322ca10214002da3bf": "", + "57287b322ca10214002da3c0": "", + "57287b322ca10214002da3c1": "", + "5729f3883f37b319004785f1": "Kuznets", + "5729f3883f37b319004785f2": "Kuznets curve", + "5729f3883f37b319004785f3": "very weak", + "5729f3883f37b319004785f4": "income inequality will eventually decrease", + "5729f3883f37b319004785f5": "the move from the manufacturing sector to the service sector", + "5ad259fdd7d075001a428e26": "", + "5ad259fdd7d075001a428e27": "", + "5ad259fdd7d075001a428e28": "", + "5ad259fdd7d075001a428e29": "", + "5ad259fdd7d075001a428e2a": "", + "57287c2bff5b5019007da26c": "Wealth concentration", + "57287c2bff5b5019007da26d": "the means to invest in new sources of creating wealth or to otherwise leverage the accumulation of wealth", + "57287c2bff5b5019007da26e": "wealth condensation", + "57287c2bff5b5019007da26f": "greater return of capital", + "5729f4273f37b319004785fb": "in the possession of already-wealthy individuals or entities", + "5729f4273f37b319004785fc": "those who already hold wealth", + "5729f4273f37b319004785fd": "wealth condensation", + "5729f4273f37b319004785fe": "Thomas Piketty", + "5729f4273f37b319004785ff": "higher returns", + "5ad25a8bd7d075001a428e30": "", + "5ad25a8bd7d075001a428e31": "", + "5ad25a8bd7d075001a428e32": "wealth condensation", + "5ad25a8bd7d075001a428e33": "", + "5ad25a8bd7d075001a428e34": "", + "5729f4e46aef051400155156": "Economist", + "5729f4e46aef051400155157": "market forces", + "5729f4e46aef051400155158": "rare and desired", + "5729f4e46aef051400155159": "political power", + "5729f4e46aef05140015515a": "rent-seeking", + "5ad25af2d7d075001a428e52": "", + "5ad25af2d7d075001a428e53": "", + "5ad25af2d7d075001a428e54": "", + "5ad25af2d7d075001a428e55": "", + "5ad25af2d7d075001a428e56": "", + "5729f60caf94a219006aa6ef": "inequality", + "5729f60caf94a219006aa6f0": "human capital is neglected", + "5729f60caf94a219006aa6f1": "life expectancy", + "5729f60caf94a219006aa6f2": "inequality", + "5729f60caf94a219006aa6f3": "lower", + "5ad25c56d7d075001a428e9a": "inequality", + "5ad25c56d7d075001a428e9b": "", + "5ad25c56d7d075001a428e9c": "", + "5ad25c56d7d075001a428e9d": "", + "5ad25c56d7d075001a428e9e": "lower", + "572a05eb3f37b31900478653": "2013", + "572a05eb3f37b31900478654": "rising inequality", + "572a05eb3f37b31900478655": "negative", + "572a05eb3f37b31900478656": "promoting social dislocation, unrest and conflict", + "572a05eb3f37b31900478657": "economic", + "5ad25cced7d075001a428ec6": "", + "5ad25cced7d075001a428ec7": "", + "5ad25cced7d075001a428ec8": "", + "5ad25cced7d075001a428ec9": "", + "5ad25cced7d075001a428eca": "economic", + "572a06866aef0514001551be": "British", + "572a06866aef0514001551bf": "lower", + "572a06866aef0514001551c0": "lower", + "572a06866aef0514001551c1": "equality", + "572a06866aef0514001551c2": "23", + "5ad25d39d7d075001a428ed8": "", + "5ad25d39d7d075001a428ed9": "", + "5ad25d39d7d075001a428eda": "life expectancy by country, educational performance, trust among strangers, women's status, social mobility, even numbers of patents issued", + "5ad25d39d7d075001a428edb": "equality", + "5ad25d39d7d075001a428edc": "", + "572a070c6aef0514001551c8": "better health and longer lives", + "572a070c6aef0514001551c9": "among poorer countries", + "572a070c6aef0514001551ca": "life expectancy", + "572a070c6aef0514001551cb": "Americans", + "572a070c6aef0514001551cc": "more equally distributed \u2013 was longer", + "5ad25eead7d075001a428f4c": "", + "5ad25eead7d075001a428f4d": "", + "5ad25eead7d075001a428f4e": "", + "5ad25eead7d075001a428f4f": "", + "5ad25eead7d075001a428f50": "", + "572a07a86aef0514001551d2": "income inequality", + "572a07a86aef0514001551d3": "Richard Wilkinson and Kate Pickett", + "572a07a86aef0514001551d4": "nine", + "572a07a86aef0514001551d5": "countries with bigger income inequalities", + "572a07a86aef0514001551d6": "greater equality", + "5ad25f42d7d075001a428f72": "", + "5ad25f42d7d075001a428f73": "", + "5ad25f42d7d075001a428f74": "", + "5ad25f42d7d075001a428f75": "", + "5ad25f42d7d075001a428f76": "", + "572a0a391d046914007796df": "inequality", + "572a0a391d046914007796e0": "homicides", + "572a0a391d046914007796e1": "fifty", + "572a0a391d046914007796e2": "tenfold", + "572a0a391d046914007796e3": "differences in the amount of inequality in each province or state", + "5ad25fcbd7d075001a428f8c": "", + "5ad25fcbd7d075001a428f8d": "", + "5ad25fcbd7d075001a428f8e": "", + "5ad25fcbd7d075001a428f8f": "", + "5ad25fcbd7d075001a428f90": "", + "572a0bafaf94a219006aa765": "the greatest good", + "572a0bafaf94a219006aa766": "", + "572a0bafaf94a219006aa767": "a great deal of utility", + "572a0bafaf94a219006aa768": "", + "572a0bafaf94a219006aa769": "higher aggregate utility", + "5ad260dbd7d075001a428fd8": "", + "5ad260dbd7d075001a428fd9": "", + "5ad260dbd7d075001a428fda": "relatively less utility", + "5ad260dbd7d075001a428fdb": "decreases", + "5ad260dbd7d075001a428fdc": "", + "572a0c541d046914007796f3": "", + "572a0c541d046914007796f4": "libertarian", + "572a0c541d046914007796f5": "2001", + "572a0c541d046914007796f6": "Thomas B. Edsall", + "572a0c541d046914007796f7": "journalist", + "5ad2616fd7d075001a429036": "", + "5ad2616fd7d075001a429037": "", + "5ad2616fd7d075001a429038": "", + "5ad2616fd7d075001a429039": "", + "5ad2616fd7d075001a42903a": "", + "572a0d21af94a219006aa783": "Central Banking economist", + "572a0d21af94a219006aa784": "systematic economic inequalities", + "572a0d21af94a219006aa785": "Financial crisis of 2007\u201308", + "572a0d21af94a219006aa786": "easier credit to the lower and middle income earners", + "572a0d21af94a219006aa787": "political pressure has developed to extend easier credit to the lower and middle income earners", + "5ad261cfd7d075001a429062": "", + "5ad261cfd7d075001a429063": "", + "5ad261cfd7d075001a429064": "", + "5ad261cfd7d075001a429065": "", + "5ad261cfd7d075001a429066": "", + "572a0e0e1d04691400779707": "inequality in wealth and income", + "572a0e0e1d04691400779708": "the quality of a country's institutions and high levels of education", + "572a0e0e1d04691400779709": "GDP growth actually declines", + "572a0e0e1d0469140077970a": "higher GDP growth", + "572a0e0e1d0469140077970b": "The poor and the middle class", + "5ad2623dd7d075001a429092": "", + "5ad2623dd7d075001a429093": "", + "5ad2623dd7d075001a429094": "", + "5ad2623dd7d075001a429095": "", + "5ad2623dd7d075001a429096": "", + "572a0ecb1d04691400779717": "", + "572a0ecb1d04691400779718": "economic growth", + "572a0ecb1d04691400779719": "subsequent long-run economic growth", + "572a0ecb1d0469140077971a": "it is a waste of resources", + "572a0ecb1d0469140077971b": "inequality-associated effects", + "5ad262aad7d075001a4290c0": "", + "5ad262aad7d075001a4290c1": "", + "5ad262aad7d075001a4290c2": "", + "5ad262aad7d075001a4290c3": "", + "5ad262aad7d075001a4290c4": "", + "572a1046af94a219006aa78d": "both global inequality and inequality within countries prevent growth by limiting aggregate demand", + "572a1046af94a219006aa78e": "limiting aggregate demand", + "572a1046af94a219006aa78f": "", + "572a1046af94a219006aa790": "increasing importance of human capital in development", + "572a1046af94a219006aa791": "widespread education", + "5ad262ffd7d075001a4290e4": "", + "5ad262ffd7d075001a4290e5": "", + "5ad262ffd7d075001a4290e6": "", + "5ad262ffd7d075001a4290e7": "increasing importance of human capital in development", + "572a11663f37b31900478693": "1993", + "572a11663f37b31900478694": "detrimental", + "572a11663f37b31900478695": "the channels through which inequality may affect economic growth", + "572a11663f37b31900478696": "redistributive taxation", + "572a11663f37b31900478697": "politically and socially unstable", + "5ad26367d7d075001a4290fe": "", + "5ad26367d7d075001a4290ff": "", + "5ad26367d7d075001a429100": "", + "5ad26367d7d075001a429101": "redistributive taxation", + "5ad26367d7d075001a429102": "", + "572a12381d0469140077972b": "Harvard", + "572a12381d0469140077972c": "growth and investment", + "572a12381d0469140077972d": "reduce", + "572a12381d0469140077972e": "encourage growth", + "572a12381d0469140077972f": "between 1960 and 2000", + "5ad26420d7d075001a429134": "", + "5ad26420d7d075001a429135": "", + "5ad26420d7d075001a429136": "encourage", + "5ad26420d7d075001a429137": "", + "5ad26420d7d075001a429138": "", + "572a13841d0469140077973b": "the Kuznets curve hypothesis", + "572a13841d0469140077973c": "increases", + "572a13841d0469140077973d": "Thomas Piketty", + "572a13841d0469140077973e": "Economist", + "572a13841d0469140077973f": "wars and \"violent economic and political shocks", + "5ad2647bd7d075001a429156": "", + "5ad2647bd7d075001a429157": "", + "5ad2647bd7d075001a429158": "", + "5ad2647bd7d075001a429159": "", + "5ad2647bd7d075001a42915a": "", + "572a18a4af94a219006aa7df": "1970s", + "572a18a4af94a219006aa7e0": "reduced consumer demand", + "572a18a4af94a219006aa7e1": "risen with increased income inequality", + "572a18a4af94a219006aa7e2": "several years", + "572a18a4af94a219006aa7e3": "more equality in the income distribution", + "5ad264e2d7d075001a42917c": "", + "5ad264e2d7d075001a42917d": "reduced consumer demand", + "5ad264e2d7d075001a42917e": "", + "5ad264e2d7d075001a42917f": "", + "5ad264e2d7d075001a429180": "", + "572a1a5c6aef051400155284": "special efforts", + "572a1a5c6aef051400155285": "the existing level of inequality", + "572a1a5c6aef051400155286": "", + "572a1a5c6aef051400155287": "United Nations", + "572a1a5c6aef051400155288": "reducing poverty", + "5ad2654fd7d075001a4291a8": "", + "5ad2654fd7d075001a4291a9": "", + "5ad2654fd7d075001a4291aa": "", + "5ad2654fd7d075001a4291ab": "", + "5ad2654fd7d075001a4291ac": "", + "572a1ba46aef05140015528e": "land and housing", + "572a1ba46aef05140015528f": "through various associations and other arrangements", + "572a1ba46aef051400155290": "extra-legal", + "572a1ba46aef051400155291": "200", + "572a1ba46aef051400155292": "government land", + "5ad265d2d7d075001a4291c6": "", + "5ad265d2d7d075001a4291c7": "", + "5ad265d2d7d075001a4291c8": "", + "5ad265d2d7d075001a4291c9": "", + "5ad265d2d7d075001a4291ca": "", + "572a1c943f37b319004786e1": "affordable housing", + "572a1c943f37b319004786e2": "quality rental units", + "572a1c943f37b319004786e3": "demand for higher quality housing increased", + "572a1c943f37b319004786e4": "gentrification of older neighbourhoods", + "572a1c943f37b319004786e5": "ad valorem property tax policy", + "5ad266efd7d075001a4291f4": "", + "5ad266efd7d075001a4291f5": "", + "5ad266efd7d075001a4291f6": "gentrification of older neighbourhoods", + "5ad266efd7d075001a4291f7": "", + "5ad266efd7d075001a4291f8": "ad valorem property tax policy", + "572a1dbb3f37b319004786f5": "everyone", + "572a1dbb3f37b319004786f6": "their finances", + "572a1dbb3f37b319004786f7": "aspirational consumption", + "572a1dbb3f37b319004786f8": "taking on debt", + "572a1dbb3f37b319004786f9": "greater inequality and potential economic instability", + "5ad2676ed7d075001a429210": "", + "5ad2676ed7d075001a429211": "", + "5ad2676ed7d075001a429212": "", + "5ad2676ed7d075001a429213": "taking on debt", + "5ad2676ed7d075001a429214": "greater inequality and potential economic instability", + "572a1f086aef0514001552c0": "environmental degradation", + "572a1f086aef0514001552c1": "environmental degradation", + "572a1f086aef0514001552c2": "environmental degradation", + "572a1f086aef0514001552c3": "/corrected", + "5ad267e2d7d075001a429246": "", + "5ad267e2d7d075001a429247": "", + "5ad267e2d7d075001a429248": "", + "5ad267e2d7d075001a429249": "", + "5ad267e2d7d075001a42924a": "/corrected", + "572a1fe16aef0514001552d0": "private ownership of the means of production", + "572a1fe16aef0514001552d1": "means of production by a class of owners, creating a situation where a small portion of the population lives off unearned property income", + "572a1fe16aef0514001552d2": "a wage or salary", + "572a1fe16aef0514001552d3": "socially owned", + "572a1fe16aef0514001552d4": "reflective", + "5ad2684bd7d075001a429262": "", + "5ad2684bd7d075001a429263": "", + "5ad2684bd7d075001a429264": "", + "5ad2684bd7d075001a429265": "", + "5ad2684bd7d075001a429266": "", + "572a20816aef0514001552e4": "Robert Nozick", + "572a20816aef0514001552e5": "taxation", + "572a20816aef0514001552e6": "force", + "572a20816aef0514001552e7": "forceful taking of property", + "572a20816aef0514001552e8": "when they improve society as a whole", + "5ad268b2d7d075001a429288": "", + "5ad268b2d7d075001a429289": "", + "5ad268b2d7d075001a42928a": "", + "5ad268b2d7d075001a42928b": "", + "5ad268b2d7d075001a42928c": "", + "572a213e6aef0514001552ee": "capability deprivation", + "572a213e6aef0514001552ef": "the end itself", + "572a213e6aef0514001552f0": "to \u201cwid[en] people\u2019s choices and the level of their achieved well-being", + "572a213e6aef0514001552f1": "to \u201cwid[en] people\u2019s choices and the level of their achieved well-being", + "572a213e6aef0514001552f2": "the ability to pursue valued goals", + "5ad2690ed7d075001a4292b0": "", + "5ad2690ed7d075001a4292b1": "", + "5ad2690ed7d075001a4292b2": "", + "5ad2690ed7d075001a4292b3": "", + "5ad2690ed7d075001a4292b4": "", + "572a2224af94a219006aa823": "they are in some way deprived of earning as much income as they would otherwise", + "572a2224af94a219006aa824": "earn as much as a healthy young man", + "572a2224af94a219006aa825": "gender roles and customs", + "572a2224af94a219006aa826": "fear of their lives", + "572a2224af94a219006aa827": "a better relevant income", + "5ad26964d7d075001a4292cc": "", + "5ad26964d7d075001a4292cd": "", + "5ad26964d7d075001a4292ce": "", + "5ad26964d7d075001a4292cf": "", + "5ad26964d7d075001a4292d0": "a better relevant income", + "57283c464b864d19001647c8": "private research", + "57283c464b864d19001647c9": "1890", + "57283c464b864d19001647ca": "seven", + "57283c464b864d19001647cb": "four", + "57283c464b864d19001647cc": "5,000", + "5acf774877cf76001a684e96": "", + "5acf774877cf76001a684e97": "", + "5acf774877cf76001a684e98": "", + "5acf774877cf76001a684e99": "U of C", + "5acf774877cf76001a684e9a": "", + "57283db6ff5b5019007d9fbc": "academic disciplines", + "57283db6ff5b5019007d9fbd": "Chicago's physics department", + "57283db6ff5b5019007d9fbe": "beneath the university's Stagg Field", + "57283db6ff5b5019007d9fbf": "University of Chicago Press", + "57283db6ff5b5019007d9fc0": "2020", + "5acf782877cf76001a684eb2": "", + "5acf782877cf76001a684eb3": "", + "5acf782877cf76001a684eb4": "Stagg Field", + "5acf782877cf76001a684eb5": "", + "5acf782877cf76001a684eb6": "", + "57283f014b864d19001647e8": "American Baptist Education Society", + "57283f014b864d19001647e9": "John D. Rockefeller", + "57283f014b864d19001647ea": "William Rainey Harper", + "57283f014b864d19001647eb": "1891", + "57283f014b864d19001647ec": "1892", + "5acf7dcf77cf76001a684f7a": "", + "5acf7dcf77cf76001a684f7b": "", + "5acf7dcf77cf76001a684f7c": "", + "5acf7dcf77cf76001a684f7d": "", + "5acf7dcf77cf76001a684f7e": "", + "57284142ff5b5019007da00a": "John D. Rockefeller", + "57284142ff5b5019007da00b": "Silas B. Cobb", + "57284142ff5b5019007da00c": "Cobb Lecture Hall", + "57284142ff5b5019007da00d": "", + "57284142ff5b5019007da00e": "Charles L. Hutchinson", + "5acf7ecb77cf76001a684fa2": "", + "5acf7ecb77cf76001a684fa3": "", + "5acf7ecb77cf76001a684fa4": "", + "5acf7ecb77cf76001a684fa5": "the Walker Museum", + "5acf7ecb77cf76001a684fa6": "", + "572843304b864d1900164848": "", + "572843304b864d1900164849": "1896", + "572843304b864d190016484a": "made a grade of A for all four years", + "572843304b864d190016484b": "Several University of Chicago professors", + "572843304b864d190016484c": "", + "5acf7fdf77cf76001a684fd4": "", + "5acf7fdf77cf76001a684fd5": "Mount Carroll", + "5acf7fdf77cf76001a684fd6": "", + "5acf7fdf77cf76001a684fd7": "", + "57284456ff5b5019007da05c": "Robert Maynard Hutchins", + "57284456ff5b5019007da05d": "1929", + "57284456ff5b5019007da05e": "24-year", + "57284456ff5b5019007da05f": "to emphasize academics over athletics", + "57284456ff5b5019007da060": "Common Core", + "5acf808877cf76001a685004": "", + "5acf808877cf76001a685005": "", + "5acf808877cf76001a685006": "", + "5acf808877cf76001a685007": "", + "5acf808877cf76001a685008": "", + "57284618ff5b5019007da0a8": "1950s", + "57284618ff5b5019007da0a9": "increasing crime and poverty", + "57284618ff5b5019007da0aa": "after their second year", + "57284618ff5b5019007da0ab": "Hyde Park", + "57284618ff5b5019007da0ac": "allowed very young students to attend college", + "5acf82c277cf76001a685064": "", + "5acf82c277cf76001a685065": "", + "5acf82c277cf76001a685066": "", + "5acf82c277cf76001a685067": "", + "5acf82c277cf76001a685068": "an early entrant program", + "572847ff3acd2414000df869": "1962", + "572847ff3acd2414000df86a": "the university's off-campus rental policies", + "572847ff3acd2414000df86b": "1967", + "572847ff3acd2414000df86c": "two", + "572847ff3acd2414000df86d": "", + "5acf86ff77cf76001a6850f8": "", + "5acf86ff77cf76001a6850f9": "", + "5acf86ff77cf76001a6850fa": "", + "5acf86ff77cf76001a6850fb": "", + "5acf86ff77cf76001a6850fc": "", + "572849b4ff5b5019007da0f2": "mid-2000s", + "572849b4ff5b5019007da0f3": "Milton Friedman Institute", + "572849b4ff5b5019007da0f4": "$200 million", + "572849b4ff5b5019007da0f5": "Chicago Theological Seminary", + "572849b4ff5b5019007da0f6": "David G. 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"Kaidu", + "5ad402ae604f3c001a3ffd60": "northeast border", + "5ad402ae604f3c001a3ffd61": "1262", + "572869b84b864d19001649ae": "preserving Mongol interests in China", + "572869b84b864d19001649af": "salt and iron", + "572869b84b864d19001649b0": "", + "572869b84b864d19001649b1": "three", + "572869b84b864d19001649b2": "Han Chinese", + "5ad402f1604f3c001a3ffd69": "", + "5ad402f1604f3c001a3ffd6a": "", + "5ad402f1604f3c001a3ffd6b": "local administrative structure of past Chinese dynasties", + "5ad402f1604f3c001a3ffd6c": "", + "5ad402f1604f3c001a3ffd6d": "", + "57286b003acd2414000df9c1": "Karakorum in Mongolia", + "57286b003acd2414000df9c2": "Khanbaliq", + "57286b003acd2414000df9c3": "1264", + "57286b003acd2414000df9c4": "Zhongdu", + "57286b003acd2414000df9c5": "Confucian propriety and ancestor veneration", + "5ad40346604f3c001a3ffd73": "Karakorum in Mongolia", + "5ad40346604f3c001a3ffd74": "", + "5ad40346604f3c001a3ffd75": "", + "5ad40346604f3c001a3ffd76": "", + "5ad40346604f3c001a3ffd77": "", + "57286bb84b864d19001649c8": "commercial, scientific, and cultural", + "57286bb84b864d19001649c9": "Mongol peace", + "57286bb84b864d19001649ca": "southern China", + "57286bb84b864d19001649cb": "Daidu in the north", + "57286bb84b864d19001649cc": "Marco Polo", + "5ad40397604f3c001a3ffd83": "", + "5ad40397604f3c001a3ffd84": "Mongol peace", + "5ad40397604f3c001a3ffd85": "", + "5ad40397604f3c001a3ffd86": "Daidu", + "5ad40397604f3c001a3ffd87": "Marco Polo", + "57286c8cff5b5019007da218": "the Song Emperor", + "57286c8cff5b5019007da219": "1115", + "57286c8cff5b5019007da21a": "1234", + "57286c8cff5b5019007da21b": "", + "57286c8cff5b5019007da21c": "30,000", + "5ad403df604f3c001a3ffd9b": "the Song Emperor", + "5ad403df604f3c001a3ffd9c": "", + "5ad403df604f3c001a3ffd9d": "1234", + "5ad403df604f3c001a3ffd9e": "Kong Zhu", + "57286d4f2ca10214002da328": "northern China", + "57286d4f2ca10214002da329": "between 1268 and 1273", + "57286d4f2ca10214002da32a": "Yangzi River basin", + "57286d4f2ca10214002da32b": "Hangzhou", + "57286d4f2ca10214002da32c": "drowned", + "5ad40432604f3c001a3ffdbb": "northern China", + "5ad40432604f3c001a3ffdbc": "between 1268 and 1273", + "5ad40432604f3c001a3ffdbd": "Yangzi River basin", + "5ad40432604f3c001a3ffdbe": "Hangzhou", + "5ad40432604f3c001a3ffdbf": "drowned", + "57286dfa2ca10214002da332": "1279", + "57286dfa2ca10214002da333": "an inauspicious typhoon", + "57286dfa2ca10214002da334": "Vietnam \u0110\u1ea1i Vi\u1ec7t", + "57286dfa2ca10214002da335": "Battle of B\u1ea1ch \u0110\u1eb1ng", + "57286dfa2ca10214002da336": "1288", + "5ad40480604f3c001a3ffdcf": "Wars and construction projects", + "5ad40480604f3c001a3ffdd0": "", + "5ad40480604f3c001a3ffdd1": "Vietnam \u0110\u1ea1i Vi\u1ec7t", + "5ad40480604f3c001a3ffdd2": "", + "57286ead2ca10214002da346": "1253", + "57286ead2ca10214002da347": "Zhenjin", + "57286ead2ca10214002da348": "1285", + "57286ead2ca10214002da349": "Emperor Chengzong", + "57286ead2ca10214002da34a": "1294 to 1307", + "5ad404d4604f3c001a3ffde7": "1253", + "5ad404d4604f3c001a3ffde8": "", + "5ad404d4604f3c001a3ffde9": "1294", + "5ad404d4604f3c001a3ffdea": "", + "5ad404d4604f3c001a3ffdeb": "1307", + "57286f373acd2414000df9db": "Buyantu Khan", + "57286f373acd2414000df9dc": "", + "57286f373acd2414000df9dd": "Li Meng", + "57286f373acd2414000df9de": "Department of State Affairs", + "57286f373acd2414000df9df": "1313", + "5ad40515604f3c001a3ffe05": "", + "5ad40515604f3c001a3ffe06": "actively support and adopt mainstream Chinese culture", + "5ad40515604f3c001a3ffe07": "Mongol elite", + "5ad40515604f3c001a3ffe08": "", + "5ad40515604f3c001a3ffe09": "", + "57286fa83acd2414000df9e5": "Emperor Gegeen Khan", + "57286fa83acd2414000df9e6": "1321 to 1323", + "57286fa83acd2414000df9e7": "Baiju", + "57286fa83acd2414000df9e8": "the comprehensive institutions of the Great Yuan", + "57286fa83acd2414000df9e9": "five", + "5ad40582604f3c001a3ffe19": "", + "5ad40582604f3c001a3ffe1a": "", + "5ad40582604f3c001a3ffe1b": "Baiju", + "5ad40582604f3c001a3ffe1c": "the comprehensive institutions of the Great Yuan", + "5ad40582604f3c001a3ffe1d": "five", + "5728705c2ca10214002da35a": "Shangdu", + "5728705c2ca10214002da35b": "War of the Two Capitals", + "5728705c2ca10214002da35c": "four days", + "5728705c2ca10214002da35d": "El Tem\u00fcr", + "5728705c2ca10214002da35e": "Tugh Tem\u00fcr", + "5ad405f0604f3c001a3ffe2d": "Tugh Tem\u00fcr was recalled to Khanbaliq by the Qipchaq commander El Tem\u00fcr", + "5ad405f0604f3c001a3ffe2e": "", + "5ad405f0604f3c001a3ffe2f": "four days", + "5ad405f0604f3c001a3ffe30": "Kusala", + "5ad405f0604f3c001a3ffe31": "Tugh Tem\u00fcr", + "5728710c3acd2414000df9ef": "his cultural contribution", + "5728710c3acd2414000df9f0": "Academy of the Pavilion of the Star of Literature", + "5728710c3acd2414000df9f1": "1329", + "5728710c3acd2414000df9f2": "Jingshi Dadian", + "5728710c3acd2414000df9f3": "Confucianism", + "5ad40639604f3c001a3ffe4b": "", + "5ad40639604f3c001a3ffe4c": "", + "5ad40639604f3c001a3ffe4d": "", + "5ad40639604f3c001a3ffe4e": "", + "5ad40639604f3c001a3ffe4f": "", + "572871bd3acd2414000dfa03": "1332", + "572871bd3acd2414000dfa04": "", + "572871bd3acd2414000dfa05": "13", + "572871bd3acd2414000dfa06": "nine", + "572871bd3acd2414000dfa07": "Liao, Jin, and Song", + "5ad4066a604f3c001a3ffe5f": "", + "5ad4066a604f3c001a3ffe60": "", + "5ad4066a604f3c001a3ffe61": "", + "5ad4066a604f3c001a3ffe62": "nine", + "5ad4066a604f3c001a3ffe63": "", + "572872822ca10214002da374": "struggle, famine, and bitterness", + "572872822ca10214002da375": "the Mongols beyond the Middle Kingdom saw them as too Chinese", + "572872822ca10214002da376": "the army and the populace", + "572872822ca10214002da377": "", + "572872822ca10214002da378": "intrigues and rivalries. Uninterested in administration", + "5ad406b6604f3c001a3ffe73": "", + "5ad406b6604f3c001a3ffe74": "the Mongols beyond the Middle Kingdom saw them as too Chinese", + "5ad406b6604f3c001a3ffe75": "the army and the populace", + "5ad406b6604f3c001a3ffe76": "", + "5ad406b6604f3c001a3ffe77": "intrigues and rivalries", + "57287338ff5b5019007da232": "late 1340s", + "57287338ff5b5019007da233": "Red Turban Rebellion", + "57287338ff5b5019007da234": "fear of betrayal", + "57287338ff5b5019007da235": "Red Turban rebels", + "57287338ff5b5019007da236": "1368\u20131644", + "5ad406e9604f3c001a3ffe7d": "late 1340s", + "5ad406e9604f3c001a3ffe7e": "the Red Turban Rebellion", + "5ad406e9604f3c001a3ffe7f": "", + "5ad406e9604f3c001a3ffe80": "Red Turban rebels", + "5ad406e9604f3c001a3ffe81": "1644", + "572878942ca10214002da3a2": "communications between Yuan dynasty and its ally and subordinate in Persia, the Ilkhanate", + "572878942ca10214002da3a3": "communications between Yuan dynasty and its ally and subordinate in Persia, the Ilkhanate", + "572878942ca10214002da3a4": "Ilkhanate", + "572878942ca10214002da3a5": "carrots, turnips, new varieties of lemons, eggplants, and melons, high-quality granulated sugar, and cotton", + "5ad40726604f3c001a3ffe8f": "", + "5ad40726604f3c001a3ffe90": "", + "5ad40726604f3c001a3ffe91": "", + "572879574b864d1900164a14": "Western", + "572879574b864d1900164a15": "Nestorianism and Roman Catholicism", + "572879574b864d1900164a16": "Taoism", + "572879574b864d1900164a17": "Confucian", + "572879574b864d1900164a18": "travel literature, cartography, geography, and scientific education", + "5ad40762604f3c001a3ffe95": "", + "5ad40762604f3c001a3ffe96": "", + "5ad40762604f3c001a3ffe97": "Taoism", + "5ad40762604f3c001a3ffe98": "Confucian", + "5ad40762604f3c001a3ffe99": "", + "57287b4a4b864d1900164a28": "Venetian Marco Polo", + "57287b4a4b864d1900164a29": "", + "57287b4a4b864d1900164a2a": "the Travels of Marco Polo", + "57287b4a4b864d1900164a2b": "", + "57287b4a4b864d1900164a2c": "through contact with Persian traders", + "5ad40796604f3c001a3ffea9": "", + "5ad40796604f3c001a3ffeaa": "", + "5ad40796604f3c001a3ffeab": "", + "5ad40796604f3c001a3ffeac": "", + "57287c142ca10214002da3d0": "Guo Shoujing", + "57287c142ca10214002da3d1": "365.2425 days of the year", + "57287c142ca10214002da3d2": "granaries were ordered built throughout the empire", + "57287c142ca10214002da3d3": "Beijing", + "57287c142ca10214002da3d4": "sorghum", + "5ad407de604f3c001a3ffebb": "", + "5ad407de604f3c001a3ffebc": "365.2425 days of the year", + "5ad407de604f3c001a3ffebd": "granaries were ordered built throughout the empire", + "5ad407de604f3c001a3ffebe": "", + "5ad407de604f3c001a3ffebf": "sorghum", + "57287ccb2ca10214002da3da": "non-native Chinese people", + "57287ccb2ca10214002da3db": "Eternal Heaven", + "57287ccb2ca10214002da3dc": "Song dynasty and the Ming dynasty", + "57287ccb2ca10214002da3dd": "Ming dynasty", + "57287ccb2ca10214002da3de": "a period of foreign domination", + "5ad4081b604f3c001a3ffed9": "", + "5ad4081b604f3c001a3ffeda": "", + "5ad4081b604f3c001a3ffedb": "Ming dynasty", + "5ad4081b604f3c001a3ffedc": "Ming dynasty", + "57287d4a2ca10214002da3e4": "Han Chinese, Khitans, Jurchens, Mongols, and Tibetan Buddhists", + "57287d4a2ca10214002da3e5": "Tang, Song, as well as Khitan Liao and Jurchen Jin dynasties", + "57287d4a2ca10214002da3e6": "Liu Bingzhong and Yao Shu", + "57287d4a2ca10214002da3e7": "Chinese tripartite", + "57287d4a2ca10214002da3e8": "Han Chinese, Khitans, Jurchens, Mongols, and Tibetan Buddhists", + "5ad408aa604f3c001a3ffeff": "", + "5ad408aa604f3c001a3fff00": "", + "5ad408aa604f3c001a3fff01": "", + "5ad408aa604f3c001a3fff02": "", + "57287ddf3acd2414000dfa3f": "the Privy Council", + "57287ddf3acd2414000dfa40": "since the Sui and Tang dynasties", + "57287ddf3acd2414000dfa41": "Mongols and Semuren", + "57287ddf3acd2414000dfa42": "", + "5ad408ed604f3c001a3fff0f": "the Privy Council", + "5ad408ed604f3c001a3fff10": "", + "5ad408ed604f3c001a3fff11": "", + "5ad408ed604f3c001a3fff12": "", + "57287e512ca10214002da3f8": "1269", + "57287e512ca10214002da3f9": "Mongolian, Tibetan, and Chinese", + "57287e512ca10214002da3fa": "converse well in the language", + "57287e512ca10214002da3fb": "Tugh Temur", + "57287e512ca10214002da3fc": "Emperor Wenzong", + "5ad40955604f3c001a3fff2b": "", + "5ad40955604f3c001a3fff2c": "", + "5ad40955604f3c001a3fff2d": "", + "5ad40955604f3c001a3fff2e": "", + "5ad40955604f3c001a3fff2f": "", + "57287ee3ff5b5019007da274": "1290", + "57287ee3ff5b5019007da275": "1291", + "57287ee3ff5b5019007da276": "costs of equipping and dispatching men for their tours of duty", + "5ad40995604f3c001a3fff45": "", + "5ad40995604f3c001a3fff46": "", + "5ad40995604f3c001a3fff47": "", + "57287f6a3acd2414000dfa51": "painting, mathematics, calligraphy, poetry, and theater", + "57287f6a3acd2414000dfa52": "painting, poetry, and calligraphy", + "57287f6a3acd2414000dfa53": "the Song dynasty", + "57287f6a3acd2414000dfa54": "qu", + "57287f6a3acd2414000dfa55": "zaju", + "5ad409d6604f3c001a3fff5f": "poetry, painting, and calligraphy", + "5ad409d6604f3c001a3fff60": "painting, poetry, and calligraphy", + "5ad409d6604f3c001a3fff61": "", + "5ad409d6604f3c001a3fff62": "", + "57287fec4b864d1900164a3c": "", + "57287fec4b864d1900164a3d": "Buddhism", + "57287fec4b864d1900164a3e": "", + "57287fec4b864d1900164a3f": "Bureau of Buddhist and Tibetan Affairs", + "57287fec4b864d1900164a40": "Sakya", + "5ad40a0e604f3c001a3fff79": "western khanates", + "5ad40a0e604f3c001a3fff7a": "", + "5ad40a0e604f3c001a3fff7b": "Tibetan Buddhism", + "5ad40a0e604f3c001a3fff7d": "", + "5728804b4b864d1900164a46": "1249", + "5728804b4b864d1900164a47": "1314", + "5728804b4b864d1900164a48": "matrices", + "5728804b4b864d1900164a49": "polynomial algebra", + "5728804b4b864d1900164a4a": "1303", + "5ad40a41604f3c001a3fff8b": "1249\u20131314", + "5ad40a41604f3c001a3fff8c": "", + "5ad40a41604f3c001a3fff8d": "matrices", + "5ad40a41604f3c001a3fff8e": "", + "5ad40a41604f3c001a3fff8f": "", + "5728809f2ca10214002da40c": "applied mathematics", + "5728809f2ca10214002da40d": "cubic interpolation formula", + "5728809f2ca10214002da40e": "Shoushi Li", + "5728809f2ca10214002da40f": "Shoushi Li", + "5728809f2ca10214002da410": "1281", + "5ad40a72604f3c001a3fffa9": "", + "5ad40a72604f3c001a3fffaa": "cubic interpolation formula", + "5ad40a72604f3c001a3fffab": "", + "5ad40a72604f3c001a3fffac": "", + "5ad40a72604f3c001a3fffad": "", + "572881022ca10214002da416": "non-Mongol physicians", + "572881022ca10214002da417": "herbal remedies", + "572881022ca10214002da418": "herbal remedies", + "572881022ca10214002da419": "Imperial Academy of Medicine", + "572881022ca10214002da41a": "it ensured a high income and medical ethics were compatible with Confucian virtues", + "5ad40ac5604f3c001a3fffc7": "non-Mongol physicians", + "5ad40ac5604f3c001a3fffc8": "", + "5ad40ac5604f3c001a3fffc9": "", + "5ad40ac5604f3c001a3fffca": "Imperial Academy of Medicine", + "5ad40ac5604f3c001a3fffcb": "", + "572881704b864d1900164a50": "four", + "572881704b864d1900164a51": "All four schools were based on the same intellectual foundation, but advocated different theoretical approaches toward medicine", + "572881704b864d1900164a52": "Under the Mongols, the practice of Chinese medicine spread to other parts of the empire", + "572881704b864d1900164a53": "acupuncture, moxibustion, pulse diagnosis, and various herbal drugs and elixirs", + "572881704b864d1900164a54": "1347", + "5ad40af0604f3c001a3fffdf": "", + "5ad40af0604f3c001a3fffe0": "", + "5ad40af0604f3c001a3fffe1": "military campaigns", + "5ad40af0604f3c001a3fffe2": "", + "572881d34b864d1900164a5a": "Muslim medicine", + "572881d34b864d1900164a5b": "Jesus the Interpreter", + "572881d34b864d1900164a5c": "1263", + "572881d34b864d1900164a5d": "humoral system", + "572881d34b864d1900164a5e": "", + "5ad40b55604f3c001a3ffffb": "", + "5ad40b55604f3c001a3ffffc": "", + "5ad40b55604f3c001a3ffffd": "", + "5ad40b55604f3c001a3ffffe": "huihui or Muslim medicine", + "5ad40b55604f3c001a3fffff": "", + "572882242ca10214002da420": "through Kingdom of Qocho and Tibetan intermediaries", + "572882242ca10214002da421": "Wang Zhen", + "572882242ca10214002da422": "12th century", + "572882242ca10214002da423": "T\u00f6regene Khatun", + "572882242ca10214002da424": "1273", + "5ad40b87604f3c001a400005": "", + "5ad40b87604f3c001a400006": "", + "5ad40b87604f3c001a400007": "", + "5ad40b87604f3c001a400008": "T\u00f6regene Khatun", + "5ad40b87604f3c001a400009": "", + "5728827b2ca10214002da42a": "chao", + "5728827b2ca10214002da42b": "bark of mulberry trees", + "5728827b2ca10214002da42c": "1275", + "5728827b2ca10214002da42d": "woodblocks", + "5728827b2ca10214002da42e": "1294", + "5ad40bd9604f3c001a400035": "", + "5ad40bd9604f3c001a400036": "bark of mulberry trees", + "5ad40bd9604f3c001a400037": "", + "5ad40bd9604f3c001a400038": "woodblocks", + "5ad40bd9604f3c001a400039": "", + "572883153acd2414000dfa6f": "traditional Chinese autocratic-bureaucratic system", + "572883153acd2414000dfa70": "traditional Chinese autocratic-bureaucratic system", + "572883153acd2414000dfa71": "various allied groups from Central Asia and the western end of the empire", + "572883153acd2414000dfa72": "fear of transferring power to the ethnic Chinese under their rule", + "572883153acd2414000dfa73": "Ilkhanate", + "5ad40c2d604f3c001a400049": "", + "5ad40c2d604f3c001a40004a": "", + "5ad40c2d604f3c001a40004b": "Mongols and the Semuren", + "5ad40c2d604f3c001a40004c": "unequal", + "572883a33acd2414000dfa79": "Central Asian Muslims", + "572883a33acd2414000dfa7a": "Han Chinese and Khitans", + "572883a33acd2414000dfa7b": "Bukhara", + "572883a33acd2414000dfa7c": "artisans and farmers", + "572883a33acd2414000dfa7d": "Qara-Khitay", + "5ad40c62604f3c001a400065": "", + "5ad40c62604f3c001a400066": "", + "5ad40c62604f3c001a400067": "", + "5ad40c62604f3c001a400068": "", + "57288428ff5b5019007da28e": "circumcision", + "57288428ff5b5019007da28f": "Kosher butchering", + "57288428ff5b5019007da290": "Zhu Yuanzhang", + "57288428ff5b5019007da291": "thanks", + "57288428ff5b5019007da292": "Muslims in the semu class", + "5ad40cac604f3c001a400087": "circumcision", + "5ad40cac604f3c001a400088": "Kosher butchering", + "5ad40cac604f3c001a400089": "", + "5ad40cac604f3c001a40008a": "", + "5ad40cac604f3c001a40008b": "the Yuan dynasty", + "5728848cff5b5019007da298": "Frederick W. Mote", + "5728848cff5b5019007da299": "", + "5728848cff5b5019007da29a": "rich and well socially standing", + "5728848cff5b5019007da29b": "lived in poverty and were ill treated", + "5ad40cdb604f3c001a400091": "Frederick W. Mote", + "5ad40cdb604f3c001a400092": "", + "5ad40cdb604f3c001a400093": "rich and well socially standing", + "5ad40cdb604f3c001a400094": "", + "572885023acd2414000dfa83": "Northern", + "572885023acd2414000dfa84": "Southern", + "572885023acd2414000dfa85": "southern China withstood and fought to the last before caving in", + "572885023acd2414000dfa86": "they surrendered to the Mongols", + "572885023acd2414000dfa87": "private southern Chinese manufacturers and merchants", + "5ad40d28604f3c001a4000b5": "", + "5ad40d28604f3c001a4000b6": "", + "5ad40d28604f3c001a4000b7": "", + "5ad40d28604f3c001a4000b8": "", + "5ad40d28604f3c001a4000b9": "", + "5728855d3acd2414000dfa8d": "Uighurs of the Kingdom of Qocho", + "5728855d3acd2414000dfa8e": "Karluk Kara-Khanid ruler", + "5728855d3acd2414000dfa8f": "Korean King", + "5728855d3acd2414000dfa90": "the Uighurs surrendered to the Mongols first", + "5ad40d50604f3c001a4000c9": "Uighurs of the Kingdom of Qocho", + "5ad40d50604f3c001a4000ca": "Karluk Kara-Khanid ruler", + "5ad40d50604f3c001a4000cb": "Korean King", + "5ad40d50604f3c001a4000cc": "", + "572885c44b864d1900164a78": "The Central Region", + "572885c44b864d1900164a79": "Central Secretariat", + "572885c44b864d1900164a7a": "Khanbaliq", + "572885c44b864d1900164a7b": "Beijing", + "572885c44b864d1900164a7c": "Zhongshu Sheng", + "5ad40d89604f3c001a4000d1": "", + "5ad40d89604f3c001a4000d2": "", + "5ad40d89604f3c001a4000d3": "", + "5ad40d89604f3c001a4000d4": "", + "5ad40d89604f3c001a4000d5": "", + "5728eff82ca10214002daadc": "disease", + "5728eff82ca10214002daadd": "pathogens", + "5728eff82ca10214002daade": "neuroimmune system", + "5728eff82ca10214002daadf": "the blood\u2013brain barrier, blood\u2013cerebrospinal fluid barrier, and similar fluid\u2013brain barriers", + "572a14af3f37b319004786c1": "pathogens", + "572a14af3f37b319004786c2": "humoral immunity versus cell-mediated immunity", + "572a14af3f37b319004786c3": "innate immune system versus the adaptive immune system, or humoral immunity versus cell-mediated immunity", + "572a14af3f37b319004786c4": "neuroimmune system", + "5ad49c34ba00c4001a268d9a": "", + "5ad49c34ba00c4001a268d9b": "", + "5ad49c34ba00c4001a268d9c": "", + "5ad49c34ba00c4001a268d9d": "", + "5ad49c34ba00c4001a268d9e": "the blood\u2013brain barrier, blood\u2013cerebrospinal fluid barrier, and similar fluid\u2013brain barriers", + "5728f2e26aef051400154896": "Immunodeficiency", + "5728f2e26aef051400154897": "autoimmunity", + "5728f2e26aef051400154898": "Immunology", + "5728f2e26aef051400154899": "HIV/AIDS", + "5ad49faaba00c4001a268e24": "", + "5ad49faaba00c4001a268e25": "hyperactive", + "5ad49faaba00c4001a268e26": "hyperactive", + "5ad49faaba00c4001a268e27": "", + "5ad49faaba00c4001a268e28": "", + "5728f3724b864d1900165116": "Robert Koch", + "5728f3724b864d1900165117": "microorganisms", + "5728f3724b864d1900165118": "yellow fever", + "5728f3724b864d1900165119": "430 BC", + "5ad4a049ba00c4001a268e42": "", + "5ad4a049ba00c4001a268e43": "", + "5ad4a049ba00c4001a268e44": "Pierre-Louis Moreau de Maupertuis", + "5ad4a049ba00c4001a268e45": "", + "5ad4a049ba00c4001a268e46": "", + "5728f6446aef0514001548e4": "Innate", + "5728f6446aef0514001548e5": "adaptive immune system", + "5728f6446aef0514001548e6": "an immunological memory", + "5728f6446aef0514001548e7": "physical barriers", + "5ad4a110ba00c4001a268e60": "layered defenses of increasing specificity", + "5ad4a110ba00c4001a268e61": "", + "5ad4a110ba00c4001a268e62": "", + "5ad4a110ba00c4001a268e63": "improved response", + "5ad4a110ba00c4001a268e64": "", + "5728f7774b864d190016512e": "self and non-self", + "5728f7774b864d190016512f": "self molecules", + "5728f7774b864d1900165130": "non-self molecules", + "5728f7774b864d1900165131": "antigens", + "5728f7774b864d1900165132": "specific immune receptors", + "5ad4a682ba00c4001a268eca": "", + "5ad4a682ba00c4001a268ecb": "antigens", + "5ad4a682ba00c4001a268ecc": "", + "5ad4a682ba00c4001a268ecd": "", + "5ad4a682ba00c4001a268ece": "", + "5728f9882ca10214002dab5a": "pattern recognition receptors", + "5728f9882ca10214002dab5b": "innate immune system", + "5728f9882ca10214002dab5c": "microorganisms", + "5728f9882ca10214002dab5d": "non-specific", + "5ad4a75aba00c4001a268ee8": "", + "5ad4a75aba00c4001a268ee9": "", + "5ad4a75aba00c4001a268eea": "", + "5ad4a75aba00c4001a268eeb": "", + "5ad4a75aba00c4001a268eec": "", + "5728fb002ca10214002dab6a": "the exoskeleton", + "5728fb002ca10214002dab6b": "waxy cuticle", + "5728fb002ca10214002dab6c": "coughing and sneezing", + "5728fb002ca10214002dab6d": "mucus", + "5728fb002ca10214002dab6e": "", + "5ad4abe25b96ef001a109d64": "", + "5ad4abe25b96ef001a109d65": "", + "5ad4abe25b96ef001a109d66": "", + "5ad4abe25b96ef001a109d67": "", + "5ad4abe25b96ef001a109d68": "", + "5728fc2eaf94a219006a9ec7": "\u03b2-defensins", + "5728fc2eaf94a219006a9ec8": "lysozyme and phospholipase A2", + "5728fc2eaf94a219006a9ec9": "defensins and zinc", + "5728fc2eaf94a219006a9eca": "gastric acid and proteases", + "5728fc2eaf94a219006a9ecb": "menarche", + "5ad4acbd5b96ef001a109d78": "antimicrobial peptides", + "5ad4acbd5b96ef001a109d79": "", + "5ad4acbd5b96ef001a109d7a": "", + "5ad4acbd5b96ef001a109d7b": "", + "5ad4acbd5b96ef001a109d7c": "gastric acid and proteases", + "5728fd206aef05140015494c": "", + "5728fd206aef05140015494d": "fungi", + "5728fd206aef05140015494e": "lactobacilli", + "5728fd206aef05140015494f": "pH or available iron", + "5ad4b0f25b96ef001a109dbc": "", + "5ad4b0f25b96ef001a109dbd": "", + "5ad4b0f25b96ef001a109dbe": "oral antibiotics", + "5ad4b0f25b96ef001a109dbf": "", + "5ad4b0f25b96ef001a109dc0": "", + "572900f73f37b31900477f69": "Inflammation", + "572900f73f37b31900477f6a": "increased blood flow into tissue", + "572900f73f37b31900477f6b": "eicosanoids and cytokines", + "572900f73f37b31900477f6c": "prostaglandins", + "572900f73f37b31900477f6d": "interleukins", + "5ad4b1895b96ef001a109dc6": "", + "5ad4b1895b96ef001a109dc7": "", + "5ad4b1895b96ef001a109dc8": "", + "5ad4b1895b96ef001a109dc9": "", + "5ad4b1895b96ef001a109dca": "", + "572905ce1d04691400778f83": "phagocytes", + "572905ce1d04691400778f84": "cytokines", + "572905ce1d04691400778f85": "phagosome", + "572905ce1d04691400778f86": "phagolysosome", + "572905ce1d04691400778f87": "acquiring nutrients", + "5ad4ca235b96ef001a10a0b6": "", + "5ad4ca235b96ef001a10a0b7": "", + "5ad4ca235b96ef001a10a0b8": "intracellular vesicle called a phagosome", + "5ad4ca235b96ef001a10a0b9": "by the activity of digestive enzymes", + "5ad4ca235b96ef001a10a0ba": "defense mechanism", + "5729081d3f37b31900477fab": "Neutrophils and macrophages", + "5729081d3f37b31900477fac": "Neutrophils", + "5729081d3f37b31900477fad": "50% to 60%", + "5729081d3f37b31900477fae": "chemotaxis", + "5729081d3f37b31900477faf": "interleukin 1", + "5ad4cb055b96ef001a10a0de": "Neutrophils and macrophages", + "5ad4cb055b96ef001a10a0df": "", + "5ad4cb055b96ef001a10a0e0": "", + "5ad4cb055b96ef001a10a0e1": "", + "5ad4cb055b96ef001a10a0e2": "", + "572908c13f37b31900477fbd": "Leukocytes", + "572908c13f37b31900477fbe": "Leukocytes", + "572908c13f37b31900477fbf": "adaptive immune system", + "572908c13f37b31900477fc0": "macrophages, neutrophils, and dendritic cells", + "5ad4c94f5b96ef001a10a098": "", + "5ad4c94f5b96ef001a10a099": "", + "5ad4c94f5b96ef001a10a09a": "", + "5ad4c94f5b96ef001a10a09b": "", + "5ad4c94f5b96ef001a10a09c": "", + "5729efab3f37b319004785cf": "Dendritic cells", + "5729efab3f37b319004785d0": "neuronal dendrites", + "5729efab3f37b319004785d1": "T cells", + "5729efab3f37b319004785d2": "T cells", + "5ad4cd245b96ef001a10a110": "", + "5ad4cd245b96ef001a10a111": "", + "5ad4cd245b96ef001a10a112": "", + "5ad4cd245b96ef001a10a113": "", + "5ad4cd245b96ef001a10a114": "", + "5729f06f1d04691400779673": "Natural killer cells", + "5729f06f1d04691400779674": "missing self", + "5729f06f1d04691400779675": "MHC I", + "5729f06f1d04691400779676": "killer cell immunoglobulin receptors", + "5ad4cf8e5b96ef001a10a148": "", + "5ad4cf8e5b96ef001a10a149": "", + "5ad4cf8e5b96ef001a10a14a": "because they express intact self MHC antigens", + "5ad4cf8e5b96ef001a10a14b": "", + "5ad4cf8e5b96ef001a10a14c": "", + "5729f12e3f37b319004785e1": "early vertebrates", + "5729f12e3f37b319004785e2": "antigen presentation", + "5729f12e3f37b319004785e3": "specific pathogens or pathogen-infected cells", + "5ad4d0385b96ef001a10a178": "", + "5ad4d0385b96ef001a10a179": "", + "5ad4d0385b96ef001a10a17a": "", + "5ad4d0385b96ef001a10a17b": "", + "5ad4d0385b96ef001a10a17c": "specific memory cells", + "5729f1fcaf94a219006aa6d3": "the killer T cell and the helper T cell", + "5729f1fcaf94a219006aa6d4": "regulatory T cells", + "5729f1fcaf94a219006aa6d5": "Class I MHC", + "5729f1fcaf94a219006aa6d6": "Class II MHC molecules", + "5729f1fcaf94a219006aa6d7": "\u03b3\u03b4 T cells", + "5ad4d10e5b96ef001a10a1a0": "", + "5ad4d10e5b96ef001a10a1a1": "", + "5ad4d10e5b96ef001a10a1a2": "", + "5ad4d10e5b96ef001a10a1a3": "", + "5ad4d10e5b96ef001a10a1a4": "", + "5729f39a6aef05140015514c": "Killer T cells", + "5729f39a6aef05140015514d": "TCR", + "5729f39a6aef05140015514e": "CD8", + "5729f39a6aef05140015514f": "perforin", + "5729f39a6aef051400155150": "granulysin", + "5ad4d2105b96ef001a10a1c6": "", + "5ad4d2105b96ef001a10a1c7": "", + "5ad4d2105b96ef001a10a1c8": "", + "5ad4d2105b96ef001a10a1c9": "", + "5ad4d2105b96ef001a10a1ca": "", + "5729f4b41d0469140077968b": "CD4", + "5729f4b41d0469140077968c": "200\u2013300", + "5729f4b41d0469140077968d": "200\u2013300", + "5729f4b41d0469140077968e": "cytokines", + "5729f4b41d0469140077968f": "CD40", + "5ad4d2d65b96ef001a10a1f8": "", + "5ad4d2d65b96ef001a10a1f9": "Helper T cells", + "5ad4d2d65b96ef001a10a1fa": "", + "5ad4d2d65b96ef001a10a1fb": "", + "5ad4d2d65b96ef001a10a1fc": "", + "5729f5a03f37b31900478605": "helper T cells, cytotoxic T cells and NK cells", + "5729f5a03f37b31900478606": "TCR", + "5729f5a03f37b31900478607": "\u03b3\u03b4 T cells", + "5729f5a03f37b31900478608": "", + "5729f5a03f37b31900478609": "V\u03b39/V\u03b42 T cells", + "5ad4d4795b96ef001a10a232": "", + "5ad4d4795b96ef001a10a233": "", + "5ad4d4795b96ef001a10a234": "", + "5ad4d4795b96ef001a10a235": "", + "5729f69caf94a219006aa6f9": "A B cell", + "5729f69caf94a219006aa6fa": "proteolysis", + "5729f69caf94a219006aa6fb": "lymphokines", + "5ad4d52a5b96ef001a10a260": "", + "5ad4d52a5b96ef001a10a261": "", + "5ad4d52a5b96ef001a10a262": "", + "5ad4d52a5b96ef001a10a263": "", + "5ad4d52a5b96ef001a10a264": "", + "5729f799af94a219006aa707": "long-lived memory cells", + "5729f799af94a219006aa708": "adaptive", + "5729f799af94a219006aa709": "passive short-term memory or active long-term memory", + "5729f799af94a219006aa70a": "specific pathogen", + "5ad4d6a75b96ef001a10a2c6": "", + "5ad4d6a75b96ef001a10a2c7": "", + "5ad4d6a75b96ef001a10a2c8": "", + "5ad4d6a75b96ef001a10a2c9": "", + "5ad4d6a75b96ef001a10a2ca": "", + "5729f8516aef05140015516c": "microbes", + "5729f8516aef05140015516d": "IgG", + "5729f8516aef05140015516e": "Breast milk or colostrum", + "5729f8516aef05140015516f": "passive", + "5ad4d7395b96ef001a10a2f4": "", + "5ad4d7395b96ef001a10a2f5": "", + "5ad4d7395b96ef001a10a2f6": "", + "5ad4d7395b96ef001a10a2f7": "", + "5ad4d7395b96ef001a10a2f8": "", + "5729f9953f37b3190047861f": "immunomodulators", + "5729f9953f37b31900478620": "adaptive and innate", + "5729f9953f37b31900478621": "lupus erythematosus", + "5729f9953f37b31900478622": "immunosuppressive", + "5ad4e61e5b96ef001a10a5ac": "", + "5ad4e61e5b96ef001a10a5ad": "", + "5ad4e61e5b96ef001a10a5ae": "", + "5ad4e61e5b96ef001a10a5af": "testosterone", + "5ad4e61e5b96ef001a10a5b0": "", + "5729fa40af94a219006aa70f": "NFIL3", + "5729fa40af94a219006aa710": "heart disease, chronic pain, and asthma", + "5729fa40af94a219006aa711": "sleep deprivation", + "5ad4ea425b96ef001a10a626": "", + "5ad4ea425b96ef001a10a627": "", + "5ad4ea425b96ef001a10a628": "", + "5ad4ea425b96ef001a10a629": "heart disease, chronic pain, and asthma", + "5ad4ea425b96ef001a10a62a": "", + "5729fb003f37b31900478627": "progressive decline in hormone levels with age", + "5729fb003f37b31900478628": "vitamin D", + "5729fb003f37b31900478629": "thyroid hormone", + "5729fb003f37b3190047862a": "cholecalciferol", + "5ad4e90e5b96ef001a10a608": "", + "5ad4e90e5b96ef001a10a609": "", + "5ad4e90e5b96ef001a10a60a": "", + "5ad4e90e5b96ef001a10a60b": "", + "5ad4e90e5b96ef001a10a60c": "", + "5729fc3d1d0469140077969d": "killer T cells", + "5729fc3d1d0469140077969e": "MHC class I", + "5729fc3d1d0469140077969f": "viral antigens", + "5729fc3d1d046914007796a0": "antibodies", + "5ad4e4cf5b96ef001a10a586": "", + "5ad4e4cf5b96ef001a10a587": "", + "5ad4e4cf5b96ef001a10a588": "", + "5ad4e4cf5b96ef001a10a589": "", + "5ad4e4cf5b96ef001a10a58a": "", + "5729fd111d046914007796a5": "phagocytic", + "5729fd111d046914007796a6": "Pathogen-associated molecular patterns or PAMPs", + "5729fd111d046914007796a7": "rapid apoptosis", + "5729fd111d046914007796a8": "Systemic acquired resistance", + "5729fd111d046914007796a9": "RNA silencing", + "5ad4e3a15b96ef001a10a560": "phagocytic cells", + "5ad4e3a15b96ef001a10a561": "the plant produces a localized hypersensitive response", + "5ad4e3a15b96ef001a10a562": "", + "5ad4e3a15b96ef001a10a563": "", + "5ad4e3a15b96ef001a10a564": "", + "5729fe5c3f37b3190047862f": "autoimmune disorders", + "5729fe5c3f37b31900478630": "self and non-self", + "5729fe5c3f37b31900478631": "thymus and bone marrow", + "5729fe5c3f37b31900478632": "self\" peptides", + "5ad4db615b96ef001a10a434": "", + "5ad4db615b96ef001a10a435": "", + "5ad4db615b96ef001a10a436": "to present young lymphocytes with self antigens produced throughout the body and to eliminate those cells that recognize self-antigens", + "5ad4db615b96ef001a10a437": "", + "5ad4db615b96ef001a10a438": "", + "5729fefbaf94a219006aa739": "Immunodeficiencies", + "5729fefbaf94a219006aa73a": "young and the elderly", + "5729fefbaf94a219006aa73b": "50 years of age", + "5729fefbaf94a219006aa73c": "obesity, alcoholism, and drug use", + "5729fefbaf94a219006aa73d": "malnutrition", + "5ad4d91d5b96ef001a10a380": "", + "5ad4d91d5b96ef001a10a381": "", + "5ad4d91d5b96ef001a10a382": "", + "5ad4d91d5b96ef001a10a383": "impaired cell-mediated immunity, complement activity, phagocyte function, IgA antibody concentrations, and cytokine production", + "5ad4d91d5b96ef001a10a384": "", + "5729ffda1d046914007796af": "vaccination", + "5729ffda1d046914007796b0": "immunization", + "5729ffda1d046914007796b1": "an antigen from a pathogen", + "5729ffda1d046914007796b2": "natural specificity", + "5ad4d8845b96ef001a10a344": "", + "5ad4d8845b96ef001a10a345": "", + "5ad4d8845b96ef001a10a346": "vaccination", + "5ad4d8845b96ef001a10a347": "", + "5ad4d8845b96ef001a10a348": "", + "572a019f3f37b31900478643": "enzymes that digest the barrier", + "572a019f3f37b31900478644": "type III secretion system", + "572a019f3f37b31900478645": "shut down host defenses", + "572a019f3f37b31900478646": "elude host immune responses", + "5ad4f4405b96ef001a10a77e": "", + "5ad4f4405b96ef001a10a77f": "", + "5ad4f4405b96ef001a10a780": "a type III secretion system, they may insert a hollow tube into the host cell", + "5ad4f4405b96ef001a10a781": "", + "5ad4f4405b96ef001a10a782": "type III secretion system", + "572a02483f37b3190047864b": "Frank Burnet", + "572a02483f37b3190047864c": "pathogens, an allograft", + "572a02483f37b3190047864d": "histocompatibility", + "572a02483f37b3190047864e": "Niels Jerne", + "5ad4f11d5b96ef001a10a702": "clonal selection theory", + "5ad4f11d5b96ef001a10a703": "Niels Jerne", + "5ad4f11d5b96ef001a10a704": "", + "5ad4f11d5b96ef001a10a705": "", + "5ad4f11d5b96ef001a10a706": "", + "572a03086aef0514001551a2": "Glucocorticoids", + "572a03086aef0514001551a3": "cytotoxic or immunosuppressive", + "572a03086aef0514001551a4": "methotrexate or azathioprine", + "572a03086aef0514001551a5": "cyclosporin", + "5ad4ef8b5b96ef001a10a6b8": "", + "5ad4ef8b5b96ef001a10a6b9": "", + "5ad4ef8b5b96ef001a10a6ba": "", + "5ad4ef8b5b96ef001a10a6bb": "", + "5ad4ef8b5b96ef001a10a6bc": "", + "572a04d51d046914007796cd": "cytotoxic natural killer cells and CTLs (cytotoxic T lymphocytes)", + "572a04d51d046914007796ce": "cortisol and catecholamines", + "572a04d51d046914007796cf": "melatonin", + "572a04d51d046914007796d0": "free radical", + "5ad4ec305b96ef001a10a668": "", + "5ad4ec305b96ef001a10a669": "to elicit an effective response against any intruding pathogens", + "5ad4ec305b96ef001a10a66a": "cortisol and catecholamines", + "5ad4ec305b96ef001a10a66b": "actively counteract free radical production", + "5ad4ec305b96ef001a10a66c": "", + "572a058aaf94a219006aa751": "vitamin D receptor", + "572a058aaf94a219006aa752": "calcitriol", + "572a058aaf94a219006aa753": "symbiotic", + "572a058aaf94a219006aa754": "CYP27B1", + "572a058aaf94a219006aa755": "dendritic cells, keratinocytes and macrophages", + "5ad4e7eb5b96ef001a10a5f4": "extends a vitamin D receptor", + "5ad4e7eb5b96ef001a10a5f5": "", + "5ad4e7eb5b96ef001a10a5f6": "", + "5ad4e7eb5b96ef001a10a5f7": "", + "5ad4e7eb5b96ef001a10a5f8": "CYP27B1", + "572a06af3f37b31900478667": "Pattern recognition receptors", + "572a06af3f37b31900478668": "defensins", + "572a06af3f37b31900478669": "phagocytic", + "572a06af3f37b3190047866a": "RNA interference pathway", + "5ad4df065b96ef001a10a4f4": "", + "5ad4df065b96ef001a10a4f5": "defensins", + "5ad4df065b96ef001a10a4f6": "", + "5ad4df065b96ef001a10a4f7": "", + "5ad4df065b96ef001a10a4f8": "", + "572a07fc6aef0514001551dc": "immunoglobulins and T cell receptors", + "572a07fc6aef0514001551dd": "lamprey and hagfish", + "572a07fc6aef0514001551de": "Variable lymphocyte receptors", + "572a07fc6aef0514001551df": "adaptive immune system", + "5ad4d5e15b96ef001a10a298": "", + "5ad4d5e15b96ef001a10a299": "", + "5ad4d5e15b96ef001a10a29a": "", + "5ad4d5e15b96ef001a10a29b": "", + "5ad4d5e15b96ef001a10a29c": "", + "572a096e6aef0514001551e4": "lymphocytes", + "572a096e6aef0514001551e5": "restriction modification system", + "572a096e6aef0514001551e6": "bacteriophages", + "572a096e6aef0514001551e7": "CRISPR sequences", + "5ad4de4c5b96ef001a10a4d8": "with the first vertebrates", + "5ad4de4c5b96ef001a10a4d9": "", + "5ad4de4c5b96ef001a10a4da": "", + "5ad4de4c5b96ef001a10a4db": "", + "5ad4de4c5b96ef001a10a4dc": "Offensive elements of the immune systems", + "572a0a686aef0514001551ec": "cellular\" and \"humoral\"", + "572a0a686aef0514001551ed": "Elie Metchnikoff", + "572a0a686aef0514001551ee": "phagocytes", + "572a0a686aef0514001551ef": "Robert Koch and Emil von Behring", + "572a0a686aef0514001551f0": "soluble components (molecules) found in the organism\u2019s \u201chumors", + "5ad4f0675b96ef001a10a6e8": "", + "5ad4f0675b96ef001a10a6e9": "Elie Metchnikoff, it was cells \u2013 more precisely, phagocytes", + "5ad4f0675b96ef001a10a6ea": "Robert Koch and Emil von Behring", + "5ad4f0675b96ef001a10a6eb": "active immune agents were soluble components", + "572a0b0b6aef0514001551f6": "cancers", + "572a0b0b6aef0514001551f7": "MHC class I molecules", + "572a0b0b6aef0514001551f8": "cytokine TGF-\u03b2", + "572a0b0b6aef0514001551f9": "", + "5ad4e56d5b96ef001a10a598": "", + "5ad4e56d5b96ef001a10a599": "", + "5ad4e56d5b96ef001a10a59a": "", + "5ad4e56d5b96ef001a10a59b": "", + "5ad4e56d5b96ef001a10a59c": "the immune system no longer attacks the tumor cells", + "572a0bf96aef051400155204": "Hypersensitivity", + "572a0bf96aef051400155205": "four", + "572a0bf96aef051400155206": "", + "572a0bf96aef051400155207": "", + "572a0bf96aef051400155208": "cytotoxic", + "5ad4dd325b96ef001a10a4a8": "", + "5ad4dd325b96ef001a10a4a9": "", + "5ad4dd325b96ef001a10a4aa": "", + "5ad4dd325b96ef001a10a4ab": "Type IV", + "5ad4dd325b96ef001a10a4ac": "", + "572a0ce11d046914007796fd": "intracellular pathogenesis", + "572a0ce11d046914007796fe": "Salmonella", + "572a0ce11d046914007796ff": "Plasmodium falciparum", + "572a0ce11d04691400779700": "Mycobacterium tuberculosis", + "572a0ce11d04691400779701": "protein A", + "5ad4f7895b96ef001a10a7f0": "evasion", + "5ad4f7895b96ef001a10a7f1": "", + "5ad4f7895b96ef001a10a7f2": "inside host cells", + "5ad4f7895b96ef001a10a7f3": "", + "5ad4f7895b96ef001a10a7f4": "", + "572a0e4b6aef051400155214": "antigenic variation", + "572a0e4b6aef051400155215": "HIV", + "572a0e4b6aef051400155216": "Trypanosoma brucei", + "572a0e4b6aef051400155217": "antigens", + "5ad4f8255b96ef001a10a80e": "", + "5ad4f8255b96ef001a10a80f": "rapidly change non-essential epitopes (amino acids and/or sugars) on the surface of the pathogen", + "5ad4f8255b96ef001a10a810": "", + "5ad4f8255b96ef001a10a811": "", + "5ad4f8255b96ef001a10a812": "", + "572a0f073f37b3190047867f": "immune surveillance", + "572a0f073f37b31900478680": "papillomavirus", + "572a0f073f37b31900478681": "tyrosinase", + "572a0f073f37b31900478682": "melanomas", + "572a0f073f37b31900478683": "melanomas", + "5ad4e4425b96ef001a10a572": "", + "5ad4e4425b96ef001a10a573": "", + "5ad4e4425b96ef001a10a574": "", + "5ad4e4425b96ef001a10a575": "", + "5ad4e4425b96ef001a10a576": "", + "572a10cd6aef051400155222": ">500 Da", + "572a10cd6aef051400155223": "hydrophilic", + "572a10cd6aef051400155224": "Immunoproteomics", + "572a10cd6aef051400155225": "B cells", + "572a10cd6aef051400155226": "immunoinformatics", + "5ad4f3a25b96ef001a10a758": "", + "5ad4f3a25b96ef001a10a759": "", + "5ad4f3a25b96ef001a10a75a": "", + "5ad4f3a25b96ef001a10a75b": "", + "5ad4f3a25b96ef001a10a75c": "", + "572a12386aef051400155234": "leptin, pituitary growth hormone, and prolactin", + "572a12386aef051400155235": "APCs", + "572a12386aef051400155236": "Th1/Th2", + "572a12386aef051400155237": "Th1", + "5ad4eb355b96ef001a10a64c": "", + "5ad4eb355b96ef001a10a64d": "blood levels", + "5ad4eb355b96ef001a10a64e": "", + "5ad4eb355b96ef001a10a64f": "leptin, pituitary growth hormone, and prolactin", + "5ad4eb355b96ef001a10a650": "", + "572a135daf94a219006aa79f": "rudimentary immune system, in the form of enzymes that protect against bacteriophage", + "572a135daf94a219006aa7a0": "defensins", + "572a135daf94a219006aa7a1": "vaccination", + "572a135daf94a219006aa7a2": "", + "5ad49d30ba00c4001a268dd4": "", + "5ad49d30ba00c4001a268dd5": "", + "5ad49d30ba00c4001a268dd6": "", + "5ad49d30ba00c4001a268dd7": "", + "5ad49d30ba00c4001a268dd8": "", + "572a142e3f37b319004786b9": "carbohydrates", + "572a142e3f37b319004786ba": "signal amplification", + "572a142e3f37b319004786bb": "catalytic", + "572a142e3f37b319004786bc": "", + "5ad4c6775b96ef001a10a010": "", + "5ad4c6775b96ef001a10a011": "", + "5ad4c6775b96ef001a10a012": "", + "5ad4c6775b96ef001a10a013": "", + "5ad4c6775b96ef001a10a014": "", + "57293b843f37b31900478133": "Intergovernmental Panel on Climate Change", + "57293b843f37b31900478134": "the World Meteorological Organization (WMO) and the United Nations Environment Programme (UNEP)", + "57293b843f37b31900478135": "greenhouse gas concentrations in the atmosphere", + "57293b843f37b31900478136": "United Nations Framework Convention on Climate Change", + "57293b843f37b31900478137": "Resolution 43/53", + "5a3e2a95378766001a0024af": "", + "5a3e2a95378766001a0024b0": "the United Nations", + "5a3e2a95378766001a0024b1": "", + "5a3e2a95378766001a0024b2": "", + "5a3e2a95378766001a0024b3": "", + "57293bc91d0469140077919b": "Hoesung Lee", + "57293bc91d0469140077919c": "Korean", + "57293bc91d0469140077919d": "Ismail El Gizouli", + "57293bc91d0469140077919e": "Hoesung Lee", + "57293bc91d0469140077919f": "February 2015", + "5a3e2ba4378766001a0024b9": "", + "5a3e2ba4378766001a0024ba": "", + "5a3e2ba4378766001a0024bb": "", + "5a3e2ba4378766001a0024bc": "", + "5a3e2ba4378766001a0024bd": "", + "57293c246aef051400154bb8": "representatives appointed by governments and organizations", + "57293c246aef051400154bb9": "322", + "57293c246aef051400154bba": "", + "57293c246aef051400154bbb": "", + "5a3e2dc0378766001a0024c3": "IPCC and IPCC Working groups", + "5a3e2dc0378766001a0024c4": "", + "5a3e2dc0378766001a0024c5": "", + "5a3e2dc0378766001a0024c6": "", + "5a3e2dc0378766001a0024c7": "", + "57293ca73f37b3190047815b": "1989", + "57293ca73f37b3190047815c": "United Nations Environment Programme (UNEP) and the World Meteorological Organization (WMO)", + "57293ca73f37b3190047815d": "", + "57293ca73f37b3190047815e": "", + "57293ca73f37b3190047815f": "", + "5a3e2f07378766001a0024cd": "IPCC Trust Fund", + "5a3e2f07378766001a0024ce": "", + "5a3e2f07378766001a0024cf": "", + "5a3e2f07378766001a0024d0": "the WMO, by UNEP, and by IPCC Members", + "5a3e2f07378766001a0024d1": "", + "57293d116aef051400154bc8": "carry out research", + "57293d116aef051400154bc9": "published sources", + "57293d116aef051400154bca": "non-peer-reviewed sources", + "57293d116aef051400154bcb": "model results, reports from government agencies and non-governmental organizations, and industry journals", + "5a3e307f378766001a0024d7": "The IPCC", + "5a3e307f378766001a0024d8": "", + "5a3e307f378766001a0024d9": "", + "5a3e307f378766001a0024da": "", + "5a3e307f378766001a0024db": "", + "57293d6d1d046914007791b7": "two", + "57293d6d1d046914007791b8": "ten to fifteen", + "57293d6d1d046914007791b9": "", + "57293d6d1d046914007791ba": "coordinating lead authors", + "57293d6d1d046914007791bb": "Working Group chairs", + "5a3e488b378766001a00253b": "", + "5a3e488b378766001a00253c": "two", + "5a3e488b378766001a00253d": "", + "5a3e488b378766001a00253e": "authors", + "5a3e488b378766001a00253f": "", + "57293e221d046914007791d5": "substantially increasing the atmospheric concentrations", + "57293e221d046914007791d6": "warming of the Earth's surface", + "57293e221d046914007791d7": "", + "57293e221d046914007791d8": "", + "57293e221d046914007791d9": "", + "5a3e3405378766001a0024e1": "", + "5a3e3405378766001a0024e2": "0.3 \u00b0C per decade", + "5a3e3405378766001a0024e3": "", + "5a3e3405378766001a0024e4": "global mean surface air temperature", + "5a3e3405378766001a0024e5": "a decade or more", + "57293e983f37b3190047818b": "2001", + "57293e983f37b3190047818c": "16", + "57293e983f37b3190047818d": "Science", + "57293e983f37b3190047818e": "at least 90%", + "57293e983f37b3190047818f": "between 1.4 and 5.8 \u00b0C above 1990 levels", + "5a3e3614378766001a0024eb": "", + "5a3e3614378766001a0024ec": "", + "5a3e3614378766001a0024ed": "Science", + "5a3e3614378766001a0024ee": "", + "5a3e3614378766001a0024ef": "", + "57293f353f37b3190047819b": "Richard Lindzen", + "57293f353f37b3190047819c": "", + "57293f353f37b3190047819d": "John Houghton", + "57293f353f37b3190047819e": "co-chair of TAR WGI", + "57293f353f37b3190047819f": "scientific evidence", + "5a3e3752378766001a0024f5": "", + "5a3e3752378766001a0024f6": "", + "5a3e3752378766001a0024f7": "", + "5a3e3752378766001a0024f8": "", + "5a3e3752378766001a0024f9": "SPM", + "57293f8a6aef051400154bde": "", + "57293f8a6aef051400154bdf": "2011", + "57293f8a6aef051400154be0": "2011", + "57293f8a6aef051400154be1": "", + "5a3e3907378766001a0024ff": "", + "5a3e3907378766001a002500": "", + "5a3e3907378766001a002501": "", + "5a3e3907378766001a002502": "", + "5a3e3907378766001a002503": "", + "572940246aef051400154bec": "Data Distribution Centre and the National Greenhouse Gas Inventories Programme", + "572940246aef051400154bed": "default emission factors", + "572940246aef051400154bee": "fuel consumption, industrial production and so on", + "572940246aef051400154bef": "WMO Executive Council and UNEP Governing Council", + "5a3e3aa9378766001a002509": "", + "5a3e3aa9378766001a00250a": "", + "5a3e3aa9378766001a00250b": "", + "5a3e3aa9378766001a00250c": "UNFCCC", + "5a3e3aa9378766001a00250d": "", + "572940973f37b319004781a5": "the date", + "572940973f37b319004781a6": "the poor application of well-established IPCC procedures", + "572940973f37b319004781a7": "WWF report", + "572940973f37b319004781a8": "2035", + "5a3e495c378766001a002545": "", + "5a3e495c378766001a002547": "", + "5a3e495c378766001a002548": "", + "5a3e495c378766001a002549": "\"Variations of Snow and Ice in the past and at present on a Global and Regional Scale\"", + "572941273f37b319004781ad": "Former IPCC chairman", + "572941273f37b319004781ae": "making it seem like climate change is more serious", + "572941273f37b319004781af": "co-chair of the IPCC working group II", + "572941273f37b319004781b0": "Himalayan glaciers", + "572941273f37b319004781b1": "\"generally unfounded and also marginal to the assessment", + "5a3e3de4378766001a002513": "Robert Watson", + "5a3e3de4378766001a002514": "The IPCC", + "5a3e3de4378766001a002515": "", + "5a3e3de4378766001a002516": "", + "5a3e3de4378766001a002517": "", + "57294209af94a219006aa201": "1999", + "57294209af94a219006aa202": "Michael E. Mann, Raymond S. Bradley and Malcolm K. Hughes", + "57294209af94a219006aa203": "hockey stick graph", + "57294209af94a219006aa204": "", + "5a3e40d1378766001a00251d": "", + "5a3e40d1378766001a00251e": "1999", + "5a3e40d1378766001a00251f": "", + "5a3e40d1378766001a002520": "", + "5a3e40d1378766001a002521": "", + "57294279af94a219006aa209": "1000 and 1900", + "57294279af94a219006aa20a": "Fred Singer", + "57294279af94a219006aa20b": "Capitol Hill, Washington, D.C.", + "57294279af94a219006aa20c": "18 July 2000", + "57294279af94a219006aa20d": "Committee on Commerce, Science and Transportation", + "5a3e42de378766001a002527": "between 1000 and 1900", + "5a3e42de378766001a002528": "", + "5a3e42de378766001a002529": "", + "5a3e42de378766001a00252a": "", + "5a3e42de378766001a00252b": "", + "572943ab1d04691400779219": "Rep. Joe Barton", + "572943ab1d0469140077921a": "Ed Whitfield", + "572943ab1d0469140077921b": "23 June 2005", + "572943ab1d0469140077921c": "Sherwood Boehlert", + "572943ab1d0469140077921d": "Sherwood Boehlert", + "5a3e44ea378766001a002531": "Ed Whitfield", + "5a3e44ea378766001a002532": "", + "5a3e44ea378766001a002533": "", + "5a3e44ea378766001a002534": "", + "5a3e44ea378766001a002535": "", + "572944e03f37b319004781e1": "2007", + "572944e03f37b319004781e2": "", + "572944e03f37b319004781e3": "Ten of these 14", + "572944e03f37b319004781e4": "Ten", + "572944e03f37b319004781e5": "divergence", + "5a3e582e378766001a00259f": "", + "5a3e582e378766001a0025a0": "", + "5a3e582e378766001a0025a1": "", + "5a3e582e378766001a0025a2": "", + "5a3e582e378766001a0025a3": "", + "572945b11d0469140077922f": "", + "572945b11d04691400779230": "", + "572945b11d04691400779231": "", + "572945b11d04691400779232": "", + "5a3e5697378766001a002595": "", + "5a3e5697378766001a002596": "", + "5a3e5697378766001a002597": "", + "5a3e5697378766001a002598": "", + "5a3e5697378766001a002599": "", + "572949306aef051400154c68": "projected rises in sea levels", + "572949306aef051400154c69": "0.5\u20131.4 m", + "572949306aef051400154c6a": "0.5\u20131.4 m [50\u2013140 cm]", + "572949306aef051400154c6b": "2001", + "5a3e4a34378766001a00254f": "", + "5a3e4a34378766001a002550": "", + "5a3e4a34378766001a002551": "", + "5a3e4a34378766001a002552": "a study on projected rises in sea levels", + "5a3e4a34378766001a002553": "", + "57294baaaf94a219006aa26b": "coordinating lead author", + "57294baaaf94a219006aa26c": "Science Magazine", + "57294baaaf94a219006aa26d": "IPCC consensus approach", + "5a3e4c01378766001a002559": "", + "5a3e4c01378766001a00255a": "", + "5a3e4c01378766001a00255b": "", + "5a3e4c01378766001a00255c": "", + "5a3e4c01378766001a00255d": "", + "57294e6b1d04691400779275": "", + "57294e6b1d04691400779276": "", + "57294e6b1d04691400779277": "", + "5a3e4e57378766001a002563": "", + "5a3e4e57378766001a002564": "", + 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"remove government oversight from its processes", + "5a3e539a378766001a00258b": "", + "5a3e539a378766001a00258c": "", + "5a3e539a378766001a00258d": "", + "5a3e539a378766001a00258e": "", + "5a3e539a378766001a00258f": "", + "57296d571d04691400779413": "", + "57296d571d04691400779414": "", + "57296d571d04691400779415": "The fundamental theorem of arithmetic", + "57296d571d04691400779416": "primes", + "57296d571d04691400779417": "one can include arbitrarily many instances of 1 in any factorization", + "5a89117e19b91f001a626f2d": "", + "5a89117e19b91f001a626f2e": "", + "5a89117e19b91f001a626f2f": "", + "5a89117e19b91f001a626f30": "", + "5a89117e19b91f001a626f31": "one can include arbitrarily many instances of 1 in any factorization", + "57296f293f37b319004783a3": "primality", + "57296f293f37b319004783a4": "trial division", + "57296f293f37b319004783a5": "Miller\u2013Rabin primality test", + "57296f293f37b319004783a6": "Miller\u2013Rabin primality test", + "57296f293f37b319004783a7": "22,338,618", + "5a89128d3b2508001a72a494": "", + "5a89128d3b2508001a72a495": "trial division", + "5a89128d3b2508001a72a496": "trial division", + "5a89128d3b2508001a72a497": "trial division", + "5a89128d3b2508001a72a498": "22,338,618 decimal digits", + "572970c11d04691400779463": "infinitely many primes", + "572970c11d04691400779464": "", + "572970c11d04691400779465": "statistical", + "572970c11d04691400779466": "prime number theorem", + "572970c11d04691400779467": "end of the 19th century", + "5a8913713b2508001a72a49e": "", + "5a8913713b2508001a72a49f": "", + "5a8913713b2508001a72a4a0": "", + "5a8913713b2508001a72a4a1": "", + "5a8913713b2508001a72a4a2": "", + "5729727baf94a219006aa437": "Goldbach's conjecture", + "5729727baf94a219006aa438": "", + "5729727baf94a219006aa439": "algebraic", + "5729727baf94a219006aa43a": "public-key cryptography", + "5729727baf94a219006aa43b": "", + "5a89150d3b2508001a72a4a8": "", + "5a89150d3b2508001a72a4a9": "", + "5a89150d3b2508001a72a4aa": "", + "5a89150d3b2508001a72a4ab": "", + "5a89150d3b2508001a72a4ac": "", + "572973f76aef051400154f0a": "", + "572973f76aef051400154f0b": "", + "572973f76aef051400154f0c": "", + "572973f76aef051400154f0d": "9", + "572973f76aef051400154f0e": "", + "5a8917433b2508001a72a4b2": "", + "5a8917433b2508001a72a4b3": "", + "5a8917433b2508001a72a4b4": "", + "5a8917433b2508001a72a4b5": "9", + "5a8917433b2508001a72a4b6": "", + "57297547af94a219006aa45b": "1", + "57297547af94a219006aa45c": "Christian Goldbach", + "57297547af94a219006aa45d": "", + "57297547af94a219006aa45e": "10,006,721", + "57297547af94a219006aa45f": "", + "5a8919843b2508001a72a4bc": "1 prime", + "5a8919843b2508001a72a4bd": "", + "5a8919843b2508001a72a4be": "", + "5a8919843b2508001a72a4bf": "10,006,721", + "5a8919843b2508001a72a4c0": "", + "57297781af94a219006aa4a3": "", + "57297781af94a219006aa4a4": "", + "57297781af94a219006aa4a5": "sum of divisors function", + "57297781af94a219006aa4a6": "sum of divisors function", + "57297781af94a219006aa4a7": "eliminate all multiples of 1", + "5a8923a23b2508001a72a4c6": "", + "5a8923a23b2508001a72a4c7": "", + "5a8923a23b2508001a72a4c8": "sum of divisors function", + "5a8923a23b2508001a72a4c9": "", + "5a8923a23b2508001a72a4ca": "", + "572978f91d046914007794d3": "Rhind papyrus", + "572978f91d046914007794d4": "Ancient Greeks", + "572978f91d046914007794d5": "Euclid's Elements", + "572978f91d046914007794d6": "Euclid", + "572978f91d046914007794d7": "a simple method to compute primes", + "5a8925e53b2508001a72a4d0": "", + "5a8925e53b2508001a72a4d1": "", + "5a8925e53b2508001a72a4d2": "", + "5a8925e53b2508001a72a4d3": "", + "5a8925e53b2508001a72a4d4": "", + "57297a276aef051400154f88": "1640", + "57297a276aef051400154f89": "Euler", + "57297a276aef051400154f8a": "22n + 1", + "57297a276aef051400154f8b": "up to n = 4", + "57297a276aef051400154f8c": "2p \u2212 1", + "5a8929e43b2508001a72a4da": "1640", + "5a8929e43b2508001a72a4db": "", + "5a8929e43b2508001a72a4dc": "", + "5a8929e43b2508001a72a4dd": "up to n = 4", + "5a8929e43b2508001a72a4de": "", + "57297bc9af94a219006aa4c7": "trial division", + "57297bc9af94a219006aa4c8": "if a complete list of primes up to is known", + "57297bc9af94a219006aa4c9": "1", + "57297bc9af94a219006aa4ca": "the square root of n", + "57297bc9af94a219006aa4cb": "three", + "5a892b473b2508001a72a4e4": "trial division", + "5a892b473b2508001a72a4e5": "if a complete list of primes up to is known", + "5a892b473b2508001a72a4e6": "", + "5a892b473b2508001a72a4e7": "", + "5a892b473b2508001a72a4e8": "three", + "57297d421d046914007794e5": "two", + "57297d421d046914007794e6": "", + "57297d421d046914007794e7": "deterministic algorithms", + "57297d421d046914007794e8": "deterministic", + "57297d421d046914007794e9": "1/(1-p)n", + "5a892d303b2508001a72a4ee": "two", + "5a892d303b2508001a72a4ef": "", + "5a892d303b2508001a72a4f0": "", + "5a892d303b2508001a72a4f1": "", + "5a892d303b2508001a72a4f2": "1/(1-p)n", + "57297ed93f37b3190047845f": "Fermat primality test", + "57297ed93f37b31900478460": "the fact (Fermat's little theorem) that np\u2261n (mod p) for any n if p is a prime number", + "57297ed93f37b31900478461": "composite numbers", + "57297ed93f37b31900478462": "Baillie-PSW, Miller-Rabin, and Solovay-Strassen tests", + "57297ed93f37b31900478463": "Baillie-PSW, Miller-Rabin, and Solovay-Strassen tests", + "5a892e8e3b2508001a72a4f8": "", + "5a892e8e3b2508001a72a4f9": "", + "5a892e8e3b2508001a72a4fa": "composite numbers", + "5a892e8e3b2508001a72a4fb": "", + "5a892e8e3b2508001a72a4fc": "", + "572980f9af94a219006aa4d1": "2p + 1 with p prime", + "572980f9af94a219006aa4d2": "form 2p \u2212 1", + "572980f9af94a219006aa4d3": "Lucas\u2013Lehmer test", + "572980f9af94a219006aa4d4": "Sophie Germain primes", + "572980f9af94a219006aa4d5": "Sophie Germain primes", + "5a8930573b2508001a72a502": "", + "5a8930573b2508001a72a503": "", + "5a8930573b2508001a72a504": "Lucas\u2013Lehmer test", + "5a8930573b2508001a72a505": "Sophie Germain primes", + "5a8930573b2508001a72a506": "Sophie Germain primes", + "572982e66aef051400154f92": "distributed", + "572982e66aef051400154f93": "2009", + "572982e66aef051400154f94": "US$100,000", + "572982e66aef051400154f95": "The Electronic Frontier Foundation", + "572982e76aef051400154f96": "", + "5a89320b3b2508001a72a50c": "distributed", + "5a89320b3b2508001a72a50d": "", + "5a89320b3b2508001a72a50e": "", + "5a89320b3b2508001a72a50f": "The Electronic Frontier Foundation", + "5a89320b3b2508001a72a510": "", + "572985011d04691400779501": "floor function", + "572985011d04691400779502": "Chebyshev", + "572985011d04691400779503": "n > 3", + "572985011d04691400779504": "there always exists at least one prime number p with n < p < 2n \u2212 2", + "572985011d04691400779505": "Wilson's theorem", + "5a8933ed3b2508001a72a516": "", + "5a8933ed3b2508001a72a517": "Chebyshev", + "5a8933ed3b2508001a72a518": "", + "5a8933ed3b2508001a72a519": "", + "5a8933ed3b2508001a72a51a": "Wilson's theorem", + "572987e46aef051400154fa2": "their greatest common divisor", + "572987e46aef051400154fa3": "", + "572987e46aef051400154fa4": "1/6", + "572987e46aef051400154fa5": "at most one", + "572987e46aef051400154fa6": "infinitely many prime numbers", + "5a89357c3b2508001a72a520": "their greatest common divisor", + "5a89357c3b2508001a72a521": "", + "5a89357c3b2508001a72a522": "", + "5a89357c3b2508001a72a523": "", + "5a89357c3b2508001a72a524": "", + "572989846aef051400154fc0": "zeta function", + "572989846aef051400154fc1": "\u03b6(1) would have a finite value", + "572989846aef051400154fc2": "", + "572989846aef051400154fc3": "exceeds any given number", + "572989846aef051400154fc4": "identity", + "5a8937553b2508001a72a52a": "", + "5a8937553b2508001a72a52b": "", + "5a8937553b2508001a72a52c": "", + "5a8937553b2508001a72a52d": "", + "5a8937553b2508001a72a52e": "", + "57298ef11d0469140077952d": "1859", + "57298ef11d0469140077952e": "s = \u22122, \u22124", + "57298ef11d0469140077952f": "", + "57298ef11d04691400779530": "asymptotic", + "57298ef11d04691400779531": "asymptotic", + "5a89392f3b2508001a72a534": "", + "5a89392f3b2508001a72a535": "s = \u22122, \u22124", + "5a89392f3b2508001a72a536": "", + "5a89392f3b2508001a72a537": "asymptotic distribution of primes", + "5a89392f3b2508001a72a538": "asymptotic", + "57299021af94a219006aa50b": "", + "57299021af94a219006aa50c": "Goldbach's conjecture", + "57299021af94a219006aa50d": "n = 2 \u00b7 1017", + "57299021af94a219006aa50e": "Vinogradov's theorem", + "57299021af94a219006aa50f": "Chen's theorem", + "5a893a003b2508001a72a53e": "", + "5a893a003b2508001a72a53f": "Goldbach's conjecture", + "5a893a003b2508001a72a540": "", + "5a893a003b2508001a72a541": "Vinogradov's theorem", + "5a893a003b2508001a72a542": "", + "572991943f37b319004784a1": "", + "572991943f37b319004784a2": "pairs of primes with difference 2", + "572991943f37b319004784a3": "", + "572991943f37b319004784a4": "n2 + 1", + "572991943f37b319004784a5": "", + "5a893bd73b2508001a72a548": "", + "5a893bd73b2508001a72a549": "", + "5a893bd73b2508001a72a54a": "", + "5a893bd73b2508001a72a54b": "", + "5a893bd73b2508001a72a54c": "", + "57299326af94a219006aa515": "number theory", + "57299326af94a219006aa516": "G. H. Hardy", + "57299326af94a219006aa517": "1970s", + "57299326af94a219006aa518": "hash tables and pseudorandom number generators", + "57299326af94a219006aa519": "pseudorandom", + "5a893ce63b2508001a72a552": "", + "5a893ce63b2508001a72a553": "G. H. Hardy", + "5a893ce63b2508001a72a554": "", + "5a893ce63b2508001a72a555": "", + "5a893ce63b2508001a72a556": "", + "572995d46aef051400154fe8": "recurring", + "572995d46aef051400154fe9": "p \u2212 1 or a divisor of p \u2212 1", + "572995d46aef051400154fea": "! + 1", + "572995d46aef051400154feb": "", + "572995d46aef051400154fec": "", + "5a8940ba3b2508001a72a55c": "recurring", + "5a8940ba3b2508001a72a55d": "p \u2212 1 or a divisor of p \u2212 1", + "5a8940ba3b2508001a72a55e": "", + "5a8940ba3b2508001a72a55f": "", + "5a8940ba3b2508001a72a560": "", + "572996c73f37b319004784b3": "RSA and the Diffie\u2013Hellman key exchange", + "572996c73f37b319004784b4": "Diffie\u2013Hellman key exchange", + "572996c73f37b319004784b5": "512", + "572996c73f37b319004784b6": "modular", + "572996c73f37b319004784b7": "1024", + "5a8942233b2508001a72a566": "", + "5a8942233b2508001a72a567": "", + "5a8942233b2508001a72a568": "", + "5a8942233b2508001a72a569": "", + "5a8942233b2508001a72a56a": "", + "572998673f37b319004784d5": "cicadas", + "572998673f37b319004784d6": "grubs underground", + "572998673f37b319004784d7": "17 years", + "572998673f37b319004784d8": "the prime number intervals between emergences", + "572998673f37b319004784d9": "2% higher", + "5a8943753b2508001a72a570": "cicadas", + "5a8943753b2508001a72a571": "grubs underground", + "5a8943753b2508001a72a572": "17 years", + "5a8943753b2508001a72a573": "the prime number intervals between emergences", + "5a8943753b2508001a72a574": "2%", + "57299a6f6aef051400155016": "minimality or indecomposability", + "57299a6f6aef051400155017": "smallest subfield", + "57299a6f6aef051400155018": "it cannot be written as the knot sum of two nontrivial knots", + "57299a6f6aef051400155019": "as a connected sum of prime knots", + "57299a6f6aef05140015501a": "any object can be, essentially uniquely, decomposed into its prime components", + "5a8944653b2508001a72a57a": "", + "5a8944653b2508001a72a57b": "smallest subfield of a field F containing both 0 and 1. 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"5729a26d6aef05140015505b": "the completed (or local) fields", + "5729a26d6aef05140015505c": "the absolute value", + "5729a26d6aef05140015505d": "local-global principle", + "5a894a483b2508001a72a5ac": "", + "5a894a483b2508001a72a5ad": "", + "5a894a483b2508001a72a5ae": "", + "5a894a483b2508001a72a5af": "", + "5a894a483b2508001a72a5b0": "", + "5729a3716aef05140015506a": "Olivier Messiaen", + "5729a3716aef05140015506b": "La Nativit\u00e9 du Seigneur (1935) and Quatre \u00e9tudes de rythme", + "5729a3716aef05140015506c": "La Nativit\u00e9 du Seigneur (1935) and Quatre \u00e9tudes de rythme", + "5729a3716aef05140015506d": "third", + "5729a3716aef05140015506e": "the movements of nature, movements of free and unequal durations", + "5a894b333b2508001a72a5b6": "Olivier Messiaen", + "5a894b333b2508001a72a5b7": "", + "5a894b333b2508001a72a5b8": "", + "5a894b333b2508001a72a5b9": "", + "5a894b333b2508001a72a5ba": "", + "572f5533a23a5019007fc55c": "", + "572f5533a23a5019007fc55d": "Cologne", + "572f5533a23a5019007fc55e": "", + "572f5533a23a5019007fc55f": "1,230 km (760 mi)", + "572fe1d404bcaa1900d76e37": "Swiss canton of Graub\u00fcnden", + "572fe1d404bcaa1900d76e3a": "", + "572fe1d404bcaa1900d76e3b": "1,230 km (760 mi)", + "5ad25e17d7d075001a428f12": "", + "5ad25e17d7d075001a428f13": "", + "5ad25e17d7d075001a428f14": "", + "5ad25e17d7d075001a428f15": "", + "5ad25e17d7d075001a428f16": "", + "572f55e8a23a5019007fc56b": "Gaulish name R\u0113nos", + "572f55e8a23a5019007fc56c": "", + "572f55e8a23a5019007fc56d": "", + "572f55e8a23a5019007fc56e": "1st century BC", + "572fe288a23a5019007fcad7": "R\u0113nos", + "572fe288a23a5019007fcad8": "", + "572fe288a23a5019007fcad9": "*R\u012bnaz", + "572fe288a23a5019007fcada": "Rijn", + "572fe288a23a5019007fcadb": "Rhijn", + "5ad262fbd7d075001a4290dc": "", + "5ad262fbd7d075001a4290dd": "", + "5ad262fbd7d075001a4290de": "", + "5ad262fbd7d075001a4290df": "", + "572f567cb2c2fd140056803f": "Rhine-kilometers\"", + "572f567cb2c2fd1400568040": "1939", + "572f567cb2c2fd1400568041": "Old Rhine Bridge at Constance", + "572f567cb2c2fd1400568042": "Hoek van Holland", + "572f567cb2c2fd1400568043": "canalisation projects", + "572fe393947a6a140053cdba": "Rhine-kilometers", + "572fe393947a6a140053cdbb": "1939", + "572fe393947a6a140053cdbc": "Old Rhine Bridge at Constance", + "572fe393947a6a140053cdbd": "Hoek van Holland", + "572fe393947a6a140053cdbe": "due to number of canalisation projects completed in the 19th and 20th century", + "5ad2649ad7d075001a429160": "0 km)", + "5ad2649ad7d075001a429161": "", + "5ad2649ad7d075001a429162": "", + "5ad2649ad7d075001a429163": "", + "5ad2649ad7d075001a429164": "", + "572f5703a23a5019007fc573": "north", + "572f5703a23a5019007fc574": "86 km long", + "572f5703a23a5019007fc575": "the Rhine Valley", + "572f5703a23a5019007fc576": "Sargans", + "572f5703a23a5019007fc577": "Liechtenstein", + "572fe41e04bcaa1900d76e4b": "near Chur", + "572fe41e04bcaa1900d76e4c": "86 km", + "572fe41e04bcaa1900d76e4d": "599 m to 396 m", + "572fe41e04bcaa1900d76e4e": "the Rhine Valley", + "572fe41e04bcaa1900d76e4f": "Liechtenstein", + "5ad2660dd7d075001a4291d8": "", + "5ad2660dd7d075001a4291d9": "599 m to 396 m", + "5ad2660dd7d075001a4291da": "Sargans", + "5ad2660dd7d075001a4291db": "", + "5ad2660dd7d075001a4291dc": "599 m to 396 m", + "572f57c704bcaa1900d7686d": "Lake Constance", + "572f57c704bcaa1900d7686e": "the Alter Rhein", + "572f57c704bcaa1900d7686f": "a modern canalized section", + "572f57c704bcaa1900d76870": "Isel", + "572f57c704bcaa1900d76871": "", + "572fe4a304bcaa1900d76e55": "Lake Constance", + "572fe4a304bcaa1900d76e56": "a modern canalized section", + "572fe4a304bcaa1900d76e57": "Alter Rhein", + "572fe4a304bcaa1900d76e58": "", + "572fe4a304bcaa1900d76e59": "", + "5ad268a9d7d075001a42927e": "The mouth of the Rhine", + "5ad268a9d7d075001a42927f": "", + "5ad268a9d7d075001a429280": "", + "5ad268a9d7d075001a429281": "", + "5ad268a9d7d075001a429282": "", + "572f5875947a6a140053c89a": "near Diepoldsau", + "572f5875947a6a140053c89b": "Fu\u00dfach", + "572f5875947a6a140053c89c": "strong sedimentation", + "572f5875947a6a140053c89d": "parallel to the canalized Rhine into the lake", + "572f5875947a6a140053c89e": "", + "572fe53104bcaa1900d76e69": "Fu\u00dfach", + "572fe53104bcaa1900d76e6a": "near Diepoldsau", + "572fe53104bcaa1900d76e6b": "to counteract the constant flooding and strong sedimentation in the western Rhine Delta", + "572fe53104bcaa1900d76e6c": "The Dornbirner Ach", + "572fe53104bcaa1900d76e6d": "continuous input of sediment", + "5ad26aa8d7d075001a429320": "", + "5ad26aa8d7d075001a429321": "", + "5ad26aa8d7d075001a429322": "", + "5ad26aa8d7d075001a429323": "", + "5ad26aa8d7d075001a429324": "", + "572f58d9a23a5019007fc57d": "three", + "572f58d9a23a5019007fc57e": "Seerhein", + "572f58d9a23a5019007fc57f": "upper lake", + "572f58d9a23a5019007fc580": "lower lake", + "572f58d9a23a5019007fc581": "Swiss-Austrian border", + "572fe60fb2c2fd140056858b": "three", + "572fe60fb2c2fd140056858c": "Austria", + "572fe60fb2c2fd140056858d": "the Alps", + "572fe60fb2c2fd140056858e": "near the Alps", + "572fe60fb2c2fd140056858f": "", + "5ad26d27d7d075001a4293c0": "three", + "5ad26d27d7d075001a4293c1": "", + "5ad26d27d7d075001a4293c2": "", + "5ad26d27d7d075001a4293c3": "", + "5ad26d27d7d075001a4293c4": "three", + "572f59b4a23a5019007fc587": "greater density of cold water", + "572f59b4a23a5019007fc588": "", + "572f59b4a23a5019007fc589": "Lindau", + "572f59b4a23a5019007fc58a": "Lake \u00dcberlingen", + "572f59b4a23a5019007fc58b": "", + "572fe92204bcaa1900d76e95": "", + "572fe92204bcaa1900d76e96": "", + "572fe92204bcaa1900d76e97": "Lake \u00dcberlingen", + "572fe92204bcaa1900d76e98": "Rhine Gutter", + "572fe92204bcaa1900d76e99": "the water level", + "5ad26fafd7d075001a42942c": "", + "5ad26fafd7d075001a42942d": "", + "5ad26fafd7d075001a42942e": "Rhine water", + "5ad26fafd7d075001a42942f": "", + "5ad26fafd7d075001a429430": "", + "572f609ca23a5019007fc5af": "westward", + "572f609ca23a5019007fc5b0": "river Aare", + "572f609ca23a5019007fc5b1": "more than doubles", + "572f609ca23a5019007fc5b2": "Finsteraarhorn", + "572f609ca23a5019007fc5b3": "Basel", + "572fe9b3947a6a140053cde0": "generally westward", + "572fe9b3947a6a140053cde1": "river Aare", + "572fe9b3947a6a140053cde2": "more than doubles", + "572fe9b3947a6a140053cde3": "Finsteraarhorn", + "572fe9b3947a6a140053cde4": "German-Swiss", + "5ad2741ed7d075001a4294d4": "river Aare", + "5ad2741ed7d075001a4294d5": "", + "5ad2741ed7d075001a4294d6": "", + "5ad2741ed7d075001a4294d7": "", + "5ad2741ed7d075001a4294d8": "", + "572f60f4947a6a140053c8ea": "Basel", + "572f60f4947a6a140053c8eb": "Rhine knee", + "572f60f4947a6a140053c8ec": "the Central Bridge", + "572f60f4947a6a140053c8ed": "300 km long", + "572f60f4947a6a140053c8ee": "40 km", + "572fec30947a6a140053cdf2": "", + "572fec30947a6a140053cdf3": "Rhine knee", + "572fec30947a6a140053cdf4": "North", + "572fec30947a6a140053cdf5": "the High Rhine", + "572fec30947a6a140053cdf6": "the Central Bridge", + "5ad275c8d7d075001a429504": "", + "5ad275c8d7d075001a429505": "", + "5ad275c8d7d075001a429506": "", + "5ad275c8d7d075001a429507": "", + "5ad275c8d7d075001a429508": "", + "572f64ccb2c2fd14005680b7": "19th", + "572f64ccb2c2fd14005680b8": "increased", + "572f64ccb2c2fd14005680b9": "the ground water level fell significantly", + "572f64ccb2c2fd14005680ba": "Grand Canal d'Alsace", + "572f64ccb2c2fd14005680bb": "large compensation pools", + "572feddda23a5019007fcb5b": "The Upper Rhine region", + "572feddda23a5019007fcb5c": "", + "572feddda23a5019007fcb5d": "increased", + "572feddda23a5019007fcb5e": "", + "572feddda23a5019007fcb5f": "", + "5ad278add7d075001a429572": "", + "5ad278add7d075001a429573": "", + "5ad278add7d075001a429574": "", + "5ad278add7d075001a429575": "", + "5ad278add7d075001a429576": "", + "572f65e9b2c2fd14005680cb": "The Rhine", + "572f65e9b2c2fd14005680cc": "", + "572f65e9b2c2fd14005680cd": "300 m3/s", + "572f65e9b2c2fd14005680ce": "", + "572f65e9b2c2fd14005680cf": "400 m (1,300 ft)", + "572ff07304bcaa1900d76ef5": "Germany", + "572ff07304bcaa1900d76ef6": "Germany", + "572ff07304bcaa1900d76ef7": "the Neckar, the Main and, later, the Moselle", + "572ff07304bcaa1900d76ef8": "", + "572ff07304bcaa1900d76ef9": "2,290 m3/s", + "5ad27abcd7d075001a42962a": "", + "5ad27abcd7d075001a42962b": "300 m3/s", + "5ad27abcd7d075001a42962c": "", + "5ad27abcd7d075001a42962d": "", + "5ad27abcd7d075001a42962e": "", + "572f6a0ba23a5019007fc5eb": "the Middle Rhine", + "572f6a0ba23a5019007fc5ec": "", + "572f6a0ba23a5019007fc5ed": "by erosion", + "572f6a0ba23a5019007fc5ee": "the Romantic Rhine", + "572ff12e04bcaa1900d76eff": "the Middle Rhine", + "572ff12e04bcaa1900d76f00": "the Rhine Gorge", + "572ff12e04bcaa1900d76f02": "its many castles and vineyards", + "572ff12e04bcaa1900d76f03": "the Romantic Rhine", + "5ad27d5dd7d075001a4296bc": "", + "5ad27d5dd7d075001a4296bd": "", + "5ad27d5dd7d075001a4296be": "", + "5ad27d5dd7d075001a4296bf": "", + "5ad27d5dd7d075001a4296c0": "", + "572f6c85947a6a140053c940": "", + "572f6c85947a6a140053c941": "Lower Rhine", + "572f6c85947a6a140053c942": "Duisburg", + "572f6c85947a6a140053c943": "The Ruhr", + "572f6c85947a6a140053c944": "drinking water", + "572ff293947a6a140053ce52": "", + "572ff293947a6a140053ce53": "Lower Rhine", + "572ff293947a6a140053ce54": "", + "572ff293947a6a140053ce55": "Duisburg", + "572ff293947a6a140053ce56": "The Ruhr", + "5ad27f33d7d075001a429752": "", + "5ad27f33d7d075001a429753": "", + "5ad27f33d7d075001a429754": "", + "5ad27f33d7d075001a429755": "", + "5ad27f33d7d075001a429756": "", + "572f6ec7a23a5019007fc621": "tourism", + "572f6ec7a23a5019007fc622": "R\u00fcdesheim am Rhein", + "572f6ec7a23a5019007fc623": "Lorelei", + "572f6ec7a23a5019007fc624": "the Middle Rhine Valley", + "572ff35f947a6a140053ce66": "tourism", + "572ff35f947a6a140053ce67": "a UNESCO World Heritage Site", + "572ff35f947a6a140053ce68": "R\u00fcdesheim am Rhein", + "572ff35f947a6a140053ce69": "Lorelei", + "572ff35f947a6a140053ce6a": "Near Sankt Goarshausen, the Rhine flows around the famous rock Lorelei", + "5ad28098d7d075001a4297b8": "", + "5ad28098d7d075001a4297b9": "", + "5ad28098d7d075001a4297ba": "", + "5ad28098d7d075001a4297bb": "Lorelei", + "5ad28098d7d075001a4297bc": "narrow river banks", + "572f7588947a6a140053c984": "", + "572f7588947a6a140053c985": "Wesel-Datteln Canal", + "572f7588947a6a140053c986": "the Lippe", + "572f7588947a6a140053c987": "the Emmerich Rhine Bridge", + "572f7588947a6a140053c988": "", + "572ff430a23a5019007fcba9": "The Lower Rhine", + "572ff430a23a5019007fcbaa": "Rhine-Ruhr region", + "572ff430a23a5019007fcbab": "Duisport", + "572ff430a23a5019007fcbac": "the Emmerich Rhine Bridge", + "572ff430a23a5019007fcbad": "400 m", + "5ad28253d7d075001a429832": "", + "5ad28253d7d075001a429833": "", + "5ad28253d7d075001a429834": "", + "5ad28253d7d075001a429835": "", + "5ad28253d7d075001a429836": "", + "572f76d1b2c2fd1400568153": "Rijn", + "572f76d1b2c2fd1400568154": "the Meuse", + "572f76d1b2c2fd1400568155": "Two thirds", + "572ff4ca04bcaa1900d76f24": "", + "572ff4ca04bcaa1900d76f25": "", + "572ff4ca04bcaa1900d76f26": "", + "572ff4ca04bcaa1900d76f27": "Oude Maas", + "5ad2852ad7d075001a429892": "", + "5ad2852ad7d075001a429893": "", + "5ad2852ad7d075001a429894": "", + "5ad2852ad7d075001a429895": "", + "572f7b33947a6a140053c9a2": "", + "572f7b33947a6a140053c9a3": "", + "572f7b33947a6a140053c9a4": "the Lek", + "572f7b33947a6a140053c9a5": "the Noord River into the Nieuwe Maas and to the North Sea", + "572ff56304bcaa1900d76f2d": "", + "572ff56304bcaa1900d76f2e": "Nederrijn", + "572ff56304bcaa1900d76f2f": "one ninth", + "572ff56304bcaa1900d76f30": "the Lek", + "572ff56304bcaa1900d76f31": "Wijk bij Duurstede", + "5ad286b4d7d075001a4298f6": "", + "5ad286b4d7d075001a4298f7": "", + "5ad286b4d7d075001a4298f8": "", + "5ad286b4d7d075001a4298f9": "", + "5ad286b4d7d075001a4298fa": "", + "572ff5fcb2c2fd1400568657": "", + "572ff5fcb2c2fd1400568658": "draining the surrounding land and polders", + "572ff5fcb2c2fd1400568659": "Kromme Rijn", + "572ff5fcb2c2fd140056865a": "Kromme Rijn", + "572ff5fcb2c2fd140056865b": "", + "5ad28861d7d075001a42993e": "", + "5ad28861d7d075001a42993f": "", + "5ad28861d7d075001a429940": "", + "5ad28861d7d075001a429941": "", + "5ad28861d7d075001a429942": "", + "572ff673b2c2fd1400568669": "The Rhine-Meuse Delta", + "572ff673b2c2fd140056866a": "near Millingen aan de Rijn", + "572ff673b2c2fd140056866b": "Rhine-Meuse", + "5ad28a54d7d075001a4299a6": "", + "5ad28a54d7d075001a4299a7": "", + "5ad28a54d7d075001a4299a8": "", + "5ad28a54d7d075001a4299a9": "", + "5ad28a54d7d075001a4299aa": "the Scheldt", + "572ff7ab04bcaa1900d76f51": "Nederrijn", + "572ff7ab04bcaa1900d76f52": "three", + "572ff7ab04bcaa1900d76f53": "Waal", + "572ff7ab04bcaa1900d76f54": "the Rip", + "572ff7ab04bcaa1900d76f55": "Old Meuse", + "5ad28c93d7d075001a429a0e": "", + "5ad28c93d7d075001a429a0f": "", + "5ad28c93d7d075001a429a10": "", + "5ad28c93d7d075001a429a11": "", + "572ff83ab2c2fd1400568681": "", + "572ff83ab2c2fd1400568682": "1421", + "572ff83ab2c2fd1400568683": "just south of today's line Merwede-Oude Maas to the North Sea", + "572ff83ab2c2fd1400568684": "", + "572ff83ab2c2fd1400568685": "1421 to 1904", + "5ad28ea7d7d075001a429a50": "1421 to 1904", + "5ad28ea7d7d075001a429a51": "", + "5ad28ea7d7d075001a429a52": "1421", + "5ad28ea7d7d075001a429a53": "", + "5ad28ea7d7d075001a429a54": "", + "572ff890a23a5019007fcbcd": "dammed", + "572ff890a23a5019007fcbce": "drainage channels", + "572ff890a23a5019007fcbcf": "The construction of Delta Works", + "572ff890a23a5019007fcbd0": "second half of the 20th Century", + "5ad2909bd7d075001a429a9e": "", + "5ad2909bd7d075001a429a9f": "", + "5ad2909bd7d075001a429aa0": "", + "5ad2909bd7d075001a429aa1": "", + "572ff935b2c2fd140056869b": "tidal", + "572ff935b2c2fd140056869c": "tidal currents", + "572ff935b2c2fd140056869d": "", + "572ff935b2c2fd140056869e": "Zaltbommel", + "5ad292f0d7d075001a429ad4": "", + "5ad292f0d7d075001a429ad5": "", + "5ad292f0d7d075001a429ad6": "", + "5ad292f0d7d075001a429ad7": "tidal currents", + "572ffa79a23a5019007fcbe9": "Tethys sea", + "572ffa79a23a5019007fcbea": "Mesozoic Era", + "572ffa79a23a5019007fcbeb": "Jurassic Period", + "572ffa79a23a5019007fcbec": "Mediterranean geography", + "572ffa79a23a5019007fcbed": "Iberia", + "5ad295d4d7d075001a429afa": "", + "5ad295d4d7d075001a429afb": "Triassic Period of the Mesozoic Era", + "5ad295d4d7d075001a429afc": "", + "5ad295d4d7d075001a429afd": "", + "5ad295d4d7d075001a429afe": "240 MBP and 220 MBP", + "572ffb02b2c2fd14005686b7": "N\u2013S rift system", + "572ffb02b2c2fd14005686b8": "Upper Rhine Graben", + "572ffb02b2c2fd14005686b9": "time of the Miocene", + "572ffb02b2c2fd14005686ba": "Rhone and Danube", + "5ad297dbd7d075001a429b2a": "", + "5ad297dbd7d075001a429b2b": "Upper Rhine Graben", + "5ad297dbd7d075001a429b2c": "", + "5ad297dbd7d075001a429b2d": "Eocene", + "572ffc0f947a6a140053cef0": "Through stream capture", + "572ffc0f947a6a140053cef1": "Pliocene period", + "572ffc0f947a6a140053cef2": "down to the Vosges Mountains", + "5ad2990cd7d075001a429b5e": "stream capture", + "5ad2990cd7d075001a429b5f": "Pliocene period", + "5ad2990cd7d075001a429b60": "", + "5ad2990cd7d075001a429b61": "", + "5ad2990cd7d075001a429b62": "", + "572ffce5a23a5019007fcc15": "the Ice Ages", + "572ffce5a23a5019007fcc16": "six", + "572ffce5a23a5019007fcc17": "120 m (390 ft)", + "572ffce5a23a5019007fcc18": "northwest", + "572ffce5a23a5019007fcc19": "offshore of Brest, France", + "5ad29b43d7d075001a429bca": "11,600 years ago", + "5ad29b43d7d075001a429bcb": "", + "5ad29b43d7d075001a429bcc": "", + "5ad29b43d7d075001a429bcd": "", + "572ffd75b2c2fd14005686e5": "~74,000", + "572ffd75b2c2fd14005686e6": "the end of the Pleistocene", + "572ffd75b2c2fd14005686e7": "west", + "572ffd75b2c2fd14005686e8": "120 m (390 ft)", + "572ffd75b2c2fd14005686e9": "", + "5ad29d35d7d075001a429c12": "", + "5ad29d35d7d075001a429c13": "", + "5ad29d35d7d075001a429c14": "", + "5ad29d35d7d075001a429c15": "", + "5ad29d35d7d075001a429c16": "", + "572fff45947a6a140053cf26": "a glacier", + "572fff45947a6a140053cf27": "A tundra", + "572fff45947a6a140053cf28": "ca. 22,000\u201314,000 yr BP", + "572fff45947a6a140053cf29": "ice-sheets", + "572fff45947a6a140053cf2a": "loess", + "5ad29f7ed7d075001a429c72": "a glacier", + "5ad29f7ed7d075001a429c73": "", + "5ad29f7ed7d075001a429c74": "", + "5ad29f7ed7d075001a429c75": "", + "572fffb404bcaa1900d76fef": "22,000 years ago", + "572fffb404bcaa1900d76ff0": "thaw and fall-winter snow covers melted in spring", + "572fffb404bcaa1900d76ff1": "the Rhine", + "572fffb404bcaa1900d76ff2": "13,000 BP", + "572fffb404bcaa1900d76ff3": "9000 BP", + "5ad2a15ad7d075001a429cc8": "", + "5ad2a15ad7d075001a429cc9": "", + "5ad2a15ad7d075001a429cca": "", + "5ad2a15ad7d075001a429ccb": "", + "573003dd947a6a140053cf42": "7500 yr ago", + "573003dd947a6a140053cf43": "Rates of sea-level rise", + "573003dd947a6a140053cf44": "", + "573003dd947a6a140053cf45": "ongoing tectonic subsidence", + "573003dd947a6a140053cf46": "1\u20133 cm (0.39\u20131.18 in) per century", + "5ad2a3b3d7d075001a429d5a": "7500 yr ago", + "5ad2a3b3d7d075001a429d5b": "", + "5ad2a3b3d7d075001a429d5c": "", + "5ad2a3b3d7d075001a429d5d": "", + "5ad2a3b3d7d075001a429d5e": "", + "5730042804bcaa1900d77011": "~11,700 years ago", + "5730042804bcaa1900d77012": "Late-Glacial valley", + "5730042804bcaa1900d77013": "Netherlands", + "5730042804bcaa1900d77014": "~8,000 years ago", + "5ad2a58bd7d075001a429dcc": "", + "5ad2a58bd7d075001a429dcd": "", + "5ad2a58bd7d075001a429dce": "", + "5ad2a58bd7d075001a429dcf": "", + "57300580b2c2fd140056874d": "Since ~3000 yr BP", + "57300580b2c2fd140056874e": "sediment load", + "57300580b2c2fd140056874f": "flooding", + "57300580b2c2fd1400568750": "approximately 80", + "57300580b2c2fd1400568751": "11\u201313th century AD", + "5ad2a71ad7d075001a429e02": "Since ~3000 yr BP", + "5ad2a71ad7d075001a429e03": "", + "5ad2a71ad7d075001a429e04": "", + "5ad2a71ad7d075001a429e05": "", + "5ad2a71ad7d075001a429e06": "", + "5730069004bcaa1900d7702d": "the North Sea", + "5730069004bcaa1900d7702e": "the North Sea", + "5730069004bcaa1900d7702f": "to the north", + "5730069004bcaa1900d77030": "", + "5730069004bcaa1900d77031": "three", + "5ad2a901d7d075001a429e28": "", + "5ad2a901d7d075001a429e29": "", + "5ad2a901d7d075001a429e2a": "", + "5ad2a901d7d075001a429e2b": "", + "5ad2a901d7d075001a429e2c": "", + "57300761947a6a140053cf9a": "1st century BC", + "57300761947a6a140053cf9b": "Germania", + "57300761947a6a140053cf9c": "6th century BC", + "57300761947a6a140053cf9d": "Herodotus", + "5ad2afe2d7d075001a429f1a": "", + "5ad2afe2d7d075001a429f1b": "", + "5ad2afe2d7d075001a429f1c": "", + "5ad2afe2d7d075001a429f1d": "8.727", + "573007fab2c2fd140056876b": "AD 14", + "573007fab2c2fd140056876c": "upper Danube", + "573007fab2c2fd140056876d": "", + "573007fab2c2fd140056876e": "the fertile plain of Frankfurt", + "573007fab2c2fd140056876f": "eastwards", + "5ad2b1e1d7d075001a429f68": "AD 14", + "5ad2b1e1d7d075001a429f69": "", + "5ad2b1e1d7d075001a429f6a": "", + "5ad2b1e1d7d075001a429f6b": "", + "5ad2b1e1d7d075001a429f6c": "", + "57300888b2c2fd1400568775": "eight", + "57300888b2c2fd1400568776": "whether a state or threat of war existed", + "57300888b2c2fd1400568777": "Pannonian troops", + "57300888b2c2fd1400568778": "oppidum Ubiorum", + "57300888b2c2fd1400568779": "oppidum Ubiorum", + "5ad2b3bcd7d075001a429fa4": "", + "5ad2b3bcd7d075001a429fa5": "AD 14 and 180", + "5ad2b3bcd7d075001a429fa6": "two", + "5ad2b3bcd7d075001a429fa7": "XXI", + "5ad2b3bcd7d075001a429fa8": "", + "57300911947a6a140053cfb6": "5th century", + "57300911947a6a140053cfb7": "kingdoms of Francia on the Lower Rhine", + "57300911947a6a140053cfb8": "dragons rock", + "57300911947a6a140053cfb9": "Siegfried", + "57300911947a6a140053cfba": "", + "5ad2b5ddd7d075001a429ff2": "", + "5ad2b5ddd7d075001a429ff3": "", + "5ad2b5ddd7d075001a429ff4": "", + "5ad2b5ddd7d075001a429ff5": "", + "5ad2b5ddd7d075001a429ff6": "", + "573009a004bcaa1900d7704f": "9th", + "573009a004bcaa1900d77050": "10th century", + "573009a004bcaa1900d77051": "Lower Lorraine", + "573009a004bcaa1900d77052": "Archduke Sigismund of Austria", + "573009a004bcaa1900d77053": "1469", + "5ad2b72fd7d075001a42a022": "6th century", + "5ad2b72fd7d075001a42a023": "", + "5ad2b72fd7d075001a42a024": "", + "5ad2b72fd7d075001a42a025": "", + "5ad2b72fd7d075001a42a026": "", + "57300a25a23a5019007fcc97": "Since the Peace of Westphalia", + "57300a25a23a5019007fcc98": "Establishing \"natural borders\" on the Rhine", + "57300a25a23a5019007fcc99": "Napoleon", + "57300a25a23a5019007fcc9a": "1806", + "57300a25a23a5019007fcc9b": "1840", + "5ad2b882d7d075001a42a040": "", + "5ad2b882d7d075001a42a041": "", + "5ad2b882d7d075001a42a042": "", + "5ad2b882d7d075001a42a043": "", + "5ad2b882d7d075001a42a044": "", + "57300a9a04bcaa1900d77063": "At the end of World War I", + "57300a9a04bcaa1900d77064": "1930", + "57300a9a04bcaa1900d77065": "the German army", + "57300a9a04bcaa1900d77066": "Adolf Hitler's rise to power", + "57300a9a04bcaa1900d77067": "1936", + "5ad2ba09d7d075001a42a064": "", + "5ad2ba09d7d075001a42a065": "", + "5ad2ba09d7d075001a42a066": "", + "5ad2ba09d7d075001a42a067": "", + "57300bf504bcaa1900d77087": "Arnhem", + "57300bf504bcaa1900d77088": "a formidable natural obstacle", + "57300bf504bcaa1900d77089": "September 1944", + "57300bf504bcaa1900d7708a": "the Ludendorff Bridge", + "57300bf504bcaa1900d7708b": "Seven Days to the River Rhine", + "5ad2bb5fd7d075001a42a080": "World War II", + "5ad2bb5fd7d075001a42a081": "", + "5ad2bb5fd7d075001a42a082": "", + "5ad2bb5fd7d075001a42a083": "Seven Days", + "5ad2bb5fd7d075001a42a084": "Seven", + "57300c67947a6a140053cff0": "1,230 kilometres", + "57300c67947a6a140053cff1": "the German encyclopedia Knaurs Lexikon", + "57300c67947a6a140053cff2": "", + "57300c67947a6a140053cff3": "a typographical error", + "57300c68947a6a140053cff4": "1932", + "5ad2bcdfd7d075001a42a0ae": "", + "5ad2bcdfd7d075001a42a0af": "", + "5ad2bcdfd7d075001a42a0b0": "", + "5ad2bcdfd7d075001a42a0b1": "", + "5ad2bcdfd7d075001a42a0b2": "", + "572fac17947a6a140053cb54": "1998", + "572fac17947a6a140053cb55": "Scotland Act 1998", + "572fac17947a6a140053cb56": "the areas in which it can make laws", + "572fac17947a6a140053cb57": "the Parliament of the United Kingdom", + "572fac17947a6a140053cb58": "Westminster", + "5ad0213377cf76001a686b0c": "", + "5ad0213377cf76001a686b0d": "", + "5ad0213377cf76001a686b0e": "", + "5ad0213377cf76001a686b0f": "", + "5ad0213377cf76001a686b10": "", + "572facb0a23a5019007fc863": "the lack of a Parliament of Scotland", + "572facb0a23a5019007fc864": "three", + "572facb0a23a5019007fc865": "due to the outbreak of the First World War", + "572facb0a23a5019007fc866": "late 1960s", + "572facb0a23a5019007fc867": "", + "5ad0225377cf76001a686b3e": "", + "5ad0225377cf76001a686b3f": "", + "5ad0225377cf76001a686b40": "", + "5ad0225377cf76001a686b41": "", + "5ad0225377cf76001a686b42": "", + "572fad30a23a5019007fc86d": "North Sea", + "572fad30a23a5019007fc86e": "", + "572fad30a23a5019007fc86f": "the revenues from the oil were not benefitting Scotland as much as they should", + "572fad30a23a5019007fc870": "1974", + "572fad30a23a5019007fc871": "1978", + "5ad0247477cf76001a686b90": "", + "5ad0247477cf76001a686b91": "", + "5ad0247477cf76001a686b92": "", + "5ad0247477cf76001a686b93": "", + "572fadcbb2c2fd1400568329": "Edinburgh", + "572fadcbb2c2fd140056832a": "40%", + "572fadcbb2c2fd140056832b": "failed", + "572fadcbb2c2fd140056832c": "51.6%", + "572fadcbb2c2fd140056832d": "32.9%", + "5ad025df77cf76001a686ba2": "", + "5ad025df77cf76001a686ba3": "", + "5ad025df77cf76001a686ba4": "", + "5ad025df77cf76001a686ba5": "32.9%", + "572fae4b04bcaa1900d76bdf": "a Scottish Parliament", + "572fae4b04bcaa1900d76be0": "the Conservative Party", + "572fae4b04bcaa1900d76be1": "1989", + "572fae4b04bcaa1900d76be2": "the Convention", + "5ad026a777cf76001a686bc8": "", + "5ad026a777cf76001a686bc9": "", + "5ad026a777cf76001a686bca": "", + "5ad026a777cf76001a686bcb": "", + "572faec7b2c2fd1400568333": "the Holyrood area of Edinburgh", + "572faec7b2c2fd1400568334": "Enric Miralles", + "572faec7b2c2fd1400568335": "Spanish", + "572faec7b2c2fd1400568336": "leaf-shaped", + "572faec7b2c2fd1400568337": "Queen Elizabeth II", + "5ad0278077cf76001a686be4": "", + "5ad0278077cf76001a686be5": "", + "5ad0278077cf76001a686be6": "", + "5ad0278077cf76001a686be7": "", + "5ad0278077cf76001a686be8": "", + "572faf74b2c2fd1400568347": "General Assembly Hall of the Church of Scotland on the Royal Mile in Edinburgh", + "572faf74b2c2fd1400568348": "the courtyard adjoining the Assembly Hall", + "572faf74b2c2fd1400568349": "the meeting of the Church's General Assembly", + "572faf74b2c2fd140056834a": "", + "572faf74b2c2fd140056834b": "University of Aberdeen", + "5ad0285977cf76001a686c0c": "", + "5ad0285977cf76001a686c0d": "", + "5ad0285977cf76001a686c0e": "", + "5ad0285977cf76001a686c0f": "", + "572fb059947a6a140053cb80": "City of Edinburgh Council", + "572fb059947a6a140053cb81": "Lothian Regional Council", + "572fb059947a6a140053cb82": "", + "572fb059947a6a140053cb83": "Parliament Square, High Street and George IV Bridge in Edinburgh", + "572fb059947a6a140053cb84": "the main hall", + "5ad0291f77cf76001a686c28": "", + "5ad0291f77cf76001a686c29": "", + "5ad0291f77cf76001a686c2a": "", + "5ad0291f77cf76001a686c2b": "", + "572fb42904bcaa1900d76c15": "one MSP", + "572fb42904bcaa1900d76c16": "Tricia Marwick", + "572fb42904bcaa1900d76c17": "secret", + "572fb42904bcaa1900d76c18": "129", + "572fb42904bcaa1900d76c19": "A vote clerk", + "5ad02a9777cf76001a686c5e": "deputies", + "5ad02a9777cf76001a686c5f": "", + "5ad02a9777cf76001a686c60": "", + "5ad02a9777cf76001a686c61": "", + "5ad02a9777cf76001a686c62": "", + "572fbb04a23a5019007fc8f7": "", + "572fbb04a23a5019007fc8f8": "the Parliamentary Bureau", + "572fbb04a23a5019007fc8f9": "five or more", + "572fbb04a23a5019007fc8fa": "The Presiding Officer", + "5ad02bef77cf76001a686ca2": "Parliamentary Bureau", + "5ad02bef77cf76001a686ca3": "", + "5ad02bef77cf76001a686ca4": "", + "5ad02bef77cf76001a686ca5": "", + "572fbea404bcaa1900d76c5b": "a hemicycle", + "572fbea404bcaa1900d76c5c": "desire to encourage consensus amongst elected members", + "572fbea404bcaa1900d76c5d": "131", + "572fbea404bcaa1900d76c5e": "2", + "572fbea404bcaa1900d76c5f": "vote", + "5ad02cfc77cf76001a686ce2": "", + "5ad02cfc77cf76001a686ce3": "", + "5ad02cfc77cf76001a686ce4": "", + "5ad02cfc77cf76001a686ce5": "", + "5ad02cfc77cf76001a686ce6": "", + "572fbf21a23a5019007fc937": "silver and inlaid with gold", + "572fbf21a23a5019007fc938": "Scottish rivers", + "572fbf21a23a5019007fc939": "Wisdom, Compassion, Justice and Integrity", + "572fbf21a23a5019007fc93a": "the Queen", + "572fbf21a23a5019007fc93b": "a glass case suspended from the lid", + "5ad02de677cf76001a686d1e": "", + "5ad02de677cf76001a686d1f": "", + "5ad02de677cf76001a686d20": "", + "5ad02de677cf76001a686d21": "", + "5ad02de677cf76001a686d22": "the parliamentary mace", + "572fbfa504bcaa1900d76c73": "", + "572fbfa504bcaa1900d76c74": "the debating chamber", + "572fbfa504bcaa1900d76c75": "the public", + "572fbfa504bcaa1900d76c76": "free", + "572fbfa504bcaa1900d76c77": "the Official Report", + "5ad02e6777cf76001a686d44": "Parliament", + "5ad02e6777cf76001a686d45": "", + "5ad02e6777cf76001a686d46": "", + "5ad02e6777cf76001a686d47": "", + "5ad02e6777cf76001a686d48": "", + "572fc043a23a5019007fc95d": "Wednesdays", + "572fc043a23a5019007fc95e": "up to four minutes", + "572fc043a23a5019007fc95f": "religious beliefs", + "572fc043a23a5019007fc960": "the Presiding Officer", + "572fc043a23a5019007fc961": "nominate speakers", + "5ad02f4977cf76001a686d72": "", + "5ad02f4977cf76001a686d73": "Time for Reflection", + "5ad02f4977cf76001a686d74": "", + "5ad02f4977cf76001a686d75": "the Presiding Officer", + "572fc41f947a6a140053cc80": "The Presiding Officer", + "572fc41f947a6a140053cc81": "who speaks in chamber debates and the amount of time for which they are allowed to speak", + "572fc41f947a6a140053cc82": "", + "572fc41f947a6a140053cc83": "ministers or party leaders", + "572fc41f947a6a140053cc84": "Gaelic", + "5ad02fdf77cf76001a686d98": "", + "5ad02fdf77cf76001a686d99": "", + "5ad02fdf77cf76001a686d9a": "", + "5ad02fdf77cf76001a686d9b": "", + "5ad02fdf77cf76001a686d9c": "", + "572fc49d04bcaa1900d76ccb": "5 pm", + "572fc49d04bcaa1900d76ccc": "Decision Time", + "572fc49d04bcaa1900d76ccd": "vote", + "572fc49d04bcaa1900d76cce": "electronic consoles on their desks", + "572fc49d04bcaa1900d76ccf": "seconds", + "5ad0309377cf76001a686dbe": "all the motions and amendments", + "5ad0309377cf76001a686dbf": "Decision Time", + "5ad0309377cf76001a686dc0": "At Decision Time", + "5ad0309377cf76001a686dc1": "", + "5ad0309377cf76001a686dc2": "", + "572fc5a1947a6a140053cc8a": "The outcome of most votes", + "572fc5a1947a6a140053cc8b": "political parties", + "572fc5a1947a6a140053cc8c": "whips", + "572fc5a1947a6a140053cc8d": "", + "572fc5a1947a6a140053cc8e": "moral", + "5ad0313b77cf76001a686dd2": "", + "5ad0313b77cf76001a686dd3": "", + "5ad0313b77cf76001a686dd4": "", + "5ad0313b77cf76001a686dd5": "", + "572fc659b2c2fd1400568447": "Immediately after Decision Time", + "572fc659b2c2fd1400568448": "45 minutes", + "572fc659b2c2fd1400568449": "issues which may be of interest to a particular area", + "572fc659b2c2fd140056844a": "", + "572fc659b2c2fd140056844b": "winds up\" the debate", + "5ad031cf77cf76001a686dea": "", + "5ad031cf77cf76001a686deb": "", + "5ad031cf77cf76001a686dec": "", + "5ad031cf77cf76001a686ded": "Members Business", + "572fc6f204bcaa1900d76cf5": "in committee", + "572fc6f204bcaa1900d76cf6": "stronger", + "572fc6f204bcaa1900d76cf7": "there is no revising chamber", + "572fc6f204bcaa1900d76cf8": "conduct inquiries and scrutinise legislation", + "572fc6f204bcaa1900d76cf9": "", + "5ad0327377cf76001a686e04": "", + "5ad0327377cf76001a686e05": "strengthening the role of backbenchers in their scrutiny of the government", + "5ad0327377cf76001a686e06": "", + "5ad0327377cf76001a686e07": "", + "572fc78d04bcaa1900d76d07": "", + "572fc78d04bcaa1900d76d08": "the balance of parties across Parliament", + "572fc78d04bcaa1900d76d09": "their functions", + "572fc78d04bcaa1900d76d0a": "", + "572fc78d04bcaa1900d76d0b": "", + "5ad0392577cf76001a686e4e": "", + "5ad0392577cf76001a686e4f": "", + "5ad0392577cf76001a686e50": "", + "5ad0392577cf76001a686e51": "", + "572fc80b04bcaa1900d76d11": "at the beginning of each parliamentary session", + "572fc80b04bcaa1900d76d12": "one", + "572fc80b04bcaa1900d76d13": "current Subject Committees", + "572fc80b04bcaa1900d76d14": "", + "5ad039be77cf76001a686e5e": "", + "5ad039be77cf76001a686e5f": "", + "5ad039be77cf76001a686e60": "", + "5ad039be77cf76001a686e61": "", + "572fc8a904bcaa1900d76d1f": "", + "572fc8a904bcaa1900d76d20": "large-scale development projects", + "572fc8a904bcaa1900d76d21": "", + "572fc8a904bcaa1900d76d22": "Private Bill Committees", + "5ad03aa977cf76001a686e88": "", + "5ad03aa977cf76001a686e89": "", + "5ad03aa977cf76001a686e8a": "", + "5ad03aa977cf76001a686e8b": "", + "572fca7eb2c2fd1400568473": "The Scotland Act 1998", + "572fca7eb2c2fd1400568474": "Queen Elizabeth II", + "572fca7eb2c2fd1400568475": "the devolved competencies", + "572fca7eb2c2fd1400568476": "the Parliament of the United Kingdom at Westminster", + "572fca7eb2c2fd1400568477": "the Parliament", + "5ad03b2777cf76001a686e98": "", + "5ad03b2777cf76001a686e99": "", + "5ad03b2777cf76001a686e9a": "", + "5ad03b2777cf76001a686e9b": "", + "5ad03b2777cf76001a686e9c": "", + "572fcb6da23a5019007fc9f1": "Schedule 5", + "572fcb6da23a5019007fc9f2": "the Scottish Parliament", + "572fcb6da23a5019007fc9f3": "", + "572fcb6da23a5019007fc9f4": "up to 3 pence in the pound", + "572fcb6da23a5019007fc9f5": "2012 Act", + "5ad03c2977cf76001a686eb4": "", + "5ad03c2977cf76001a686eb5": "", + "5ad03c2977cf76001a686eb6": "", + "5ad03c2977cf76001a686eb7": "", + "572fcc43b2c2fd140056847d": "Reserved matters", + "572fcc43b2c2fd140056847e": "", + "572fcc43b2c2fd140056847f": "", + "572fcc43b2c2fd1400568480": "", + "5ad03cd377cf76001a686ec4": "", + "5ad03cd377cf76001a686ec5": "", + "5ad03cd377cf76001a686ec6": "", + "5ad03cd377cf76001a686ec7": "", + "572fcd86947a6a140053ccda": "Bills", + "572fcd86947a6a140053ccdb": "the Scottish Government", + "572fcd86947a6a140053ccdc": "", + "572fcd86947a6a140053ccdd": "an outside proposer", + "572fcd86947a6a140053ccde": "in a number of stages", + "5ad03e5077cf76001a686ed4": "", + "5ad03e5077cf76001a686ed5": "", + "5ad03e5077cf76001a686ed6": "", + "5ad03e5077cf76001a686ed7": "", + "572fce12a23a5019007fca11": "the first, or introductory stage", + "572fce13a23a5019007fca12": "documents", + "572fce13a23a5019007fca13": "", + "572fce13a23a5019007fca14": "in the relevant committee or committees", + "572fce13a23a5019007fca15": "Stage 2", + "5ad03efa77cf76001a686edc": "", + "5ad03efa77cf76001a686edd": "", + "5ad03efa77cf76001a686ede": "", + "5ad03efa77cf76001a686edf": "", + "572fd1c4947a6a140053cd02": "Stage 3", + "572fd1c4947a6a140053cd03": "two parts", + "572fd1c4947a6a140053cd04": "final vote", + "572fd1c4947a6a140053cd05": "wrecking amendments", + "572fd1c4947a6a140053cd06": "Decision Time", + "5ad03f8077cf76001a686ee4": "", + "5ad03f8077cf76001a686ee5": "Stage 3", + "5ad03f8077cf76001a686ee6": "", + "5ad03f8077cf76001a686ee7": "", + "572fd264b2c2fd14005684a9": "the Monarch", + "572fd264b2c2fd14005684aa": "", + "572fd264b2c2fd14005684ab": "4-week", + "572fd264b2c2fd14005684ac": "the Supreme Court of the United Kingdom", + "572fd264b2c2fd14005684ad": "a conventional enacting formula", + "5ad0403c77cf76001a686eec": "", + "5ad0403c77cf76001a686eed": "", + "5ad0403c77cf76001a686eee": "", + "5ad0403c77cf76001a686eef": "", + "5ad0403c77cf76001a686ef0": "", + "572fd47fa23a5019007fca55": "The party, or parties, that hold the majority of seats in the Parliament", + "572fd47fa23a5019007fca56": "a First Minister", + "572fd47fa23a5019007fca57": "Any member", + "572fd47fa23a5019007fca58": "elected MSPs", + "572fd47fa23a5019007fca59": "the Sovereign", + "5ad040d977cf76001a686ef6": "", + "5ad040d977cf76001a686ef7": "", + "5ad040d977cf76001a686ef8": "", + "5ad040d977cf76001a686ef9": "", + "572fd6aa04bcaa1900d76d9f": "Thursday", + "572fd6aa04bcaa1900d76da0": "May", + "572fd6aa04bcaa1900d76da1": "the Monarch", + "572fd6aa04bcaa1900d76da2": "28", + "572fd6aa04bcaa1900d76da3": "they supplant it", + "5ad0415577cf76001a686f04": "", + "5ad0415577cf76001a686f05": "", + "5ad0415577cf76001a686f06": "", + "5ad0415577cf76001a686f07": "", + "572fd73e947a6a140053cd32": "Several procedures", + "572fd73e947a6a140053cd33": "the leaders of the opposition parties and other MSPs", + "572fd73e947a6a140053cd34": "a statement", + "572fd73e947a6a140053cd35": "issues related to the substance of the statement", + "5ad041c477cf76001a686f0c": "", + "5ad041c477cf76001a686f0d": "", + "5ad041c477cf76001a686f0e": "", + "5ad041c477cf76001a686f0f": "", + "572fd7b8947a6a140053cd3a": "Parliamentary time", + "572fd7b8947a6a140053cd3b": "Thursday", + "572fd7b8947a6a140053cd3c": "any member of the Scottish Government", + "572fd7b8947a6a140053cd3d": "issues under their jurisdiction", + "572fd7b8947a6a140053cd3e": "four", + "5ad0426c77cf76001a686f1c": "", + "5ad0426c77cf76001a686f1d": "", + "5ad0426c77cf76001a686f1e": "", + "5ad0426c77cf76001a686f1f": "Opposition leaders", + "572fd8efb2c2fd14005684f9": "73", + "572fd8efb2c2fd14005684fa": "one", + "572fd8efb2c2fd14005684fb": "2005", + "572fd8efb2c2fd14005684fc": "55,000", + "572fd8efb2c2fd14005684fd": "their dispersed population and distance from the Scottish Parliament in Edinburgh", + "5ad0431077cf76001a686f2e": "", + "5ad0431077cf76001a686f2f": "", + "5ad0431077cf76001a686f30": "", + "5ad0431077cf76001a686f31": "", + "572fda6fb2c2fd140056850b": "proportionally to the number of votes received in the second vote of the ballot using the d'Hondt method", + "572fda6fb2c2fd140056850c": "d'Hondt method", + "572fda6fb2c2fd140056850d": "quotient", + "572fda6fb2c2fd140056850e": "second seat", + "572fda6fb2c2fd140056850f": "iteratively", + "5ad043a977cf76001a686f36": "", + "5ad043a977cf76001a686f37": "", + "5ad043a977cf76001a686f38": "", + "5ad043a977cf76001a686f39": "", + "572fdb17b2c2fd140056851d": "a number of qualifications", + "572fdb17b2c2fd140056851e": "1981", + "572fdb17b2c2fd140056851f": "18", + "572fdb17b2c2fd1400568520": "", + "572fdb17b2c2fd1400568521": "Mental Health (Care and Treatment) (Scotland) Act 2003", + "5ad0440a77cf76001a686f48": "", + "5ad0440a77cf76001a686f49": "", + "5ad0440a77cf76001a686f4a": "", + "5ad0440a77cf76001a686f4b": "", + "572fdbb004bcaa1900d76dd9": "the Scottish Parliament", + "572fdbb004bcaa1900d76dda": "Labour", + "572fdbb004bcaa1900d76ddb": "", + "572fdbb004bcaa1900d76ddc": "eight", + "572fdbb004bcaa1900d76ddd": "Scottish independence", + "5ad0447f77cf76001a686f50": "16", + "5ad0447f77cf76001a686f51": "", + "5ad0447f77cf76001a686f52": "", + "5ad0447f77cf76001a686f53": "Democrats", + "572fdc34a23a5019007fca93": "Conservatives", + "572fdc34a23a5019007fca94": "Edinburgh Pentlands", + "572fdc34a23a5019007fca95": "five seats", + "572fdc34a23a5019007fca96": "", + "572fdc34a23a5019007fca97": "", + "5ad044f977cf76001a686f60": "", + "5ad044f977cf76001a686f61": "", + "5ad044f977cf76001a686f62": "", + "5ad044f977cf76001a686f63": "", + "5ad044f977cf76001a686f64": "Cameron", + "572fdd03a23a5019007fca9d": "procedural", + "572fdd03a23a5019007fca9e": "domestic legislation of the Scottish Parliament", + "572fdd03a23a5019007fca9f": "the West Lothian question", + "572fdd03a23a5019007fcaa0": "Conservative", + "572fdd03a23a5019007fcaa1": "England", + "5ad0457b77cf76001a686f6a": "", + "5ad0457b77cf76001a686f6b": "", + "5ad0457b77cf76001a686f6c": "", + "5ad0457b77cf76001a686f6d": "", + "572ff626947a6a140053ce8e": "Islamism", + "572ff626947a6a140053ce8f": "all spheres", + "572ff626947a6a140053ce90": "reordering", + "572ff626947a6a140053ce91": "two poles", + "572ff626947a6a140053ce92": "revolution or invasion", + "5acfe40a77cf76001a686390": "", + "5acfe40a77cf76001a686391": "", + "5acfe40a77cf76001a686392": "", + "5acfe40a77cf76001a686393": "", + "572ff760b2c2fd1400568677": "democratic", + "572ff760b2c2fd1400568678": "Palestine", + "572ff760b2c2fd1400568679": "abolish the state of Israel", + "572ff760b2c2fd140056867a": "democracy", + "572ff760b2c2fd140056867b": "religious", + "5acfe5ce77cf76001a6863ac": "", + "5acfe5ce77cf76001a6863ad": "", + "5acfe5ce77cf76001a6863ae": "", + "5acfe5ce77cf76001a6863af": "", + "5acfe5ce77cf76001a6863b0": "", + "572ff86004bcaa1900d76f65": "", + "572ff86004bcaa1900d76f66": "Sunni pan-Islamism", + "572ff86004bcaa1900d76f67": "sharia", + "572ff86004bcaa1900d76f68": "democracy", + "572ff86004bcaa1900d76f69": "to maintain their legitimacy", + "5acfe69177cf76001a6863be": "", + "5acfe69177cf76001a6863bf": "", + "5acfe69177cf76001a6863c0": "", + "5acfe69177cf76001a6863c1": "", + "5acfe69177cf76001a6863c2": "", + "572ff932a23a5019007fcbd5": "political", + "572ff932a23a5019007fcbd6": "Islam", + "572ff932a23a5019007fcbd7": "", + "572ff932a23a5019007fcbd8": "illiberal Islamic regimes", + "572ff932a23a5019007fcbd9": "religion from politics", + "5acfe6eb77cf76001a6863c8": "", + "5acfe6eb77cf76001a6863c9": "", + "5acfe6eb77cf76001a6863ca": "", + "5acfe6eb77cf76001a6863cb": "illiberal Islamic regimes", + "5acfe6eb77cf76001a6863cc": "", + "572ffabf04bcaa1900d76f9f": "Islamism", + "572ffabf04bcaa1900d76fa0": "Americans", + "572ffabf04bcaa1900d76fa1": "a historical fluke of the \"short-lived era of the heyday of secular Arab nationalism", + "572ffabf04bcaa1900d76fa2": "between 1945 and 1970", + "572ffabf04bcaa1900d76fa3": "quietist/non-political Islam", + "5acfe73c77cf76001a6863d2": "", + "5acfe73c77cf76001a6863d3": "", + "5acfe73c77cf76001a6863d4": "", + "5acfe73c77cf76001a6863d5": "between 1945 and 1970", + "5acfe73c77cf76001a6863d6": "quietist/non-political Islam", + "572ffbaa947a6a140053cee6": "During the 1970s", + "572ffbaa947a6a140053cee7": "dangerous enemies", + "572ffbaa947a6a140053cee8": "leftist/communist/nationalist insurgents/opposition", + "572ffbaa947a6a140053cee9": "mujahideen Muslim Afghanistan", + "572ffbaab2c2fd14005686cd": "experience, ideology, and weapons", + "5acfe78477cf76001a6863e6": "", + "5acfe78477cf76001a6863e7": "dangerous enemies", + "5acfe78477cf76001a6863e8": "leftist/communist/nationalist insurgents/opposition", + "5acfe78477cf76001a6863e9": "", + "5acfe78477cf76001a6863ea": "", + "572ffc99947a6a140053cef6": "Anwar Sadat", + "572ffc99947a6a140053cef7": "making peace", + "572ffc99947a6a140053cef8": "making peace with Israel", + "572ffc99947a6a140053cef9": "1975", + "572ffc99947a6a140053cefa": "making peace with Israel \u2013 released Islamists from prison and welcomed home exiles in tacit exchange for political support", + "5acfe80877cf76001a6863f0": "", + "5acfe80877cf76001a6863f1": "leftists", + "5acfe80877cf76001a6863f2": "home exiles", + "5acfe80877cf76001a6863f3": "1975", + "5acfe80877cf76001a6863f4": "making peace with Israel \u2013 released Islamists from prison and welcomed home exiles in tacit exchange for political support", + "572ffd9e04bcaa1900d76fc7": "Saudi-based Wahhabism", + "572ffd9e04bcaa1900d76fc8": "", + "572ffd9e04bcaa1900d76fc9": "horrible wars", + "572ffd9e04bcaa1900d76fca": "", + "572ffd9e04bcaa1900d76fcb": "Saudi-interpretation", + "5acfe84677cf76001a686404": "", + "5acfe84677cf76001a686405": "", + "5acfe84677cf76001a686406": "", + "5acfe84677cf76001a686407": "infidels", + "5acfe84677cf76001a686408": "", + "572ffe6fb2c2fd14005686ef": "Islamist", + "572ffe6fb2c2fd14005686f0": "housing", + "572ffe6fb2c2fd14005686f1": "to avoid prohibitively costly dowry demands, legal assistance, sports facilities, and women's groups", + "572ffe6fb2c2fd14005686f2": "incompetent, inefficient, or neglectful", + "572ffe6fb2c2fd14005686f3": "rhetoric", + "5acfe89777cf76001a68640e": "", + "5acfe89777cf76001a68640f": "", + "5acfe89777cf76001a686410": "", + "5acfe89777cf76001a686411": "", + "5acfe89777cf76001a686412": "", + "572ffee1947a6a140053cf14": "law and philosophy", + "572ffee1947a6a140053cf15": "All India Muslim League", + "572ffee1947a6a140053cf16": "1908", + "572ffee1947a6a140053cf17": "Indian National Congress", + "572ffee1947a6a140053cf18": "The Reconstruction of Religious Thought in Islam", + "5acfe8e777cf76001a686422": "", + "5acfe8e777cf76001a686423": "", + "5acfe8e777cf76001a686424": "", + "5acfe8e777cf76001a686425": "", + "5acfe8e777cf76001a686426": "", + "572fffb1b2c2fd14005686f9": "secularism and secular nationalism", + "572fffb1b2c2fd14005686fa": "crowd out", + "572fffb1b2c2fd14005686fb": "nationalist differences", + "572fffb1b2c2fd14005686fc": "1930", + "572fffb1b2c2fd14005686fd": "Pakistan movement", + "5acfe91c77cf76001a686436": "", + "5acfe91c77cf76001a686437": "crowd", + "5acfe91c77cf76001a686438": "", + "5acfe91c77cf76001a686439": "", + "5acfe91c77cf76001a68643a": "", + "5730005db2c2fd1400568703": "Sayyid Abul Ala Maududi", + "5730005db2c2fd1400568704": "journalism", + "5730005db2c2fd1400568705": "1941", + "57300137b2c2fd1400568717": "Sayyid Abul Ala Maududi", + "57300137b2c2fd1400568718": "journalism", + "57300137b2c2fd140056871a": "", + "57300137b2c2fd140056871b": "modern context", + "5acfe95877cf76001a686440": "", + "5acfe95877cf76001a686441": "journalism", + "5acfe95877cf76001a686442": "1972", + "5acfe95877cf76001a686443": "", + "5acfe95877cf76001a686444": "", + "57300200b2c2fd1400568729": "Sharia", + "57300200b2c2fd140056872a": "an Islamic state", + "57300200b2c2fd140056872b": "unity of God", + "57300200b2c2fd140056872c": "Islamic", + "57300200b2c2fd140056872d": "an educational process or da'wah", + "5acfe99177cf76001a686454": "Sharia", + "5acfe99177cf76001a686455": "Sharia", + "5acfe99177cf76001a686456": "", + "5acfe99177cf76001a686457": "", + "5acfe99177cf76001a686458": "", + "5730035e04bcaa1900d77001": "1928", + "5730035e04bcaa1900d77002": "Ismailiyah, Egypt", + "5730035e04bcaa1900d77003": "Hassan al Banna", + "5730035e04bcaa1900d77004": "the Qur'an", + "5730035e04bcaa1900d77005": "imperialist", + "5acfe9d477cf76001a68645e": "", + "5acfe9d477cf76001a68645f": "", + "5730040f947a6a140053cf4c": "violence", + "5730040f947a6a140053cf4d": "1949", + "5730040f947a6a140053cf4e": "Mahmud Fami Naqrashi", + "5730040f947a6a140053cf4f": "1948", + "5730040f947a6a140053cf50": "Gamal Abdul Nasser", + "5acfea0677cf76001a686462": "orders", + "5acfea0677cf76001a686463": "", + "5acfea0677cf76001a686464": "", + "5acfea0677cf76001a686465": "1948", + "5acfea0677cf76001a686466": "Gamal Abdul Nasser", + "573004bf947a6a140053cf56": "one of the most influential movements", + "573004bf947a6a140053cf57": "semi-legal", + "573004bf947a6a140053cf58": "field candidates", + "573004bf947a6a140053cf59": "75%", + "573004bf947a6a140053cf5a": "Mohamed Morsi", + "5acfea4977cf76001a686476": "", + "5acfea4977cf76001a686477": "semi-legal", + "5acfea4977cf76001a686478": "field candidates", + "5acfea4977cf76001a686479": "75%", + "5acfea4977cf76001a68647a": "Mohamed Morsi", + "573005b9947a6a140053cf6a": "quick and decisive defeat of the Arab troops during the Six-Day War by Israeli troops constituted a pivotal event in the Arab Muslim world", + "573005b9947a6a140053cf6b": "a pivotal event", + "573005b9947a6a140053cf6c": "economic", + "573005b9947a6a140053cf6d": "A steep and steady decline", + "573005b9947a6a140053cf6e": "different democratic and anti-democratic Islamist movements", + "5acfea9277cf76001a68648a": "", + "5acfea9277cf76001a68648b": "", + "5acfea9277cf76001a68648c": "economic", + "5acfea9277cf76001a68648d": "", + "5acfea9277cf76001a68648e": "popularity and credibility of secular, socialist and nationalist politics", + "5730088e947a6a140053cfac": "Ali Shariati", + "5730088e947a6a140053cfad": "ideological", + "5730088e947a6a140053cfae": "somewhere between beliefs of Sunni Islamic thinkers", + "5730088e947a6a140053cfaf": "Prophet Mohammad", + "5730088e947a6a140053cfb0": "conspiracy against Islam", + "5acfeae177cf76001a68649e": "", + "5acfeae177cf76001a68649f": "", + "5acfeae177cf76001a6864a0": "", + "5acfeae177cf76001a6864a1": "", + "57300e2604bcaa1900d770b7": "The Islamic Republic", + "57300e2604bcaa1900d770b8": "economic", + "57300e2604bcaa1900d770b9": "Shia terrorist groups", + "57300e2604bcaa1900d770ba": "2006 Israel-Lebanon conflict", + "57300e2604bcaa1900d770bb": "President Mahmoud Ahmadinejad", + "5acfeb2577cf76001a6864b0": "", + "5acfeb2577cf76001a6864b1": "", + "5acfeb2577cf76001a6864b2": "", + "5acfeb2577cf76001a6864b3": "", + "5acfeb2577cf76001a6864b4": "", + "57300ec0947a6a140053d004": "the Soviet Union", + "57300ec0947a6a140053d005": "Islamic rebellion", + "57300ec0947a6a140053d006": "send aid", + "57300ec0947a6a140053d007": "marginal", + "57300ec0947a6a140053d008": "16,000 to 35,000", + "5acfeb5f77cf76001a6864ba": "", + "5acfeb5f77cf76001a6864bb": "Islamic rebellion", + "5acfeb5f77cf76001a6864bc": "", + "5acfeb5f77cf76001a6864bd": "marginal", + "5acfeb5f77cf76001a6864be": "", + "57300f8504bcaa1900d770d1": "put an end to Saddam Hussein's occupation of Kuwait", + "57300f8504bcaa1900d770d2": "Saddam Hussein", + "57300f8504bcaa1900d770d3": "Islamist groups", + "57300f8504bcaa1900d770d4": "Saudi", + "57300f8504bcaa1900d770d5": "the west", + "5acfeba077cf76001a6864c4": "radicalize the Islamist movement", + "5acfeba077cf76001a6864c5": "", + "5acfeba077cf76001a6864c6": "", + "5acfeba077cf76001a6864c7": "", + "5acfeba077cf76001a6864c8": "", + "573010fab2c2fd14005687d7": "conservative Muslims", + "573010fab2c2fd14005687d8": "the kingdom", + "573010fab2c2fd14005687d9": "prestige", + "573010fab2c2fd14005687da": "Algeria", + "573010fab2c2fd14005687db": "Osama bin Laden", + "5acfebe477cf76001a6864d6": "", + "5acfebe477cf76001a6864d7": "the kingdom", + "5acfebe477cf76001a6864d8": "", + "5acfebe477cf76001a6864d9": "", + "5acfebe477cf76001a6864da": "", + "573011de04bcaa1900d770f9": "Qutb's", + "573011de04bcaa1900d770fa": "1966", + "573011de04bcaa1900d770fb": "the Brotherhood", + "573011de04bcaa1900d770fc": "Fringe or splinter movements", + "573011de04bcaa1900d770fd": "1970s", + "5acfec2077cf76001a6864f2": "", + "5acfec2077cf76001a6864f3": "", + "5acfec2077cf76001a6864f4": "", + "5acfec2077cf76001a6864f5": "", + "5acfec2077cf76001a6864f6": "", + "5730126ba23a5019007fcd09": "Egyptian Islamic Jihad organization", + "5730126ba23a5019007fcd0a": "1981", + "5730126ba23a5019007fcd0b": "\"apostate\" leaders of Muslim states", + "5730126ba23a5019007fcd0c": "apostate", + "5730126ba23a5019007fcd0d": "Muhammad Abd al-Salaam Farag", + "5acfec5577cf76001a6864fc": "", + "5acfec5577cf76001a6864fd": "", + "5acfec5577cf76001a6864fe": "", + "5acfec5577cf76001a6864ff": "", + "5acfec5577cf76001a686500": "", + "5730131c947a6a140053d052": "violence", + "5730131c947a6a140053d053": "al-Gama'a al-Islamiyya", + "5730131c947a6a140053d054": "unsuccessful", + "5730131c947a6a140053d055": "2003", + "5730131c947a6a140053d056": "political figures", + "5acfec9277cf76001a686506": "", + "5acfec9277cf76001a686507": "", + "5acfec9277cf76001a686508": "unsuccessful", + "5acfec9277cf76001a686509": "", + "5acfec9277cf76001a68650a": "", + "5730208fa23a5019007fcded": "quiescent", + "5730208fa23a5019007fcdee": "HAMAS", + "5730208fa23a5019007fcdef": "destruction of Israel and the establishment of an Islamic state in Palestine", + "5730208fa23a5019007fcdf0": "Palestine", + "5730208fa23a5019007fcdf1": "alcohol", + "5acfecc577cf76001a686510": "", + "5acfecc577cf76001a686511": "", + "5acfecc577cf76001a686512": "destruction of Israel and the establishment of an Islamic state in Palestine", + "5acfecc577cf76001a686513": "", + "5acfecc577cf76001a686514": "alcohol", + "573020f7b2c2fd14005688f7": "Hamas", + "573020f7b2c2fd14005688f8": "542", + "573020f7b2c2fd14005688f9": "the majority of the seats", + "573020f7b2c2fd14005688fa": "2007", + "573020f7b2c2fd14005688fb": "driving Israel out of the Gaza Strip", + "5acfed0b77cf76001a686524": "", + "5acfed0b77cf76001a686525": "", + "5acfed0b77cf76001a686526": "", + "5acfed0b77cf76001a686527": "2007", + "5acfed0b77cf76001a686528": "", + "57302700a23a5019007fce89": "Islamist", + "57302700a23a5019007fce8a": "Hassan al-Turabi", + "57302700a23a5019007fce8b": "National Islamic Front", + "57302700a23a5019007fce8c": "with money from foreign Islamist banking systems", + "57302700a23a5019007fce8d": "university and military academy", + "5acfed5277cf76001a68652e": "Islamist", + "5acfed5277cf76001a68652f": "", + "5acfed5277cf76001a686530": "", + "5acfed5277cf76001a686531": "university and military academy", + "573027d6a23a5019007fce9d": "1985", + "573027d6a23a5019007fce9e": "", + "573027d6a23a5019007fce9f": "sharia law, torture and mass imprisonment of the opposition", + "573027d6a23a5019007fcea0": "Osama bin Laden", + "573027d6a23a5019007fcea1": "American attack on Iraq", + "5acfed9477cf76001a686540": "", + "5acfed9477cf76001a686541": "", + "5acfed9477cf76001a686542": "", + "5acfed9477cf76001a686543": "", + "5730285a04bcaa1900d7726d": "Front Islamique de Salut (the Islamic Salvation Front", + "5730285a04bcaa1900d7726e": "Algeria", + "5730285a04bcaa1900d7726f": "1989", + "5730285a04bcaa1900d77270": "alleviate the high rate of unemployment", + "5730285a04bcaa1900d77271": "a military coup d'\u00e9tat", + "5acfedc577cf76001a686548": "Front Islamique de Salut (the Islamic Salvation Front", + "5acfedc577cf76001a686549": "", + "5acfedc577cf76001a68654a": "1989", + "5acfedc577cf76001a68654b": "", + "5acfedc577cf76001a68654c": "", + "573028fa04bcaa1900d77287": "justice and prosperity", + "573028fa04bcaa1900d77288": "vicious and destructive", + "573028fa04bcaa1900d77289": "", + "573028fa04bcaa1900d7728a": "1992", + "573028fa04bcaa1900d7728b": "80%", + "5acfee0a77cf76001a686552": "justice and prosperity", + "5acfee0a77cf76001a686553": "", + "5acfee0a77cf76001a686554": "", + "5acfee0a77cf76001a686555": "", + "5acfee0a77cf76001a686556": "", + "57302a3aa23a5019007fcecf": "The Taliban were spawned by the thousands of madrasahs the Deobandi movement", + "57302a3aa23a5019007fced0": "Pakistan", + "57302a3aa23a5019007fced1": "Islamic fundamentalist or neofundamentalist", + "57302a3aa23a5019007fced2": "", + "57302a3aa23a5019007fced3": "Wahhabism", + "5acfee4777cf76001a68655c": "The Taliban were spawned by the thousands of madrasahs the Deobandi movement", + "5acfee4777cf76001a68655d": "", + "5acfee4777cf76001a68655e": "Islamic fundamentalist or neofundamentalist", + "5acfee4777cf76001a68655f": "", + "5acfee4777cf76001a686560": "", + "57302ad804bcaa1900d772af": "July 1977", + "57302ad804bcaa1900d772b0": "alcohol and nightclubs", + "57302ad804bcaa1900d772b1": "Islamism", + "57302ad804bcaa1900d772b2": "his means of seizing power", + "57302ad804bcaa1900d772b3": "1988", + "5acfee8977cf76001a686566": "", + "5acfee8977cf76001a686567": "alcohol and nightclubs", + "5acfee8977cf76001a686568": "", + "5acfee8977cf76001a686569": "his means of seizing power", + "5acfee8977cf76001a68656a": "", + "57302bd0b2c2fd14005689db": "Wahhabi/Salafi jihadist extremist militant group", + "57302bd0b2c2fd14005689dc": "Sunni Arabs", + "57302bd0b2c2fd14005689dd": "a caliphate", + "57302bd0b2c2fd14005689de": "ten million", + "57302bd0b2c2fd14005689df": "international recognition", + "5acfeee177cf76001a686570": "", + "5acfeee177cf76001a686571": "", + "5acfeee177cf76001a686572": "", + "5acfeee177cf76001a686573": "", + "5acfeee177cf76001a686574": "", + "57302cd004bcaa1900d772d7": "2004", + "57302cd004bcaa1900d772d8": "March 2003", + "57302cd004bcaa1900d772d9": "March 2011", + "57302cd004bcaa1900d772da": "", + "57302cd004bcaa1900d772db": "", + "5acfef1b77cf76001a68657a": "", + "5acfef1b77cf76001a68657b": "", + "5acfef1b77cf76001a68657c": "", + "5acfef1b77cf76001a68657d": "", + "57302e45947a6a140053d22e": "focus on the Caliphate", + "57302e45947a6a140053d22f": "7th century", + "57302e45947a6a140053d230": "1924", + "57302e45947a6a140053d231": "the true Islamic system", + "57302e45947a6a140053d232": "", + "5acfef5477cf76001a686582": "focus on the Caliphate", + "5acfef5477cf76001a686583": "", + "5acfef5477cf76001a686584": "", + "5acfef5477cf76001a686585": "", + "5acfef5477cf76001a686586": "", + "57302efe04bcaa1900d772f5": "armed", + "57302efe04bcaa1900d772f6": "through \"ideological struggle", + "57302efe04bcaa1900d772f7": "Muslim", + "57302efe04bcaa1900d772f8": "Egypt", + "57302efe04bcaa1900d772f9": "terrorist groups", + "5acfef9577cf76001a6865a0": "", + "5acfef9577cf76001a6865a1": "through \"ideological struggle", + "5acfef9577cf76001a6865a2": "elites", + "5acfef9577cf76001a6865a3": "Egypt", + "5acfef9577cf76001a6865a4": "", + "57302faa04bcaa1900d77311": "over 900,000", + "57302faa04bcaa1900d77312": "strong Islamist", + "57302faa04bcaa1900d77313": "2007", + "57302faa04bcaa1900d77314": "Londonistan", + "57302faa04bcaa1900d77315": "incitement to terrorism", + "5acfefcc77cf76001a6865aa": "", + "5acfefcc77cf76001a6865ab": "", + "5acfefcc77cf76001a6865ac": "2007", + "5acfefcc77cf76001a6865ad": "", + "5acfefcc77cf76001a6865ae": "incitement to terrorism", + "57303048947a6a140053d254": "since 2001", + "57303048947a6a140053d255": "State Department", + "57303048947a6a140053d256": "Christian Whiton", + "57303048947a6a140053d257": "U.S. Defense Secretary", + "57303048947a6a140053d258": "undermining the communist ideology", + "5acff00c77cf76001a6865b4": "", + "5acff00c77cf76001a6865b5": "", + "5acff00c77cf76001a6865b6": "", + "5acff00c77cf76001a6865b7": "", + "5acff00c77cf76001a6865b8": "", + "573060b48ab72b1400f9c4c6": "Latin", + "573060b48ab72b1400f9c4c7": "a policy of extending a country's power and influence through colonization", + "573060b48ab72b1400f9c4c9": "Japanese", + "573060b48ab72b1400f9c4ca": "technologies and ideas", + "5acff36377cf76001a6865ee": "Latin", + "5acff36377cf76001a6865ef": "", + "5acff36377cf76001a6865f0": "19th and 20th centuries", + "5acff36377cf76001a6865f1": "", + "5acff36377cf76001a6865f2": "", + "573062662461fd1900a9cdf7": "influence", + "573062662461fd1900a9cdf8": "Formal", + "573062662461fd1900a9cdfa": "diplomacy or military force", + "573062662461fd1900a9cdfb": "direct", + "5acff3b377cf76001a6865f8": "", + "5acff3b377cf76001a6865f9": "", + "5acff3b377cf76001a6865fa": "", + "5acff3b377cf76001a6865fb": "diplomacy or military force", + "5acff3b377cf76001a6865fc": "powerful form", + "57306797396df919000960ee": "", + "57306797396df919000960ef": "informal", + "57306797396df919000960f0": "aggressiveness", + "57306797396df919000960f1": "Informal rule", + "57306797396df919000960f2": "technological superiority", + "5acff4b177cf76001a686614": "", + "5acff4b177cf76001a686615": "", + "5acff4b177cf76001a686616": "", + "5acff4b177cf76001a686617": "Informal rule", + "5acff4b177cf76001a686618": "", + "573081c2069b531400832133": "", + "573081c2069b531400832134": "", + "573081c2069b531400832135": "Lenin", + "573081c2069b531400832136": "", + "573081c2069b531400832137": "sea and trade routes", + "5acff55577cf76001a68661e": "", + "5acff55577cf76001a68661f": "", + "5acff55577cf76001a686620": "", + "5acff55577cf76001a686621": "", + "5acff55577cf76001a686622": "", + "573083dc2461fd1900a9ce6d": "colonialism", + "573083dc2461fd1900a9ce6e": "political focus", + "573083dc2461fd1900a9ce6f": "", + "573083dc2461fd1900a9ce70": "Ottoman", + "573083dc2461fd1900a9ce71": "a person or group of people", + "5acff5b077cf76001a686628": "colonialism", + "5acff5b077cf76001a686629": "one's superiority, domination and influence upon a person or group of people", + "5acff5b077cf76001a68662a": "", + "5acff5b077cf76001a68662b": "Ottoman", + "5acff5b077cf76001a68662c": "", + "573085ea8ab72b1400f9c54c": "Imperialism", + "573085ea8ab72b1400f9c54d": "taking physical control of another", + "573085ea8ab72b1400f9c54e": "by conquering the other state's lands and therefore increasing its own dominance", + "573085ea8ab72b1400f9c54f": "", + "573085ea8ab72b1400f9c550": "the exploitation of the valuable assets and supplies of the nation that was conquered and the conquering nation then gaining the benefits from the spoils of the war", + "5acff63377cf76001a68665a": "", + "5acff63377cf76001a68665b": "", + "5acff63377cf76001a68665c": "", + "5acff63377cf76001a68665d": "", + "5acff63377cf76001a68665e": "", + "5730876a396df9190009617a": "defense and justification of empire-building", + "5730876a396df9190009617b": "races of highest 'social efficiency", + "5730876a396df9190009617c": "imperialism", + "5730876a396df9190009617d": "Social Darwinism", + "5730876a396df9190009617e": "whiteness", + "5acff69e77cf76001a686664": "", + "5acff69e77cf76001a686665": "", + "5acff69e77cf76001a686666": "", + "5acff69e77cf76001a686667": "", + "5acff69e77cf76001a686668": "whiteness", + "573088da069b53140083216b": "Germany", + "573088da069b53140083216c": "Britain", + "573088da069b53140083216d": "Political", + "573088da069b53140083216e": "expansion was necessary for a state\u2019s survival", + "573088da069b53140083216f": "able to fund travelers who would come back with tales of their discoveries", + "5acff6ea77cf76001a686680": "Germany", + "5acff6ea77cf76001a686681": "Britain", + "5acff6ea77cf76001a686682": "", + "5acff6ea77cf76001a686683": "", + "5acff6ea77cf76001a686684": "", + "57308cf88ab72b1400f9c576": "environmental determinism", + "57308cf88ab72b1400f9c577": "tropical", + "57308cf88ab72b1400f9c578": "Orientalism", + "57308cf88ab72b1400f9c579": "uncivilized people", + "57308cf88ab72b1400f9c57a": "", + "5acff73377cf76001a68668a": "", + "5acff73377cf76001a68668b": "", + "5acff73377cf76001a68668c": "Orientalism", + "5acff73377cf76001a68668d": "", + "5acff73377cf76001a68668e": "", + "57308ddc396df919000961a4": "British Empire", + "57308ddc396df919000961a5": "Roman law", + "57308ddc396df919000961a6": "Aboriginal", + "57308ddc396df919000961a7": "eighteenth century", + "57308ddc396df919000961a8": "empty land", + "5ad02ab477cf76001a686c68": "", + "5ad02ab477cf76001a686c69": "", + "5ad02ab477cf76001a686c6a": "", + "5ad02ab477cf76001a686c6b": "", + "5ad02ab477cf76001a686c6c": "", + "57308f6b8ab72b1400f9c580": "imaginative geography", + "57308f6b8ab72b1400f9c581": "", + "57308f6b8ab72b1400f9c582": "", + "57308f6b8ab72b1400f9c583": "", + "57308f6b8ab72b1400f9c584": "inferior", + "5ad02aff77cf76001a686c7c": "", + "5ad02aff77cf76001a686c7d": "", + "5ad02aff77cf76001a686c7e": "", + "5ad02aff77cf76001a686c7f": "", + "5ad02aff77cf76001a686c80": "", + "5730909d8ab72b1400f9c58a": "analysis of the role of nineteenth-century maps", + "5730909d8ab72b1400f9c58b": "", + "5730909d8ab72b1400f9c58c": "unknown or unexplored territory", + "5730909d8ab72b1400f9c58d": "", + "5730909d8ab72b1400f9c58e": "French", + "5ad02be477cf76001a686c9a": "", + "5ad02be477cf76001a686c9b": "", + "5ad02be477cf76001a686c9c": "", + "5ad02be477cf76001a686c9d": "", + "573092088ab72b1400f9c594": "Genghis Khan", + "573092088ab72b1400f9c595": "pre-Columbian era", + "573092088ab72b1400f9c596": "Sub-Saharan Africa", + "573092088ab72b1400f9c597": "dozens", + "573092088ab72b1400f9c598": "", + "5ad02cf577cf76001a686cd8": "", + "5ad02cf577cf76001a686cd9": "", + "5ad02cf577cf76001a686cda": "", + "5ad02cf577cf76001a686cdb": "", + "5ad02cf577cf76001a686cdc": "", + "573093598ab72b1400f9c5ae": "Cultural imperialism", + "573093598ab72b1400f9c5af": "its soft power", + "573093598ab72b1400f9c5b0": "Dallas", + "573093598ab72b1400f9c5b1": "Roman", + "573093598ab72b1400f9c5b2": "bans on foreign popular culture, control of the internet and unauthorised satellite dishes", + "5ad02d3077cf76001a686cf6": "", + "5ad02d3077cf76001a686cf7": "", + "5ad02d3077cf76001a686cf8": "", + "5ad02d3077cf76001a686cf9": "", + "5ad02d3077cf76001a686cfa": "", + "57309446396df919000961b8": "around 1700", + "57309446396df919000961b9": "", + "57309446396df919000961ba": "thousands", + "57309446396df919000961bb": "", + "57309446396df919000961bc": "Open Door Policy", + "5ad02de177cf76001a686d14": "", + "5ad02de177cf76001a686d15": "", + "5ad02de177cf76001a686d16": "", + "5ad02de177cf76001a686d17": "around 1700", + "5ad02de177cf76001a686d18": "", + "57309564069b5314008321a5": "1919", + "57309564069b5314008321a6": "1999", + "57309564069b5314008321a7": "historians", + "57309564069b5314008321a8": "the world's economy", + "57309564069b5314008321a9": "many imperial powers", + "5ad02e3377cf76001a686d32": "", + "5ad02e3377cf76001a686d33": "", + "5ad02e3377cf76001a686d34": "", + "5ad02e3377cf76001a686d35": "", + "573098f38ab72b1400f9c5d2": "economic growth", + "573098f38ab72b1400f9c5d3": "colonies", + "573098f38ab72b1400f9c5d4": "mid-18th century", + "573098f38ab72b1400f9c5d5": "political weakness of the Mughal state", + "5ad02e8277cf76001a686d4e": "", + "5ad02e8277cf76001a686d4f": "", + "5ad02e8277cf76001a686d50": "", + "5ad02e8277cf76001a686d51": "", + "5ad02e8277cf76001a686d52": "", + "573099ee8ab72b1400f9c5dc": "advancements in communication", + "573099ee8ab72b1400f9c5dd": "deadly explosives", + "573099ee8ab72b1400f9c5de": "", + "573099ee8ab72b1400f9c5df": "arrows, swords, and leather shields", + "573099ee8ab72b1400f9c5e0": "Europe", + "5ad02ef677cf76001a686d68": "", + "5ad02ef677cf76001a686d69": "", + "5ad02ef677cf76001a686d6a": "", + "5ad02ef677cf76001a686d6b": "arrows, swords, and leather shields", + "5ad02ef677cf76001a686d6c": "", + "57309bfb8ab72b1400f9c5e6": "British", + "57309bfb8ab72b1400f9c5e7": "late 1870s", + "57309bfb8ab72b1400f9c5e8": "", + "57309bfb8ab72b1400f9c5e9": "", + "5ad02f5777cf76001a686d84": "", + "5ad02f5777cf76001a686d85": "", + "5ad02f5777cf76001a686d86": "", + "5ad02f5777cf76001a686d87": "", + "5ad02f5777cf76001a686d88": "late 19th century", + "57309ef18ab72b1400f9c600": "aristocracy", + "57309ef18ab72b1400f9c601": "before World War I", + "57309ef18ab72b1400f9c602": "1950s", + "57309ef18ab72b1400f9c603": "", + "57309ef18ab72b1400f9c604": "removing its economic foundation", + "5ad02fda77cf76001a686d8e": "", + "5ad02fda77cf76001a686d8f": "", + "5ad02fda77cf76001a686d90": "", + "5ad02fda77cf76001a686d91": "", + "5ad02fda77cf76001a686d92": "", + "5730a0778ab72b1400f9c60a": "environmental determinism", + "5730a0778ab72b1400f9c60b": "the environment in which they lived", + "5730a0778ab72b1400f9c60c": "less civilized", + "5730a0778ab72b1400f9c60d": "", + "5730a0778ab72b1400f9c60e": "orientalism and tropicality", + "5ad0301577cf76001a686db4": "", + "5ad0301577cf76001a686db5": "", + "5ad0301577cf76001a686db6": "", + "5ad0301577cf76001a686db7": "", + "5ad0301577cf76001a686db8": "orientalism and tropicality", + "5730a314069b5314008321eb": "geographic scholars", + "5730a314069b5314008321ec": "Northern Europe and the Mid-Atlantic", + "5730a314069b5314008321ed": "guidance and intervention", + "5730a314069b5314008321ee": "", + "5730a314069b5314008321ef": "", + "5ad0312677cf76001a686dc8": "", + "5ad0312677cf76001a686dc9": "", + "5ad0312677cf76001a686dca": "", + "5ad0312677cf76001a686dcb": "", + "5ad0312677cf76001a686dcc": "", + "5730a40f396df91900096234": "sixteenth century", + "5730a40f396df91900096235": "1599", + "5730a40f396df91900096236": "Queen Elizabeth", + "5730a40f396df91900096237": "bankruptcy", + "5730a40f396df91900096238": "Portuguese", + "5ad0316177cf76001a686dda": "", + "5ad0316177cf76001a686ddb": "", + "5ad0316177cf76001a686ddc": "", + "5ad0316177cf76001a686ddd": "bankruptcy", + "5ad0316177cf76001a686dde": "Portuguese", + "5730a4d02461fd1900a9cf29": "1830", + "5730a4d02461fd1900a9cf2a": "after 1850", + "5730a4d02461fd1900a9cf2b": "North and West Africa", + "5730a4d02461fd1900a9cf2c": "", + "5730a4d02461fd1900a9cf2d": "Catholicism", + "5ad031ef77cf76001a686df2": "", + "5ad031ef77cf76001a686df3": "after 1850", + "5ad031ef77cf76001a686df4": "", + "5ad031ef77cf76001a686df5": "", + "5ad031ef77cf76001a686df6": "", + "5730a951069b531400832213": "civilize the inferior", + "5730a951069b531400832214": "Full citizenship rights", + "5730a951069b531400832215": "France sent small numbers of settlers to its colonies", + "5730a951069b531400832216": "Christianity and French culture", + "5730a951069b531400832217": "", + "5ad0322877cf76001a686dfc": "civilize the inferior", + "5ad0322877cf76001a686dfd": "", + "5ad0322877cf76001a686dfe": "France sent small numbers of settlers to its colonies", + "5ad0322877cf76001a686dff": "", + "5730aa52069b53140083221d": "overseas colonies", + "5730aa52069b53140083221e": "anti-colonial movements", + "5730aa52069b53140083221f": "Vietnam", + "5730aa52069b531400832220": "Vietnam", + "5730aa52069b531400832221": "1960", + "5ad032b377cf76001a686e0c": "", + "5ad032b377cf76001a686e0d": "", + "5ad032b377cf76001a686e0e": "", + "5ad032b377cf76001a686e0f": "", + "5ad032b377cf76001a686e10": "", + "5730ab63396df91900096260": "Scandinavia and northern Europe", + "5730ab63396df91900096261": "middle period of classical antiquity", + "5730ab63396df91900096262": "late antiquity", + "5730ab63396df91900096263": "Muslim Iberia", + "5730ab63396df91900096264": "central Europe", + "5ad0354e77cf76001a686e1e": "", + "5ad0354e77cf76001a686e1f": "", + "5ad0354e77cf76001a686e20": "", + "5ad0354e77cf76001a686e21": "", + "5730ac782461fd1900a9cf73": "late 19th century", + "5730ac782461fd1900a9cf74": "1862", + "5730ac782461fd1900a9cf75": "after the Franco-German War", + "5730ac782461fd1900a9cf76": "Europe itself", + "5730ac782461fd1900a9cf77": "the defeat of Napoleon", + "5ad035bd77cf76001a686e26": "late 19th century", + "5ad035bd77cf76001a686e27": "1862\u201390", + "5ad035bd77cf76001a686e28": "", + "5ad035bd77cf76001a686e29": "", + "5ad035bd77cf76001a686e2a": "", + "5730aef38ab72b1400f9c682": "South Pacific", + "5730aef38ab72b1400f9c683": "German prestige", + "5730aef38ab72b1400f9c684": "German New Guinea", + "5730aef38ab72b1400f9c685": "1884", + "5730aef38ab72b1400f9c686": "Hamburg merchants and traders", + "5ad0383677cf76001a686e38": "", + "5ad0383677cf76001a686e39": "", + "5ad0383677cf76001a686e3a": "German New Guinea", + "5ad0383677cf76001a686e3b": "", + "5730b1022461fd1900a9cfa3": "1894", + "5730b1022461fd1900a9cfa4": "Japan took part of Sakhalin Island from Russia", + "5730b1022461fd1900a9cfa5": "Manchuria", + "5730b1022461fd1900a9cfa6": "Thailand", + "5ad0388377cf76001a686e40": "1937", + "5ad0388377cf76001a686e41": "", + "5ad0388377cf76001a686e42": "Manchuria", + "5ad0388377cf76001a686e43": "", + "5730b255396df919000962b0": "People\u2019s Republic of China", + "5730b255396df919000962b1": "1932", + "5730b255396df919000962b2": "Lenin", + "5730b255396df919000962b3": "Eastern Europe", + "5730b255396df919000962b4": "Bolshevik leaders", + "5ad0391f77cf76001a686e48": "", + "5ad0391f77cf76001a686e49": "1923", + "5ad0391f77cf76001a686e4a": "", + "5730b4282461fd1900a9cfc5": "as part of a world revolution", + "5730b4282461fd1900a9cfc6": "Lenin", + "5730b4282461fd1900a9cfc7": "socialism in one country", + "5730b4282461fd1900a9cfc8": "Nikita Khrushchev", + "5730b4282461fd1900a9cfc9": "Mao Zedong", + "5ad039ec77cf76001a686e66": "", + "5ad039ec77cf76001a686e67": "", + "5ad039ec77cf76001a686e68": "", + "5730b541396df919000962c2": "mercantilism", + "5730b541396df919000962c3": "1776", + "5730b541396df919000962c4": "1820", + "5730b541396df919000962c5": "free trade", + "5730b541396df919000962c6": "1815", + "5ad03a1a77cf76001a686e6c": "", + "5ad03a1a77cf76001a686e6d": "1776", + "5ad03a1a77cf76001a686e6e": "1820", + "5ad03a1a77cf76001a686e6f": "free trade", + "5730b6592461fd1900a9cfcf": "British Empire", + "5730b6592461fd1900a9cfd0": "pseudo-sciences", + "5730b6592461fd1900a9cfd1": "Middle East", + "5730b6592461fd1900a9cfd2": "spokesmen", + "5ad03a3e77cf76001a686e74": "", + "5ad03a3e77cf76001a686e75": "pseudo-sciences", + "5ad03a3e77cf76001a686e76": "Middle East", + "5730b7ce069b5314008322c3": "", + "5730b7ce069b5314008322c4": "interventionism in Central America", + "5730b7ce069b5314008322c5": "", + "5730b7ce069b5314008322c6": "", + "5730b7ce069b5314008322c7": "racket", + "5ad03a6b77cf76001a686e7a": "", + "5ad03a6b77cf76001a686e7b": "", + "5ad03a6b77cf76001a686e7c": "", + "5ad03a6b77cf76001a686e7d": "", + "5730b8ca8ab72b1400f9c704": "Isiah Bowman", + "5730b8ca8ab72b1400f9c705": "1917", + "5730b8ca8ab72b1400f9c706": "President Wilson and the American delegation", + "5730b8ca8ab72b1400f9c707": "to build a premise that would allow for U.S authorship of a 'new world'", + "5730b8ca8ab72b1400f9c708": "", + "5ad03a8a77cf76001a686e82": "", + "5ad03a8a77cf76001a686e83": "", + "5ad03a8a77cf76001a686e84": "", + "5730bb522461fd1900a9d011": "internal strife", + "5730bb522461fd1900a9d012": "internal colonialism", + "5730bb522461fd1900a9d013": "12 to 15 million", + "5730bb522461fd1900a9d015": "the contemporary Orient", + "5ad03b0b77cf76001a686e90": "", + "5ad03b0b77cf76001a686e91": "", + "5ad03b0b77cf76001a686e92": "", + "5ad03b0b77cf76001a686e93": "", + "5730bc308ab72b1400f9c73c": "1923", + "5730bc308ab72b1400f9c73d": "Suleiman the Magnificent", + "5730bc308ab72b1400f9c73e": "32", + "5730bc308ab72b1400f9c73f": "the Horn of Africa", + "5730bc308ab72b1400f9c740": "During the 16th and 17th centuries", + "5ad03b4677cf76001a686ea2": "1299 to 1923", + "5ad03b4677cf76001a686ea3": "", + "5ad03b4677cf76001a686ea4": "", + "5ad03b4677cf76001a686ea5": "the Horn of Africa", + "5730bd00069b5314008322d7": "Istanbul", + "5730bd00069b5314008322d9": "Germany", + "5730bd00069b5314008322da": "Turkey", + "5730bd00069b5314008322db": "creation of modern Balkan and Middle Eastern states", + "5ad03b7977cf76001a686eaa": "", + "5ad03b7977cf76001a686eab": "Istanbul", + "5ad03b7977cf76001a686eac": "Germany", + "5ad03b7977cf76001a686ead": "Turkey", + "5ad03b7977cf76001a686eae": "", + "5732b6b5328d981900602021": "Warsaw", + "5732b6b5328d981900602022": "Vistula River", + "5732b6b5328d981900602023": "260 kilometres (160 mi)", + "5732b6b5328d981900602024": "2.666 million", + "5732b6b5328d981900602025": "9th", + "5ad4bbbb5b96ef001a109e88": "Warszawa", + "5ad4bbbb5b96ef001a109e89": "", + "5ad4bbbb5b96ef001a109e8a": "", + "5ad4bbbb5b96ef001a109e8b": "", + "5ad4bbbb5b96ef001a109e8c": "9th", + "573312fcd058e614000b56e6": "the Economist Intelligence Unit", + "573312fcd058e614000b56e7": "2012", + "573312fcd058e614000b56e8": "FMCG manufacturing, metal processing, steel and electronic manufacturing and food processing", + "573312fcd058e614000b56e9": "Warsaw Stock Exchange", + "573312fcd058e614000b56ea": "Frontex", + "5ad4bcc45b96ef001a109e9c": "", + "5ad4bcc45b96ef001a109e9d": "manufacturing, metal processing, steel and electronic manufacturing and food processing", + "5ad4bcc45b96ef001a109e9e": "Warsaw Stock Exchange", + "5ad4bcc45b96ef001a109e9f": "", + "5ad4bcc45b96ef001a109ea0": "Frontex", + "5733140a4776f419006606e0": "1313", + "5733140a4776f419006606e1": "Krak\u00f3w", + "5733140a4776f419006606e2": "1596", + "5733140a4776f419006606e3": "King Sigismund III Vasa", + "5733140a4776f419006606e4": "it has survived many wars, conflicts and invasions throughout its long history", + "5ad4bdbd5b96ef001a109ed8": "", + "5ad4bdbd5b96ef001a109ed9": "", + "5ad4bdbd5b96ef001a109eda": "1795", + "5ad4bdbd5b96ef001a109edb": "King Sigismund III Vasa", + "5ad4bdbd5b96ef001a109edc": "", + "573314e3d058e614000b56f0": "Roman Catholic", + "573314e3d058e614000b56f1": "Polish Academy of Sciences", + "573314e3d058e614000b56f2": "UNESCO World Heritage Site", + "573314e3d058e614000b56f3": "architectural attractions", + "573314e3d058e614000b56f4": "luxurious parks and royal gardens", + "5ad510be5b96ef001a10ab56": "", + "5ad510be5b96ef001a10ab57": "", + "5ad510be5b96ef001a10ab58": "", + "5ad510be5b96ef001a10ab59": "Polish Academy of Sciences", + "5ad510be5b96ef001a10ab5a": "", + "57332442d058e614000b5720": "Warszawa", + "57332442d058e614000b5721": "belonging to Warsz", + "57332442d058e614000b5722": "a 12th/13th-century nobleman", + "57332442d058e614000b5723": "a village located at the modern-day site of Mariensztat neighbourhood", + "57332442d058e614000b5724": "miasto sto\u0142eczne Warszawa", + "5ad50bb95b96ef001a10aaae": "Warszawa", + "5ad50bb95b96ef001a10aaaf": "", + "5ad50bb95b96ef001a10aab0": "", + "5ad50bb95b96ef001a10aab1": "", + "5ad50bb95b96ef001a10aab2": "sto\u0142eczne Warszawa", + "57332562d058e614000b5730": "Jazd\u00f3w", + "57332562d058e614000b5731": "The Prince of P\u0142ock", + "57332562d058e614000b5732": "1300", + "57332562d058e614000b5733": "1413", + "57332562d058e614000b5734": "1526", + "5ad4bea25b96ef001a109ef6": "The Prince of P\u0142ock", + "5ad4bea25b96ef001a109ef7": "1300", + "5ad4bea25b96ef001a109ef8": "Jazd\u00f3w", + "5ad4bea25b96ef001a109ef9": "1413", + "5ad4bea25b96ef001a109efa": "1526", + "5733266d4776f41900660712": "General Sejm", + "5733266d4776f41900660713": "1569", + "5733266d4776f41900660714": "religious freedom", + "5733266d4776f41900660715": "its central location between the Commonwealth's capitals of Krak\u00f3w and Vilnius", + "5733266d4776f41900660716": "1596", + "5ad4c99d5b96ef001a10a0a3": "", + "5ad4c99d5b96ef001a10a0a4": "", + "5ad4c99d5b96ef001a10a0a5": "", + "5ad4c99d5b96ef001a10a0a6": "", + "57332a734776f41900660726": "until 1796", + "57332a734776f41900660727": "Kingdom of Prussia", + "57332a734776f41900660728": "Napoleon's army", + "57332a734776f41900660729": "Following the Congress of Vienna of 1815", + "57332a734776f4190066072a": "1816", + "5ad4ca605b96ef001a10a0ca": "Kingdom of Prussia", + "5ad4ca605b96ef001a10a0cb": "Napoleon's army", + "5ad4ca605b96ef001a10a0cc": "", + "5ad4ca605b96ef001a10a0cd": "", + "5ad4ca605b96ef001a10a0ce": "until 1796", + "57332b66d058e614000b5758": "4 August 1915 until November 1918", + "57332b66d058e614000b5759": "areas controlled by Russia", + "57332b66d058e614000b575a": "Pi\u0142sudski", + "57332b66d058e614000b575b": "1920", + "57332b66d058e614000b575c": "Red Army", + "5ad4caf45b96ef001a10a0d4": "", + "5ad4caf45b96ef001a10a0d5": "", + "5ad4caf45b96ef001a10a0d6": "Pi\u0142sudski", + "5ad4caf45b96ef001a10a0d7": "", + "5ad4caf45b96ef001a10a0d8": "", + "57332c1e4776f4190066073a": "1 September 1939", + "57332c1e4776f4190066073b": "", + "57332c1e4776f4190066073c": "several hundred thousand", + "57332c1e4776f4190066073d": "19 April 1943", + "57332c1e4776f4190066073e": "almost a month", + "5ad50c9f5b96ef001a10aae0": "", + "5ad50c9f5b96ef001a10aae1": "", + "5ad50c9f5b96ef001a10aae2": "", + "5ad50c9f5b96ef001a10aae3": "", + "5ad50c9f5b96ef001a10aae4": "almost a month", + "57332e48d058e614000b5762": "the Red Army", + "57332e48d058e614000b5763": "Stalin was hostile to the idea of an independent Poland", + "57332e48d058e614000b5764": "1 August 1944", + "57332e48d058e614000b5765": "63", + "57332e48d058e614000b5766": "between 150,000 and 200,000", + "5ad4cc135b96ef001a10a0f2": "", + "5ad4cc135b96ef001a10a0f3": "Stalin was hostile to the idea of an independent Poland", + "5ad4cc135b96ef001a10a0f4": "1 August 1944", + "5ad4cc135b96ef001a10a0f5": "63", + "5ad4cc135b96ef001a10a0f6": "between 150,000 and 200,000", + "57332f81d058e614000b5776": "Bricks for Warsaw", + "57332f81d058e614000b5777": "prefabricated", + "57332f81d058e614000b5778": "", + "57332f81d058e614000b5779": "Palace of Culture and Science", + "57332f81d058e614000b577a": "UNESCO's World Heritage list", + "5ad4cd6e5b96ef001a10a124": "", + "5ad4cd6e5b96ef001a10a125": "prefabricated", + "5ad4cd6e5b96ef001a10a126": "", + "5ad4cd6e5b96ef001a10a127": "", + "5ad4cd6e5b96ef001a10a128": "", + "573330444776f41900660758": "", + "573330444776f41900660759": "anti-communist fervor", + "573330444776f4190066075a": "less than a year", + "573330444776f4190066075b": "Victory Square", + "573330444776f4190066075c": "the incentive for the democratic changes", + "5ad4d0ca5b96ef001a10a196": "", + "5ad4d0ca5b96ef001a10a197": "", + "5ad4d0ca5b96ef001a10a198": "", + "5ad4d0ca5b96ef001a10a199": "", + "5ad4d0ca5b96ef001a10a19a": "", + "5733314e4776f4190066076a": "300", + "5733314e4776f4190066076b": "325", + "5733314e4776f4190066076c": "Vistula River", + "5733314e4776f4190066076d": "115.7 metres", + "5733314e4776f4190066076e": "at the right bank of the Vistula", + "5ad4d1785b96ef001a10a1b2": "300", + "5ad4d1785b96ef001a10a1b3": "325", + "5ad4d1785b96ef001a10a1b4": "Vistula River", + "5ad4d1785b96ef001a10a1b5": "115.7 metres (379.6 ft)", + "5ad4d1785b96ef001a10a1b6": "at the right bank of the Vistula", + "57335c20d058e614000b58f9": "two", + "57335c20d058e614000b58fa": "Vistula Valley", + "57335c20d058e614000b58fb": "The Vistula River", + "57335c20d058e614000b58fc": "moraine plateau", + "57335c20d058e614000b58fd": "Warsaw Escarpment", + "5ad4d2855b96ef001a10a1da": "Vistula Valley", + "5ad4d2855b96ef001a10a1db": "two", + "5ad4d2855b96ef001a10a1dc": "The Vistula River", + "5ad4d2855b96ef001a10a1dd": "", + "5ad4d2855b96ef001a10a1de": "moraine plateau", + "57335ddbd058e614000b592f": "plain moraine plateau", + "57335ddbd058e614000b5930": "former flooded terraces", + "57335ddbd058e614000b5931": "valleys and ground depressions", + "57335ddbd058e614000b5932": "the highest terrace", + "57335ddbd058e614000b5933": "pine forest", + "5ad50de85b96ef001a10ab12": "pine forest", + "5ad50de85b96ef001a10ab13": "", + "5ad50de85b96ef001a10ab14": "", + "5ad50de85b96ef001a10ab15": "plain moraine plateau", + "5ad50de85b96ef001a10ab16": "former flooded terraces", + "57335fcad058e614000b5970": "the turbulent history of the city and country", + "57335fcad058e614000b5971": "Second World War", + "57335fcad058e614000b5972": "After liberation", + "57335fcad058e614000b5973": "Leopold Kronenberg Palace", + "57335fcad058e614000b5974": "Eastern bloc countries", + "5ad4d55f5b96ef001a10a274": "After liberation", + "5ad4d55f5b96ef001a10a275": "the turbulent history of the city and country", + "5ad4d55f5b96ef001a10a276": "", + "5ad4d55f5b96ef001a10a277": "Second World War", + "5ad4d55f5b96ef001a10a278": "Eastern bloc countries", + "573361404776f4190066093c": "Gothic", + "573361404776f4190066093d": "14th century", + "573361404776f4190066093e": "Masovian gothic style", + "573361404776f4190066093f": "Renaissance", + "573361404776f41900660940": "mannerist architecture", + "5ad50f1c5b96ef001a10ab2e": "1562", + "5ad50f1c5b96ef001a10ab2f": "", + "5ad50f1c5b96ef001a10ab30": "Renaissance", + "5ad50f1c5b96ef001a10ab31": "", + "5ad50f1c5b96ef001a10ab32": "", + "573362b94776f41900660974": "17th century", + "573362b94776f41900660975": "1688\u20131692", + "573362b94776f41900660976": "", + "573362b94776f41900660977": "neoclassical architecture", + "573362b94776f41900660978": "1775\u20131795", + "5ad4d8d65b96ef001a10a362": "", + "5ad4d8d65b96ef001a10a363": "", + "5ad4d8d65b96ef001a10a364": "", + "5ad4d8d65b96ef001a10a365": "", + "5ad4d8d65b96ef001a10a366": "", + "5733638fd058e614000b59e8": "bourgeois", + "5733638fd058e614000b59e9": "", + "5733638fd058e614000b59ea": "socialist realism", + "5733638fd058e614000b59eb": "Warsaw University of Technology building", + "5733638fd058e614000b59ec": "the most distinctive buildings", + "5ad4d9be5b96ef001a10a3b0": "", + "5ad4d9be5b96ef001a10a3b1": "", + "5ad4d9be5b96ef001a10a3b2": "", + "5ad4d9be5b96ef001a10a3b3": "", + "5ad4d9be5b96ef001a10a3b4": "", + "5733647e4776f419006609ae": "Pawiak", + "5733647e4776f419006609af": "Pawiak", + "5733647e4776f419006609b0": "The Warsaw Citadel", + "5733647e4776f419006609b1": "children who served as messengers and frontline troops in the Warsaw Uprising", + "5733647e4776f419006609b2": "Warsaw Uprising Monument by Wincenty Ku\u0107ma", + "5ad4da795b96ef001a10a3e6": "", + "5ad4da795b96ef001a10a3e7": "Pawiak", + "5ad4da795b96ef001a10a3e8": "children who served as messengers and frontline troops in the Warsaw Uprising", + "5ad4da795b96ef001a10a3e9": "", + "5ad4da795b96ef001a10a3ea": "Warsaw Uprising Monument by Wincenty Ku\u0107ma", + "57336755d058e614000b5a3c": "", + "57336755d058e614000b5a3d": "100", + "57336755d058e614000b5a3e": "", + "57336755d058e614000b5a3f": "the Krasi\u0144ski Palace Garden", + "57336755d058e614000b5a40": "\u0141azienki Park", + "5ad4db9f5b96ef001a10a43e": "", + "5ad4db9f5b96ef001a10a43f": "", + "5ad4db9f5b96ef001a10a440": "", + "5ad4db9f5b96ef001a10a441": "", + "5ad4db9f5b96ef001a10a442": "east", + "573368044776f41900660a29": "green", + "573368044776f41900660a2a": "the New Orangery", + "573368044776f41900660a2b": "Pole Mokotowskie", + "573368044776f41900660a2c": "Park Ujazdowski", + "573368044776f41900660a2d": "1927", + "5ad4dc755b96ef001a10a46e": "", + "5ad4dc755b96ef001a10a46f": "", + "5ad4dc755b96ef001a10a470": "1927", + "5ad4dc755b96ef001a10a471": "green", + "5ad4dc755b96ef001a10a472": "the New Orangery", + "573368e54776f41900660a53": "the location of Warsaw within the border region of several big floral regions", + "573368e54776f41900660a54": "within the borders of Warsaw", + "573368e54776f41900660a55": "Masovian Primeval Forest", + "573368e54776f41900660a56": "Kabaty Forest", + "573368e54776f41900660a57": "two", + "5ad50fe55b96ef001a10ab4c": "two", + "5ad50fe55b96ef001a10ab4d": "Bielany Forest", + "5ad50fe55b96ef001a10ab4e": "the location of Warsaw", + "5ad50fe55b96ef001a10ab4f": "", + "5ad50fe55b96ef001a10ab50": "Kabaty Forest", + "57337ddc4776f41900660bba": "13", + "57337ddc4776f41900660bbb": "15 kilometres (9 miles)", + "57337ddc4776f41900660bbc": "otter, beaver and hundreds of bird species", + "57337ddc4776f41900660bbd": "13", + "57337ddc4776f41900660bbe": "to clean them of plants and sediments", + "5ad4dd325b96ef001a10a49e": "13", + "5ad4dd325b96ef001a10a49f": "15 kilometres", + "5ad4dd325b96ef001a10a4a0": "otter, beaver and hundreds of bird species", + "5ad4dd325b96ef001a10a4a1": "13", + "5ad4dd325b96ef001a10a4a2": "to clean them of plants and sediments", + "57337ea24776f41900660bd0": "foreign-born inhabitants", + "57337ea24776f41900660bd1": "Jewish", + "57337ea24776f41900660bd2": "34%", + "57337ea24776f41900660bd3": "833,500", + "57337ea24776f41900660bd4": "internal migration and urbanisation", + "5ad4f1365b96ef001a10a70c": "", + "5ad4f1365b96ef001a10a70d": "", + "5ad4f1365b96ef001a10a70e": "", + "5ad4f1365b96ef001a10a70f": "internal migration and urbanisation", + "5ad4f1365b96ef001a10a710": "34%", + "57337f6ad058e614000b5bcb": "c. 1,300,000", + "57337f6ad058e614000b5bcc": "420,000", + "57337f6ad058e614000b5bcd": "1951", + "57337f6ad058e614000b5bce": "better only because they lived in the capital", + "57337f6ad058e614000b5bcf": "residency registration", + "5ad4f1c95b96ef001a10a726": "c. 1,300,000", + "5ad4f1c95b96ef001a10a727": "420,000", + "5ad4f1c95b96ef001a10a728": "1951", + "5ad4f1c95b96ef001a10a729": "", + "5ad4f1c95b96ef001a10a72a": "", + "57338007d058e614000b5bda": "multi-cultural", + "57338007d058e614000b5bdb": "711,988", + "57338007d058e614000b5bdc": "56.2%", + "57338007d058e614000b5bdd": "2.8%", + "57338007d058e614000b5bde": "in the aftermath of the Warsaw Uprising of 1944", + "5ad4f28c5b96ef001a10a730": "", + "5ad4f28c5b96ef001a10a731": "", + "5ad4f28c5b96ef001a10a732": "56.2%", + "5ad4f28c5b96ef001a10a733": "2.8%", + "5ad4f28c5b96ef001a10a734": "in the aftermath of the Warsaw Uprising of 1944", + "573380e0d058e614000b5be9": "a commune", + "573380e0d058e614000b5bea": "counties or powiats", + "573380e0d058e614000b5beb": "Krak\u00f3w", + "5ad4f40c5b96ef001a10a774": "a commune", + "5ad4f40c5b96ef001a10a775": "counties or powiats", + "5ad4f40c5b96ef001a10a776": "", + "5ad4f40c5b96ef001a10a777": "", + "5ad4f40c5b96ef001a10a778": "Krak\u00f3w", + "57338160d058e614000b5bf9": "Warsaw City Council", + "57338160d058e614000b5bfa": "60", + "57338160d058e614000b5bfb": "every four years", + "57338160d058e614000b5bfc": "committees", + "57338160d058e614000b5bfd": "30", + "5ad4f4d95b96ef001a10a792": "Warsaw City Council", + "5ad4f4d95b96ef001a10a793": "60", + "5ad4f4d95b96ef001a10a794": "", + "5ad4f4d95b96ef001a10a795": "committees", + "5ad4f4d95b96ef001a10a796": "30", + "57338255d058e614000b5c0d": "President", + "57338255d058e614000b5c0e": "Jan Andrzej Menich", + "57338255d058e614000b5c0f": "1695\u20131696", + "57338255d058e614000b5c10": "the City council", + "57338255d058e614000b5c11": "Centrum", + "5ad4f5765b96ef001a10a7a6": "", + "5ad4f5765b96ef001a10a7a7": "Jan Andrzej Menich", + "5ad4f5765b96ef001a10a7a8": "1994\u20131999", + "5ad4f5765b96ef001a10a7a9": "the City council", + "5ad4f5765b96ef001a10a7aa": "", + "573382d24776f41900660c37": "\u015ar\u00f3dmie\u015bcie", + "573382d24776f41900660c38": "304,016", + "573382d24776f41900660c39": "emerging market", + "573382d24776f41900660c3a": "12%", + "573382d24776f41900660c3b": "191.766 billion PLN, 111696 PLN per capita", + "5ad4f63b5b96ef001a10a7c2": "", + "5ad4f63b5b96ef001a10a7c3": "304,016", + "5ad4f63b5b96ef001a10a7c4": "emerging market", + "5ad4f63b5b96ef001a10a7c5": "12%", + "5ad4f63b5b96ef001a10a7c6": "191.766 billion", + "5733834ed058e614000b5c26": "1817", + "5733834ed058e614000b5c27": "World War II", + "5733834ed058e614000b5c28": "World War II", + "5733834ed058e614000b5c29": "374", + "5733834ed058e614000b5c2a": "", + "5ad4f7235b96ef001a10a7dc": "", + "5ad4f7235b96ef001a10a7dd": "reintroduction of a free-market economy", + "5ad4f7235b96ef001a10a7de": "", + "5ad4f7235b96ef001a10a7df": "", + "5ad4f7235b96ef001a10a7e0": "", + "573383d0d058e614000b5c35": "1951", + "573383d0d058e614000b5c36": "", + "573383d0d058e614000b5c37": "Daewoo", + "573383d0d058e614000b5c38": "AvtoZAZ", + "573383d0d058e614000b5c39": "The license for the production of the Aveo", + "5ad4f7df5b96ef001a10a7fa": "1951", + "5ad4f7df5b96ef001a10a7fb": "", + "5ad4f7df5b96ef001a10a7fc": "AvtoZAZ", + "5ad4f7df5b96ef001a10a7fd": "", + "5ad4f7df5b96ef001a10a7fe": "", + "57339555d058e614000b5df3": "1816", + "57339555d058e614000b5df4": "Warsaw University of Technology", + "57339555d058e614000b5df5": "2,000", + "57339555d058e614000b5df6": "Medical University of Warsaw", + "57339555d058e614000b5df7": "the Fryderyk Chopin University of Music", + "5ad4f8b35b96ef001a10a82a": "", + "5ad4f8b35b96ef001a10a82b": "Warsaw University of Technology", + "5ad4f8b35b96ef001a10a82c": "2,000", + "5ad4f8b35b96ef001a10a82d": "Medical University of Warsaw", + "5ad4f8b35b96ef001a10a82e": "Fryderyk Chopin University of Music", + "57339902d058e614000b5e70": "1816", + "57339902d058e614000b5e71": "over two million", + "57339902d058e614000b5e72": "", + "57339902d058e614000b5e73": "Irena Bajerska", + "57339902d058e614000b5e74": "more than 10,000 m2", + "5ad4faa45b96ef001a10a85a": "", + "5ad4faa45b96ef001a10a85b": "", + "5ad4faa45b96ef001a10a85c": "", + "5ad4faa45b96ef001a10a85d": "", + "5ad4faa45b96ef001a10a85e": "", + "573399b54776f41900660e64": "infrastructure", + "573399b54776f41900660e65": "the initial Three-Year Plan", + "573399b54776f41900660e66": "solid economic growth", + "573399b54776f41900660e67": "improved markedly", + "5ad4fbeb5b96ef001a10a882": "infrastructure", + "5ad4fbeb5b96ef001a10a883": "", + "5ad4fbeb5b96ef001a10a884": "solid economic growth", + "5ad4fbeb5b96ef001a10a885": "improved markedly", + "5ad4fbeb5b96ef001a10a886": "", + "57339a554776f41900660e74": "Warsaw", + "57339a554776f41900660e75": "Children's Memorial Health Institute", + "57339a554776f41900660e76": "Maria Sk\u0142odowska-Curie Institute of Oncology", + "57339a554776f41900660e77": "700", + "57339a554776f41900660e78": "developed", + "5ad4fd0f5b96ef001a10a896": "", + "5ad4fd0f5b96ef001a10a897": "", + "5ad4fd0f5b96ef001a10a898": "Maria Sk\u0142odowska-Curie Institute of Oncology", + "5ad4fd0f5b96ef001a10a899": "700", + "5ad4fd0f5b96ef001a10a89a": "developed", + "57339ad74776f41900660e86": "musical venues", + "57339ad74776f41900660e87": "events and festivals", + "57339ad74776f41900660e88": "Palace of Culture and Science", + "57339ad74776f41900660e89": "Warsaw", + "57339ad74776f41900660e8a": "events and festivals", + "5ad4fe635b96ef001a10a8b8": "musical", + "5ad4fe635b96ef001a10a8b9": "International Contemporary Music Festival", + "5ad4fe635b96ef001a10a8ba": "Palace of Culture and Science", + "5ad4fe635b96ef001a10a8bb": "", + "5ad4fe635b96ef001a10a8bc": "events and festivals", + "57339c16d058e614000b5ec5": "Ogr\u00f3d Saski", + "57339c16d058e614000b5ec6": "Ogr\u00f3d Saski", + "57339c16d058e614000b5ec7": "1870 to 1939", + "57339c16d058e614000b5ec8": "Momus", + "57339c16d058e614000b5ec9": "Wojciech Bogus\u0142awski Theatre", + "5ad4ff375b96ef001a10a8d6": "", + "5ad4ff375b96ef001a10a8d7": "", + "5ad4ff375b96ef001a10a8d8": "", + "5ad4ff375b96ef001a10a8d9": "Momus", + "5ad4ff375b96ef001a10a8da": "Wojciech Bogus\u0142awski Theatre", + "57339dd94776f41900660ecc": "Wianki", + "57339dd94776f41900660ecd": "thousands", + "57339dd94776f41900660ece": "Midsummer\u2019s Night", + "57339dd94776f41900660ecf": "when they would be married", + "57339dd94776f41900660ed0": "fern", + "5ad500e95b96ef001a10a912": "Wianki", + "5ad500e95b96ef001a10a913": "thousands", + "5ad500e95b96ef001a10a914": "19th century", + "5ad500e95b96ef001a10a915": "", + "5ad500e95b96ef001a10a916": "fern", + "57339eb9d058e614000b5ef6": "art posters", + "57339eb9d058e614000b5ef7": "60", + "57339eb9d058e614000b5ef8": "collections of paintings in the country", + "57339eb9d058e614000b5ef9": "paintings", + "57339eb9d058e614000b5efa": "arms", + "5ad502385b96ef001a10a954": "one of the largest collections of art posters in the world", + "5ad502385b96ef001a10a955": "", + "5ad502385b96ef001a10a956": "", + "5ad502385b96ef001a10a957": "", + "5ad502385b96ef001a10a958": "arms", + "5733a1854776f41900660f0a": "Warsaw Uprising Museum", + "5733a1854776f41900660f0b": "Katy\u0144 Museum", + "5733a1854776f41900660f0c": "stereoscopic", + "5733a1854776f41900660f0d": "The Museum of Independence", + "5733a1854776f41900660f0e": "60", + "5ad5036c5b96ef001a10a984": "the Katy\u0144 Museum", + "5ad5036c5b96ef001a10a985": "Katy\u0144 Museum", + "5ad5036c5b96ef001a10a986": "stereoscopic", + "5ad5036c5b96ef001a10a987": "The Museum of Independence", + "5ad5036c5b96ef001a10a988": "60", + "5733a2a9d058e614000b5f28": "Royal Ujazd\u00f3w Castle", + "5733a2a9d058e614000b5f29": "about 500", + "5733a2a9d058e614000b5f2a": "Zach\u0119ta National Gallery of Art", + "5733a2a9d058e614000b5f2b": "Polish and international artists", + "5733a2a9d058e614000b5f2c": "last weekend of September", + "5ad5041c5b96ef001a10a9ac": "Royal Ujazd\u00f3w Castle", + "5ad5041c5b96ef001a10a9ad": "", + "5ad5041c5b96ef001a10a9ae": "Zach\u0119ta National Gallery of Art", + "5ad5041c5b96ef001a10a9af": "Polish and international artists", + "5ad5041c5b96ef001a10a9b0": "last weekend of September", + "5733a32bd058e614000b5f32": "Polonia Warsaw", + "5733a32bd058e614000b5f33": "1946", + "5733a32bd058e614000b5f34": "twice", + "5733a32bd058e614000b5f35": "Konwiktorska Street", + "5733a32bd058e614000b5f36": "their disastrous financial situation", + "5ad505165b96ef001a10a9f4": "", + "5ad505165b96ef001a10a9f5": "1946", + "5ad505165b96ef001a10a9f6": "twice", + "5ad505165b96ef001a10a9f7": "Konwiktorska Street", + "5ad505165b96ef001a10a9f8": "", + "5733a45d4776f41900660f23": "syrenka", + "5733a45d4776f41900660f24": "The mermaid", + "5733a45d4776f41900660f25": "since at least the mid-14th century", + "5733a45d4776f41900660f26": "1390", + "5733a45d4776f41900660f27": "a sword", + "5ad5071f5b96ef001a10aa38": "upper body", + "5ad5071f5b96ef001a10aa39": "Civitatis Varsoviensis", + "5ad5071f5b96ef001a10aa3a": "at least the mid-14th century", + "5ad5071f5b96ef001a10aa3b": "1390", + "5ad5071f5b96ef001a10aa3c": "holding a sword", + "5733a560d058e614000b5f77": "", + "5733a560d058e614000b5f78": "the depths of the oceans and seas", + "5733a560d058e614000b5f79": "on the coast of Denmark", + "5733a560d058e614000b5f7a": "Warszowa", + "5733a560d058e614000b5f7b": "heard her songs; he followed the fishermen and captured", + "5ad507d25b96ef001a10aa4c": "", + "5ad507d25b96ef001a10aa4d": "", + "5ad507d25b96ef001a10aa4e": "", + "5ad507d25b96ef001a10aa4f": "Warszowa", + "5ad507d25b96ef001a10aa50": "heard her songs", + "5733a5f54776f41900660f44": "Maria Sk\u0142odowska-Curie", + "5733a5f54776f41900660f45": "Nobel Prize", + "5733a5f54776f41900660f46": "Famous musicians", + "5733a5f54776f41900660f47": "seven months old", + "5733a5f54776f41900660f48": "1745", + "5ad508665b96ef001a10aa68": "Maria Sk\u0142odowska-Curie", + "5ad508665b96ef001a10aa69": "Nobel Prize", + "5ad508665b96ef001a10aa6a": "", + "5ad508665b96ef001a10aa6b": "seven months old", + "5ad508665b96ef001a10aa6c": "1745", + "5733a6ac4776f41900660f58": "Warsaw", + "5733a6ac4776f41900660f59": "1916", + "5733a6ac4776f41900660f5a": "Art Deco style", + "5733a6ac4776f41900660f5b": "poet", + "5733a6ac4776f41900660f5c": "Isaac Bashevis Singer", + "5ad509615b96ef001a10aa7c": "", + "5ad509615b96ef001a10aa7d": "", + "5ad509615b96ef001a10aa7e": "", + "5ad509615b96ef001a10aa7f": "", + "5ad509615b96ef001a10aa80": "Isaac Bashevis Singer", + "5733cf61d058e614000b62e9": "1754\u20131763", + "5733cf61d058e614000b62ea": "British America and New France", + "5733cf61d058e614000b62eb": "60,000", + "5733cf61d058e614000b62ec": "2 million", + "5ad3a01a604f3c001a3fe971": "", + "5ad3a01a604f3c001a3fe972": "", + "5ad3a01a604f3c001a3fe973": "Native American allies", + "5ad3a01a604f3c001a3fe974": "", + "5ad3a01a604f3c001a3fe975": "", + "5733cff84776f419006612b4": "along the frontiers between New France and the British colonies", + "5733cff84776f419006612b5": "with a dispute over control of the confluence of the Allegheny and Monongahela rivers", + "5733cff84776f419006612b6": "May 1754", + "5ad3a076604f3c001a3fe9a7": "", + "5ad3a076604f3c001a3fe9a8": "", + "5ad3a076604f3c001a3fe9a9": "", + "5ad3a076604f3c001a3fe9aa": "", + "5ad3a076604f3c001a3fe9ab": "", + "5733d13e4776f419006612c4": "1755", + "5733d13e4776f419006612c5": "disaster", + "5733d13e4776f419006612c6": "poor management, internal divisions, and effective Canadian scouts, French regular forces, and Indian warrior allies", + "5733d13e4776f419006612c7": "Fort Beaus\u00e9jour", + "5733d13e4776f419006612c8": "", + "5ad3a16d604f3c001a3fe9e1": "1755", + "5ad3a16d604f3c001a3fe9e2": "a disaster", + "5ad3a16d604f3c001a3fe9e3": "poor management, internal divisions, and effective Canadian scouts, French regular forces, and Indian warrior allies", + "5ad3a16d604f3c001a3fe9e4": "Fort Beaus\u00e9jour", + "5ad3a16d604f3c001a3fe9e5": "", + "5733d249d058e614000b6331": "William Pitt", + "5733d249d058e614000b6332": "", + "5733d249d058e614000b6333": "France concentrated its forces against Prussia and its allies in the European theatre of the war", + "5733d249d058e614000b6334": "Sainte Foy in Quebec", + "5ad3a1cd604f3c001a3fe9f5": "", + "5ad3a1cd604f3c001a3fe9f6": "", + "5ad3a1cd604f3c001a3fe9f7": "", + "5ad3a1cd604f3c001a3fe9f8": "", + "5ad3a1cd604f3c001a3fe9f9": "Sainte Foy in Quebec", + "5733d2dbd058e614000b6339": "France ceded its territory east of the Mississippi to Great Britain", + "5733d2dbd058e614000b633a": "Havana, Cuba", + "5733d2dbd058e614000b633b": "The outcome was one of the most significant developments in a century of Anglo-French conflict", + "5ad3a21d604f3c001a3fea1d": "", + "5ad3a21d604f3c001a3fea1e": "French Louisiana west of the Mississippi River", + "5ad3a21d604f3c001a3fea1f": "", + "5ad3a21d604f3c001a3fea20": "", + "5ad3a21d604f3c001a3fea21": "The outcome was one of the most significant developments in a century of Anglo-French conflict", + "5733d3cb4776f419006612ea": "the 1740s", + "5733d3cb4776f419006612eb": "Indians fought on both sides of the conflict", + "5733d3cb4776f419006612ec": "a much larger conflict between France and Great Britain", + "5733d3cb4776f419006612ed": "", + "5ad3a27c604f3c001a3fea31": "", + "5ad3a27c604f3c001a3fea32": "", + "5ad3a27c604f3c001a3fea33": "", + "5ad3a27c604f3c001a3fea34": "", + "5ad3a27c604f3c001a3fea35": "", + "5733d4c8d058e614000b6353": "1756 to the signing of the peace treaty in 1763", + "5733d4c8d058e614000b6354": "six years", + "5733d4c8d058e614000b6355": "1760", + "5733d4c8d058e614000b6356": "Battle of Jumonville Glen", + "5ad3a2e3604f3c001a3fea3b": "", + "5ad3a2e3604f3c001a3fea3c": "", + "5ad3a2e3604f3c001a3fea3d": "", + "5ad3a2e3604f3c001a3fea3e": "", + "5ad3a2e3604f3c001a3fea3f": "", + "5733d5704776f4190066130e": "", + "5733d5704776f4190066130f": "along the St. Lawrence River valley", + "5733d5704776f41900661310": "St. Lawrence and Mississippi watersheds", + "5ad3a342604f3c001a3fea59": "", + "5ad3a342604f3c001a3fea5a": "", + "5ad3a342604f3c001a3fea5b": "", + "5ad3a342604f3c001a3fea5c": "", + "5ad3a342604f3c001a3fea5d": "", + "5733d68ed058e614000b637f": "20 to 1", + "5733d68ed058e614000b6380": "Nova Scotia and Newfoundland", + "5733d68ed058e614000b6381": "along the coast", + "5ad3a38c604f3c001a3fea63": "", + "5ad3a38c604f3c001a3fea64": "", + "5ad3a38c604f3c001a3fea65": "", + "5ad3a38c604f3c001a3fea66": "Nova Scotia and Newfoundland", + "5ad3a38c604f3c001a3fea67": "", + "5733d7cbd058e614000b63ab": "native tribes", + "5733d7cbd058e614000b63ac": "the Mi'kmaq and the Abenaki", + "5733d7cbd058e614000b63ad": "present-day Upstate New York and the Ohio Country", + "5733d7cbd058e614000b63ae": "Iroquois rule", + "5ad3a3fc604f3c001a3fea77": "", + "5ad3a3fc604f3c001a3fea78": "native tribes", + "5ad3a3fc604f3c001a3fea79": "", + "5ad3a3fc604f3c001a3fea7a": "", + "5ad3a3fc604f3c001a3fea7b": "", + "5733da01d058e614000b63f9": "Catawba, Muskogee-speaking Creek and Choctaw", + "5733da01d058e614000b63fa": "western portions of the Great Lakes region", + "5733da01d058e614000b63fb": "Iroquois Six Nations", + "5ad3a733604f3c001a3feac9": "", + "5ad3a733604f3c001a3feaca": "", + "5ad3a733604f3c001a3feacb": "", + "5ad3a733604f3c001a3feacc": "", + "5ad3a733604f3c001a3feacd": "", + "5733dab4d058e614000b6409": "no French regular army troops were stationed in North America, and few British troops", + "5733dab4d058e614000b640a": "few", + "5733dab4d058e614000b640b": "", + "5ad3a79a604f3c001a3fead3": "no French regular army troops were stationed in North America, and few British troops", + "5ad3a79a604f3c001a3fead4": "", + "5ad3a79a604f3c001a3fead5": "", + "5ad3a79a604f3c001a3fead6": "", + "5ad3a79a604f3c001a3fead7": "", + "5733db8dd058e614000b6428": "3,000 miles (4,800 km)", + "5733db8dd058e614000b6429": "200 Troupes de la marine and 30 Indians", + "5733db8dd058e614000b642a": "C\u00e9loron informed them of the French claims on the territory and told them to leave", + "5ad3a7ef604f3c001a3feadd": "", + "5ad3a7ef604f3c001a3feade": "", + "5ad3a7ef604f3c001a3feadf": "", + "5ad3a7ef604f3c001a3feae0": "", + "5ad3a7ef604f3c001a3feae1": "", + "5733dc95d058e614000b644a": "informed C\u00e9loron that they owned the Ohio Country", + "5733dc95d058e614000b644b": "Pickawillany", + "5733dc95d058e614000b644c": "C\u00e9loron threatened \"Old Briton\" with severe consequences if he continued to trade with the British. \"Old Briton\" ignored the warning", + "5733dc95d058e614000b644d": "ignored the warning", + "5ad3a839604f3c001a3feaf1": "", + "5ad3a839604f3c001a3feaf2": "", + "5ad3a839604f3c001a3feaf3": "", + "5ad3a839604f3c001a3feaf4": "", + "5ad3a839604f3c001a3feaf5": "", + "5733dd4f4776f419006613aa": "the Natives of these localities are very badly disposed towards the French", + "5733dd4f4776f419006613ab": "", + "5733dd4f4776f419006613ac": "William Shirley, the expansionist governor of the Province of Massachusetts Bay, was particularly forceful", + "5ad3a893604f3c001a3feafb": "", + "5ad3a893604f3c001a3feafc": "the Natives of these localities are very badly disposed towards the French", + "5ad3a893604f3c001a3feafd": "", + "5ad3a893604f3c001a3feafe": "", + "5ad3a893604f3c001a3feaff": "William Shirley, the expansionist governor of the Province of Massachusetts Bay, was particularly forceful", + "5733e5a14776f4190066145b": "1749", + "5733e5a14776f4190066145c": "Ohio Company of Virginia", + "5733e5a14776f4190066145d": "Christopher Gist", + "5733e5a14776f4190066145e": "", + "5733e5a14776f4190066145f": "at the mouth of the Monongahela River", + "5ad3a8fe604f3c001a3feb05": "1749", + "5ad3a8fe604f3c001a3feb06": "", + "5ad3a8fe604f3c001a3feb07": "", + "5ad3a8fe604f3c001a3feb08": "", + "5ad3a8fe604f3c001a3feb09": "", + "5733e771d058e614000b6545": "", + "5733e771d058e614000b6546": "Treaty of Aix-la-Chapelle", + "5733e771d058e614000b6547": "", + "5733e771d058e614000b6548": "The issues of conflicting territorial claims between British and French colonies in North America were turned over to a commission to resolve", + "5ad3ad01604f3c001a3febd3": "", + "5ad3ad01604f3c001a3febd4": "", + "5ad3ad01604f3c001a3febd5": "", + "5ad3ad01604f3c001a3febd6": "resolving issues in Europe", + "5ad3ad01604f3c001a3febd7": "", + "5733e8ae4776f419006614a6": "Marquis de la Jonqui\u00e8re", + "5733e8ae4776f419006614a7": "300 men", + "5733e8ae4776f419006614a8": "to punish the Miami people of Pickawillany for not following C\u00e9loron's orders to cease trading with the British", + "5733e8ae4776f419006614a9": "capturing three traders and killing 14 people of the Miami nation", + "5ad3ad60604f3c001a3fec03": "", + "5ad3ad60604f3c001a3fec04": "", + "5ad3ad60604f3c001a3fec05": "", + "5ad3ad60604f3c001a3fec06": "", + "5ad3ad60604f3c001a3fec07": "", + "5733ea04d058e614000b6594": "", + "5733ea04d058e614000b6595": "Lake Erie's south shore", + "5733ea04d058e614000b6596": "Fort Le Boeuf", + "5733ea04d058e614000b6597": "to protect the King's land in the Ohio Valley from the British", + "5733ea04d058e614000b6598": "Tanaghrisson", + "5ad3ade2604f3c001a3fec15": "", + "5ad3ade2604f3c001a3fec16": "", + "5ad3ade2604f3c001a3fec17": "Lake Erie's south shore", + "5ad3ade2604f3c001a3fec18": "", + "5ad3ade2604f3c001a3fec19": "", + "5733eb34d058e614000b65cc": "Superintendent for Indian Affairs", + "5733eb34d058e614000b65cd": "Warraghiggey", + "5733eb34d058e614000b65ce": "Warraghiggey", + "5733eb34d058e614000b65cf": "Mohawk Chief Hendrick", + "5ad3ae4f604f3c001a3fec47": "", + "5ad3ae4f604f3c001a3fec48": "colonel of the Western New York Militia", + "5ad3ae4f604f3c001a3fec49": "", + "5ad3ae4f604f3c001a3fec4a": "", + "5ad3ae4f604f3c001a3fec4b": "", + "5733ef47d058e614000b662b": "Ohio Company", + "5733ef47d058e614000b662c": "George Washington", + "5733ef47d058e614000b662d": "Jacob Van Braam", + "5733ef47d058e614000b662e": "December 12", + "5ad3aedc604f3c001a3fec51": "", + "5ad3aedc604f3c001a3fec52": "", + "5ad3aedc604f3c001a3fec53": "", + "5ad3aedc604f3c001a3fec54": "Jacob Van Braam", + "5ad3aedc604f3c001a3fec55": "", + "5733f062d058e614000b6633": "Jacques Legardeur de Saint-Pierre", + "5733f062d058e614000b6634": "the letter from Dinwiddie", + "5733f062d058e614000b6635": "\"As to the Summons you send me to retire, I do not think myself obliged to obey it.\"", + "5733f062d058e614000b6636": "France's claim to the region was superior to that of the British", + "5ad3af4e604f3c001a3fec73": "", + "5ad3af4e604f3c001a3fec74": "", + "5ad3af4e604f3c001a3fec75": "", + "5ad3af4e604f3c001a3fec76": "\"As to the Summons you send me to retire, I do not think myself obliged to obey it.\"", + "5ad3af4e604f3c001a3fec77": "", + "5733f1784776f41900661575": "", + "5733f1784776f41900661576": "", + "5733f1784776f41900661577": "Fort Duquesne", + "5ad3afa9604f3c001a3fec85": "", + "5ad3afa9604f3c001a3fec86": "", + "5ad3afa9604f3c001a3fec87": "", + "5ad3afa9604f3c001a3fec88": "", + "5ad3afa9604f3c001a3fec89": "", + "5733f309d058e614000b6648": "surprised the Canadians", + "5733f309d058e614000b6649": "They killed many of the Canadians", + "5733f309d058e614000b664a": "Tanaghrisson had promised support to the British", + "5ad3b08b604f3c001a3fecb1": "", + "5ad3b08b604f3c001a3fecb2": "", + "5ad3b08b604f3c001a3fecb3": "", + "5ad3b08b604f3c001a3fecb4": "", + "5ad3b08b604f3c001a3fecb5": "", + "5733f410d058e614000b6663": "to dislodge the French", + "5733f410d058e614000b6664": "well before Braddock's departure for North America", + "5733f410d058e614000b6665": "dispatched six regiments to New France", + "5733f410d058e614000b6666": "blockade French ports", + "5ad3b147604f3c001a3fecd5": "to dislodge the French", + "5ad3b147604f3c001a3fecd6": "", + "5ad3b147604f3c001a3fecd7": "", + "5ad3b147604f3c001a3fecd8": "", + "5ad3b147604f3c001a3fecd9": "blockade French ports", + "5733f5264776f419006615a3": "Albany Congress", + "5733f5264776f419006615a4": "to formalize a unified front in trade and negotiations with various Indians", + "5733f5264776f419006615a5": "The plan that the delegates agreed to was never ratified by the colonial legislatures nor approved of by the crown", + "5733f5264776f419006615a6": "to formalize a unified front in trade and negotiations with various Indians", + "5ad3b1be604f3c001a3fece9": "", + "5ad3b1be604f3c001a3fecea": "", + "5ad3b1be604f3c001a3feceb": "", + "5ad3b1be604f3c001a3fecec": "", + "5ad3b1be604f3c001a3feced": "", + "5733f5f24776f419006615c1": "Braddock", + "5733f5f24776f419006615c2": "", + "5733f5f24776f419006615c3": "Approximately 1,000 British soldiers were killed or injured", + "5733f5f24776f419006615c4": "Washington and Thomas Gage", + "5ad3b260604f3c001a3fed05": "", + "5ad3b260604f3c001a3fed06": "", + "5ad3b260604f3c001a3fed07": "", + "5ad3b260604f3c001a3fed08": "", + "5ad3b260604f3c001a3fed09": "", + "5733f7b9d058e614000b66a9": "Shirley and Johnson", + "5733f7b9d058e614000b66aa": "logistical", + "5733f7b9d058e614000b66ab": "", + "5733f7b9d058e614000b66ac": "garrisons", + "5ad3b2e8604f3c001a3fed23": "Shirley and Johnson", + "5ad3b2e8604f3c001a3fed24": "", + "5ad3b2e8604f3c001a3fed25": "", + "5ad3b2e8604f3c001a3fed26": "", + "5ad3b2e8604f3c001a3fed27": "", + "5733f8dc4776f419006615f7": "Marquis de Vaudreuil", + "5733f8dc4776f419006615f8": "sent Dieskau to Fort St. Fr\u00e9d\u00e9ric to meet that threat", + "5733f8dc4776f419006615f9": "", + "5733f8dc4776f419006615fa": "Fort William Henry", + "5733f8dc4776f419006615fb": "Ticonderoga Point", + "5ad3b373604f3c001a3fed49": "", + "5ad3b373604f3c001a3fed4a": "", + "5ad3b373604f3c001a3fed4b": "", + "5ad3b373604f3c001a3fed4c": "", + "5ad3b373604f3c001a3fed4d": "Ticonderoga Point", + "5733f9fa4776f4190066161f": "Colonel Monckton", + "5733f9fa4776f41900661620": "Nova Scotia's Governor Charles Lawrence ordered the deportation of the French-speaking Acadian population from the area", + "5733f9fa4776f41900661621": "the only clashes of any size were at Petitcodiac in 1755 and at Bloody Creek near Annapolis Royal in 1757", + "5ad3b3dc604f3c001a3fed67": "", + "5ad3b3dc604f3c001a3fed68": "Colonel Monckton", + "5ad3b3dc604f3c001a3fed69": "", + "5ad3b3dc604f3c001a3fed6a": "", + "5ad3b3dc604f3c001a3fed6b": "", + "5733faaf4776f4190066162f": "William Shirley", + "5733faaf4776f41900661630": "Albany", + "5733faaf4776f41900661631": "attacks on Fort Frontenac", + "5733faaf4776f41900661632": "through the wilderness of the Maine district and down the Chaudi\u00e8re River", + "5ad3b498604f3c001a3fed7b": "", + "5ad3b498604f3c001a3fed7c": "", + "5ad3b498604f3c001a3fed7d": "", + "5ad3b498604f3c001a3fed7e": "", + "5ad3b498604f3c001a3fed7f": "", + "5733fb7bd058e614000b66ff": "Major General James Abercrombie", + "5733fb7bd058e614000b6700": "Major General Louis-Joseph de Montcalm", + "5733fb7bd058e614000b6701": "May 18, 1756", + "5ad3b4e8604f3c001a3fed99": "", + "5ad3b4e8604f3c001a3fed9a": "", + "5ad3b4e8604f3c001a3fed9b": "", + "5ad3b4e8604f3c001a3fed9c": "", + "5ad3b4e8604f3c001a3fed9d": "May 18, 1756", + "5733fc6ed058e614000b670f": "Oneida Carry", + "5733fc6ed058e614000b6710": "the British supply chain", + "5733fc6ed058e614000b6711": "45,000 pounds", + "5733fc6ed058e614000b6712": "any British hopes for campaigns on Lake Ontario", + "5ad3b567604f3c001a3fedb3": "", + "5ad3b567604f3c001a3fedb4": "", + "5ad3b567604f3c001a3fedb5": "he ordered an attack against the forts Shirley had erected at the Oneida Carry.", + "5ad3b567604f3c001a3fedb6": "45,000 pounds", + "5ad3b567604f3c001a3fedb7": "", + "5733fd66d058e614000b6735": "Abercrombie", + "5733fd66d058e614000b6736": "Ticonderoga", + "5733fd66d058e614000b6737": "", + "5733fd66d058e614000b6738": "the disposition of prisoners' personal effects", + "5ad3b6d8604f3c001a3fedfb": "Ticonderoga", + "5ad3b6d8604f3c001a3fedfc": "Abercrombie", + "5ad3b6d8604f3c001a3fedfd": "", + "5ad3b6d8604f3c001a3fedfe": "Oswego", + "5ad3b6d8604f3c001a3fedff": "", + "5733fe73d058e614000b673d": "an attack on New France's capital, Quebec", + "5733fe73d058e614000b673e": "to distract Montcalm", + "5733fe73d058e614000b673f": "William Pitt", + "5733fe73d058e614000b6740": "returned to New York", + "5ad3b781604f3c001a3fee23": "", + "5ad3b781604f3c001a3fee24": "", + "5ad3b781604f3c001a3fee25": "", + "5ad3b781604f3c001a3fee26": "William Pitt", + "5ad3b781604f3c001a3fee27": "returned to New York", + "5733ffa7d058e614000b674f": "Montcalm and 7,000 troops", + "5733ffa7d058e614000b6750": "Lake George", + "5733ffa7d058e614000b6751": "attacked the British column", + "5ad3b826604f3c001a3fee47": "Montcalm and 7,000 troops", + "5ad3b826604f3c001a3fee48": "", + "5ad3b826604f3c001a3fee49": "Lake George", + "5ad3b826604f3c001a3fee4a": "Lake George", + "5ad3b826604f3c001a3fee4b": "attacked the British column", + "57340111d058e614000b677d": "poor harvest", + "57340111d058e614000b677e": "poor harvest", + "57340111d058e614000b677f": "St. Lawrence", + "5ad3b911604f3c001a3fee63": "", + "5ad3b911604f3c001a3fee64": "", + "5ad3b911604f3c001a3fee65": "poor harvest", + "5ad3b911604f3c001a3fee66": "poor harvest", + "5ad3b911604f3c001a3fee67": "defense of the St. Lawrence", + "5734025d4776f419006616c3": "The British failures in North America", + "5734025d4776f419006616c4": "Pitt", + "5734025d4776f419006616c5": "three major offensive actions involving large numbers of regular troops", + "5734025d4776f419006616c6": "Two", + "5ad3b9cd604f3c001a3fee87": "", + "5ad3b9cd604f3c001a3fee88": "British failures in North America", + "5ad3b9cd604f3c001a3fee89": "", + "5ad3b9cd604f3c001a3fee8a": "Pitt", + "5ad3b9cd604f3c001a3fee8b": "", + "573403394776f419006616dd": "3,600", + "573403394776f419006616de": "18,000", + "573403394776f419006616df": "decisively defeated Abercrombie's force of 18,000 regulars, militia and Native American allies", + "573403394776f419006616e0": "Abercrombie was recalled and replaced by Jeffery Amherst, victor at Louisbourg.", + "5ad3ba81604f3c001a3fee9b": "3,600", + "5ad3ba81604f3c001a3fee9c": "", + "5ad3ba81604f3c001a3fee9d": "18,000", + "5ad3ba81604f3c001a3fee9e": "decisively defeated Abercrombie's force of 18,000 regulars, militia and Native American allies", + 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the Restigouche", + "5ad3bb68604f3c001a3feec3": "James Wolfe", + "5ad3bb68604f3c001a3feec4": "James Wolfe", + "5ad3bb68604f3c001a3feec5": "victory at Fort Niagara successfully cut off the French frontier forts", + "5ad3bb68604f3c001a3feec6": "", + "5ad3bb68604f3c001a3feec7": "Battle of Sainte-Foy", + "573407d7d058e614000b6813": "Governor Vaudreuil", + "573407d7d058e614000b6814": "The British provided medical treatment for the sick and wounded French soldiers and French regular troops were returned to France aboard British ships", + "573407d7d058e614000b6815": "General Amherst", + "5ad3bbcc604f3c001a3feecd": "Governor Vaudreuil", + "5ad3bbcc604f3c001a3feece": "", + "5ad3bbcc604f3c001a3feecf": "The British provided medical treatment for the sick and wounded French soldiers and French regular troops were returned to France aboard British ships", + "5ad3bbcc604f3c001a3feed0": "", + "5ad3bbcc604f3c001a3feed1": "General Amherst", + "573408ef4776f41900661757": "10 February 1763", + 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"lands west of the Appalachian Mountains", + "5ad3bd30604f3c001a3fef0f": "", + "5ad3bd30604f3c001a3fef10": "", + "5ad3bd30604f3c001a3fef11": "", + "5ad3bd30604f3c001a3fef12": "", + "5ad3bd30604f3c001a3fef13": "", + "57340d124776f419006617bf": "", + "57340d124776f419006617c0": "legal and illegal settlement due to the construction of military roads to the area by Braddock and Forbes", + "57340d124776f419006617c1": "1769", + "57340d124776f419006617c2": "", + "57340d124776f419006617c3": "Cuba", + "5ad3bd87604f3c001a3fef23": "", + "5ad3bd87604f3c001a3fef24": "", + "5ad3bd87604f3c001a3fef25": "", + "5ad3bd87604f3c001a3fef26": "", + "5ad3bd87604f3c001a3fef27": "", + "573735e8c3c5551400e51e71": "concept of force", + "573735e8c3c5551400e51e72": "A fundamental error", + "573735e8c3c5551400e51e73": "", + "573735e8c3c5551400e51e74": "", + "573735e8c3c5551400e51e75": "", + "5ad25efad7d075001a428f56": "", + "5ad25efad7d075001a428f57": "motion", + "5ad25efad7d075001a428f58": "Galileo Galilei and Sir Isaac Newton", + "5ad25efad7d075001a428f59": "motion and force", + "5ad25efad7d075001a428f5a": "Sir Isaac Newton", + "57373a9fc3c5551400e51e7b": "", + "57373a9fc3c5551400e51e7c": "gauge bosons", + "57373a9fc3c5551400e51e7d": "", + "57373a9fc3c5551400e51e7e": "", + "57373a9fc3c5551400e51e7f": "", + "5ad25f82d7d075001a428f84": "", + "5ad25f82d7d075001a428f85": "", + "5ad25f82d7d075001a428f86": "", + "5ad25f82d7d075001a428f87": "", + "57373d0cc3c5551400e51e85": "Aristotle", + "57373d0cc3c5551400e51e86": "Aristotelian cosmology", + "57373d0cc3c5551400e51e87": "four", + "57373d0cc3c5551400e51e88": "on the ground", + "57373d0cc3c5551400e51e89": "", + "5ad2605dd7d075001a428fc6": "", + "5ad2605dd7d075001a428fc7": "", + "5ad2605dd7d075001a428fc8": "left alone", + "5ad2605dd7d075001a428fc9": "", + "57373f80c3c5551400e51e8f": "", + "57373f80c3c5551400e51e90": "", + "57373f80c3c5551400e51e91": "", + "57373f80c3c5551400e51e92": "", + "57373f80c3c5551400e51e93": "friction", + "5ad26103d7d075001a428fec": "", + "5ad26103d7d075001a428fed": "", + "5ad26103d7d075001a428fee": "", + "5ad26103d7d075001a428fef": "", + "5737432bc3c5551400e51e99": "Newton", + "5737432bc3c5551400e51e9a": "", + "5737432bc3c5551400e51e9b": "", + "5737432bc3c5551400e51e9c": "Newton's First Law", + "5737432bc3c5551400e51e9d": "", + "5ad261a4d7d075001a429048": "", + "5ad261a4d7d075001a429049": "", + "5ad261a4d7d075001a42904a": "", + "5ad261a4d7d075001a42904b": "", + "5737477bc3c5551400e51ea3": "laws of physics", + "5737477bc3c5551400e51ea4": "curving parabolic path", + "5737477bc3c5551400e51ea5": "at rest", + "5737477bc3c5551400e51ea6": "Inertia", + "5ad26257d7d075001a42909c": "", + "5ad26257d7d075001a42909d": "the person", + "5ad26257d7d075001a42909e": "", + "5ad26257d7d075001a42909f": "", + "573749741c4567190057445d": "inertia", + "573749741c4567190057445e": "", + "573749741c4567190057445f": "Albert Einstein", + "573749741c45671900574460": "", + "573749741c45671900574461": "principle of equivalence", + "5ad262f7d7d075001a4290d4": "", + "5ad262f7d7d075001a4290d5": "", + "5ad262f7d7d075001a4290d6": "", + "5ad262f7d7d075001a4290d7": "", + "573750f51c45671900574467": "Newton's Second Law", + "573750f61c45671900574468": "", + "573750f61c45671900574469": "General relativity", + "573750f61c4567190057446a": "General relativity", + "573750f61c4567190057446b": "fixed", + "5ad26382d7d075001a42911a": "", + "5ad26382d7d075001a42911b": "", + "5ad26382d7d075001a42911c": "", + "5ad26382d7d075001a42911d": "", + "5737534ec3c5551400e51eab": "Newton's Third Law", + "5737534ec3c5551400e51eac": "The third law", + "5737534ec3c5551400e51ead": "unidirectional force", + "5737534ec3c5551400e51eae": "", + "5ad26421d7d075001a42913e": "", + "5ad26421d7d075001a42913f": "", + "5ad26421d7d075001a429140": "a force \u2212F", + "573755afc3c5551400e51eb3": "the center of mass", + "573755afc3c5551400e51eb4": "closed", + "573755afc3c5551400e51eb5": "", + "5ad266f6d7d075001a4291fe": "forces that are unbalanced", + "5ad266f6d7d075001a4291ff": "", + "5ad266f6d7d075001a429200": "", + "5ad266f6d7d075001a429201": "", + "573766251c45671900574471": "an intuitive understanding", + "573766251c45671900574472": "", + "573766251c45671900574473": "Newtonian mechanics", + "573766251c45671900574474": "Through experimentation", + "5ad26797d7d075001a429236": "", + "5ad26797d7d075001a429237": "Newtonian mechanics", + "5ad26797d7d075001a429238": "", + "5ad26797d7d075001a429239": "", + "57376828c3c5551400e51eb9": "vector quantities", + "57376828c3c5551400e51eba": "scalar quantities", + "57376828c3c5551400e51ebb": "Associating forces with vectors", + "57376828c3c5551400e51ebc": "ambiguous", + "57376828c3c5551400e51ebd": "", + "5ad26839d7d075001a42925a": "", + "5ad26839d7d075001a42925b": "", + "5ad26839d7d075001a42925c": "", + "5ad26839d7d075001a42925d": "", + "57376a1bc3c5551400e51ec3": "static equilibrium", + "57376a1bc3c5551400e51ec4": "magnitude and direction", + "57376a1bc3c5551400e51ec5": "net force", + "57376a1bc3c5551400e51ec6": "their respective lines of application", + "57376a1bc3c5551400e51ec7": "", + "5ad26925d7d075001a4292c4": "", + "5ad26925d7d075001a4292c5": "", + "5ad26925d7d075001a4292c6": "", + "5ad26925d7d075001a4292c7": "", + "57376c50c3c5551400e51ecd": "", + "57376c50c3c5551400e51ece": "two", + "57376c50c3c5551400e51ecf": "yields the original force", + "57376c50c3c5551400e51ed0": "", + "57376c50c3c5551400e51ed1": "three-dimensional", + "5ad269a7d7d075001a4292e0": "", + "5ad269a7d7d075001a4292e1": "", + "5ad269a7d7d075001a4292e2": "", + "5ad269a7d7d075001a4292e3": "", + "57376df3c3c5551400e51ed7": "", + "57376df3c3c5551400e51ed8": "", + "57376df3c3c5551400e51ed9": "applied force", + "57376df3c3c5551400e51eda": "increases or decreases", + "5ad26a5fd7d075001a429318": "", + "5ad26a5fd7d075001a429319": "", + "5ad26a5fd7d075001a42931a": "", + "5ad26a5fd7d075001a42931b": "", + "57377083c3c5551400e51edf": "", + "57377083c3c5551400e51ee0": "spring reaction force", + "57377083c3c5551400e51ee1": "the object's weight", + "57377083c3c5551400e51ee2": "force of gravity", + "57377083c3c5551400e51ee3": "Isaac Newton", + "5ad26aedd7d075001a429332": "", + "5ad26aedd7d075001a429333": "", + "5ad26aedd7d075001a429334": "", + "5ad26aedd7d075001a429335": "", + "573776eec3c5551400e51ee9": "Galileo", + "573776eec3c5551400e51eea": "rest", + "573776eec3c5551400e51eeb": "Aristotle", + "573776eec3c5551400e51eec": "", + "573776eec3c5551400e51eed": "", + "5ad26c15d7d075001a42937c": "", + "5ad26c15d7d075001a42937d": "", + "5ad26c15d7d075001a42937e": "Aristotelian", + "5ad26c15d7d075001a42937f": "", + "57377862c3c5551400e51ef3": "", + "57377862c3c5551400e51ef4": "kinetic friction force", + "57377862c3c5551400e51ef5": "kinetic friction", + "57377862c3c5551400e51ef6": "Aristotle", + "5ad27697d7d075001a429518": "", + "5ad27697d7d075001a429519": "", + "5ad27697d7d075001a42951a": "", + "5ad27697d7d075001a42951b": "", + "57377aac1c45671900574479": "Schr\u00f6dinger equation", + 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"", + "5ad278c3d7d075001a42957f": "", + "5737804dc3c5551400e51f0f": "", + "5737804dc3c5551400e51f10": "strong and weak forces", + "5737804dc3c5551400e51f11": "electromagnetic force", + "5737804dc3c5551400e51f12": "masses", + "5737804dc3c5551400e51f13": "Pauli exclusion principle", + "5ad27941d7d075001a4295a8": "", + "5ad27941d7d075001a4295a9": "four", + "5ad27941d7d075001a4295aa": "", + "5ad27941d7d075001a4295ab": "", + "5737821cc3c5551400e51f19": "Isaac Newton", + "5737821cc3c5551400e51f1a": "20th", + "5737821cc3c5551400e51f1b": "self-consistent unification models", + "5737821cc3c5551400e51f1c": "self-consistent unification models", + "5ad279e5d7d075001a4295c2": "", + "5ad279e5d7d075001a4295c3": "", + "5ad279e5d7d075001a4295c4": "", + "5ad279e5d7d075001a4295c5": "", + "573784fa1c45671900574483": "Isaac Newton", + "573784fa1c45671900574484": "", + "573784fa1c45671900574485": "", + "573784fa1c45671900574486": "", + "573784fa1c45671900574487": "", + "5ad27a80d7d075001a4295fa": "", + "5ad27a80d7d075001a4295fb": "", + "5ad27a80d7d075001a4295fc": "", + "5ad27a80d7d075001a4295fd": "", + "573786b51c4567190057448d": "larger distances", + "573786b51c4567190057448e": "the same force of gravity", + "573786b51c4567190057448f": "the mass of the attracting body", + "573786b51c45671900574490": "radius", + "5ad27e30d7d075001a429700": "", + "5ad27e30d7d075001a429701": "the same force of gravity", + "5ad27e30d7d075001a429702": "", + "5ad27e30d7d075001a429703": "", + "57378862c3c5551400e51f21": "", + "57378862c3c5551400e51f22": "Henry Cavendish", + "57378862c3c5551400e51f23": "1798", + "57378862c3c5551400e51f24": "Newton", + "5ad27f01d7d075001a429742": "", + "5ad27f01d7d075001a429743": "", + "5ad27f01d7d075001a429744": "", + "5ad27f01d7d075001a429745": "", + "5737898f1c45671900574495": "", + "5737898f1c45671900574496": "Vulcan", + "5737898f1c45671900574497": "", + "5737898f1c45671900574498": "Albert Einstein", + "5737898f1c45671900574499": "Albert Einstein", + 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "52 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"52 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "53 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"53 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "54 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"54 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "55 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"55 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "56 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"56 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "57 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"57 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "58 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"58 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "59 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"59 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "60 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"60 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "61 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"61 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "62 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"62 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "63 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"62 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "67 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"63 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "64 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"64 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "65 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"65 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "66 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"66 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "67 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"67 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "69 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "70 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "73 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"68 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "90 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"69 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "76 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"70 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "71 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"71 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "72 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"72 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "78 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"73 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "74 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"74 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "75 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"75 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "84 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"76 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "77 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"77 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "79 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"78 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "79 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"79 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "80 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"80 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "81 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"81 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "82 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"82 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "83 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"83 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "84 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"84 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "85 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"85 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "86 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"86 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "87 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"87 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "88 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"88 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "89 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"89 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "90 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"90 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "91 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"91 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "92 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"91 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "96 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"92 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "93 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"93 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "94 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"94 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "95 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"95 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "96 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"96 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "97 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"97 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"97 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "99 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"97 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "102 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"97 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "119 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"98 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "105 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"99 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "100 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"100 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "101 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"101 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "107 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"102 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "103 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"103 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "104 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"104 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "113 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"105 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "106 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"106 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "108 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"107 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "108 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"108 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "109 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"109 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "110 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"110 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "111 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"111 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "112 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"112 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "113 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"113 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "114 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"114 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "115 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"115 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "116 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"116 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "117 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"117 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "118 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"118 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "119 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"121 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "122 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"122 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "123 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"123 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "124 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"124 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "125 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"125 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "127 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "128 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "131 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"126 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "148 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"127 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "134 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"128 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "129 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"129 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "130 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"130 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "136 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"131 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "132 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"132 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "133 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"133 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "142 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"134 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "135 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"135 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "137 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"136 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "137 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"137 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "138 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"138 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "139 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"139 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "140 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"140 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "141 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"141 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "142 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"142 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "143 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"143 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "144 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"144 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "145 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"145 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "146 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"146 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "147 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"147 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "148 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"150 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "151 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"151 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "152 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"152 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "153 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"153 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "154 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"154 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "156 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "157 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "160 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"155 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"156 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "163 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"157 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "158 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"158 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "159 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"159 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "165 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"160 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "161 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"161 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "162 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"162 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "171 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"163 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "164 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"164 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "166 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"165 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "166 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"166 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "167 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"167 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "168 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"168 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "169 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"169 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "170 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"170 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "171 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"171 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "172 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"172 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "173 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"173 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "174 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"174 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "175 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"175 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "176 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"176 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "177 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"179 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "180 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"180 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "181 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"181 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "182 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"182 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "183 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"183 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "184 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"184 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"184 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "186 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"184 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "189 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"184 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "206 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"185 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "192 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"186 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "187 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"187 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "188 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"188 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "194 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"189 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "190 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"190 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "191 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"191 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "200 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"192 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "193 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"193 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "195 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"194 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "195 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"195 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "196 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"196 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "197 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"197 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "198 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"198 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "199 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"199 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "200 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"200 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "201 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"201 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "202 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"202 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "203 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"203 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "204 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"204 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "205 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"205 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "206 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"208 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"209 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "210 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"210 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "211 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"211 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "212 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"212 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "213 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"213 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"213 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "215 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"213 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"213 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "235 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"214 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "221 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"215 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "216 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"216 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "217 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"217 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "223 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"218 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "219 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"219 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "220 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"220 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "229 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"221 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "222 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"222 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "224 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"223 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "224 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"224 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "225 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"225 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"228 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "229 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"229 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "230 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"230 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "231 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"231 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "232 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"232 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "233 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"233 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "234 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"234 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "235 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"237 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "238 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"238 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "239 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"239 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "240 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"240 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "241 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"241 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "242 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"242 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "243 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"242 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "244 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"242 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "247 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"242 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "264 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"243 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "250 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"244 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "245 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"245 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "246 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"246 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "252 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"247 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "248 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"248 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "249 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"249 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "258 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"250 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "251 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"251 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "253 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"252 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "253 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"253 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "254 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"254 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "255 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"255 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "256 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"256 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "257 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"257 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "258 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"258 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "259 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"259 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "260 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"260 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "261 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"261 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "262 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"262 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "263 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"263 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "264 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"266 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "267 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"267 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "268 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"268 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "269 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"269 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "270 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"270 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "271 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"271 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "274 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"274 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "275 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"275 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "281 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"276 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "277 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"277 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "278 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"278 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"281 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "282 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"282 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "283 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"283 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "284 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"284 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "285 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"285 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "286 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"286 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "287 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"287 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "288 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"288 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "289 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"289 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "290 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"290 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "291 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"291 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "292 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"292 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "293 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; 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BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"295 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "296 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"296 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "297 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 384, 3072) \n0 -> 0", style=solid]; +"297 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "298 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"298 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "299 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"299 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "301 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "302 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "305 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"300 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "322 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 384, 768) \n0 -> 1", style=solid]; +"301 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "308 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"302 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "303 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"303 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "304 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"304 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "310 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"305 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "306 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 384, 768) \n0 -> 0", style=solid]; +"306 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "307 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"307 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "316 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 384, 64) \n0 -> 1", style=solid]; +"308 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "309 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 384, 12, 64) \n0 -> 0", style=solid]; +"309 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "311 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 384, 64) \n0 -> 0", style=solid]; +"310 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "311 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 384) \n0 -> 1", style=solid]; +"311 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "312 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"312 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "313 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"313 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "314 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 384, 384) \n0 -> 0", style=solid]; +"314 BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "315 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1: 512, 2: 768, 3: 576, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 3050, 14: 3072, 15: 1926, 16: 3072, 17: 938, 18: 789, 19: 693, 20: 2995, 21: 653, 22: 3072, 23: 505})])",MACs,24535.498752,top1_acc,-77.67026307773203 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 768, 4: 576, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 2684, 13: 3050, 14: 3072, 15: 2662, 16: 2580, 17: 938, 18: 2363, 19: 2291, 20: 3072, 21: 3072, 22: 1287, 23: 2472})])",MACs,29316.612096,top1_acc,-78.14734395992902 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 512, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 966, 13: 3072, 14: 2670, 15: 1926, 16: 1807, 17: 1759, 18: 3006, 19: 3009, 20: 2078, 21: 280, 22: 332, 23: 3072})])",MACs,25089.933312,top1_acc,-78.08765642895037 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 576, 4: 576, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1898, 14: 1040, 15: 3072, 16: 3037, 17: 2521, 18: 3072, 19: 693, 20: 1175, 21: 653, 22: 665, 23: 3072})])",MACs,23738.646528,top1_acc,-77.82336660619556 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 768, 5: 448, 6: 768, 7: 512, 8: 576, 9: 768, 10: 384, 11: 384, 12: 2684, 13: 3072, 14: 1940, 15: 1926, 16: 1807, 17: 938, 18: 3006, 19: 3072, 20: 517, 21: 2913, 22: 665, 23: 3072})])",MACs,25771.180032,top1_acc,-77.93261967319509 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 2662, 16: 2580, 17: 938, 18: 2363, 19: 2291, 20: 3072, 21: 653, 22: 3072, 23: 752})])",MACs,24603.918336,top1_acc,-78.38573620135466 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 2684, 13: 3050, 14: 2670, 15: 3072, 16: 989, 17: 1759, 18: 3006, 19: 2291, 20: 2078, 21: 280, 22: 3072, 23: 505})])",MACs,24924.192768,top1_acc,-78.14010371667182 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 3041, 15: 1926, 16: 3037, 17: 3018, 18: 3006, 19: 693, 20: 1175, 21: 280, 22: 2844, 23: 505})])",MACs,25076.957184,top1_acc,-77.9679734868702 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 768, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 3072, 14: 3072, 15: 3043, 16: 3037, 17: 938, 18: 1554, 19: 2291, 20: 517, 21: 3072, 22: 332, 23: 1138})])",MACs,23777.574912,top1_acc,-77.58154859071692 +"OrderedDict([(, {0: 768, 1: 768, 2: 576, 3: 768, 4: 576, 5: 768, 6: 768, 7: 512, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 1040, 15: 1007, 16: 2580, 17: 1759, 18: 3072, 19: 693, 20: 1175, 21: 1500, 22: 332, 23: 1138})])",MACs,23435.476992,top1_acc,-77.80324067981738 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 640, 5: 768, 6: 768, 7: 768, 8: 576, 9: 768, 10: 768, 11: 384, 12: 3072, 13: 2674, 14: 3041, 15: 1926, 16: 2580, 17: 3018, 18: 789, 19: 3072, 20: 3072, 21: 2913, 22: 3072, 23: 752})])",MACs,29763.698688,top1_acc,-78.1155420022469 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 1040, 15: 3043, 16: 989, 17: 1759, 18: 3006, 19: 2291, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,25452.675072,top1_acc,-78.23638764739273 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 1759, 18: 3006, 19: 3009, 20: 1175, 21: 280, 22: 3072, 23: 505})])",MACs,24371.52768,top1_acc,-78.1186308092041 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 768, 5: 448, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 2670, 15: 3043, 16: 989, 17: 2521, 18: 789, 19: 2291, 20: 1175, 21: 2913, 22: 2844, 23: 1138})])",MACs,25868.500992,top1_acc,-78.03226261780266 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 1007, 16: 2580, 17: 3072, 18: 3072, 19: 693, 20: 1175, 21: 280, 22: 2844, 23: 2472})])",MACs,26277.838848,top1_acc,-77.87192834922726 +"OrderedDict([(, {0: 768, 1: 768, 2: 576, 3: 576, 4: 768, 5: 768, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 3072, 14: 3072, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 693, 20: 2995, 21: 3072, 22: 2844, 23: 3072})])",MACs,28743.303168,top1_acc,-77.79730427379339 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 576, 4: 704, 5: 768, 6: 576, 7: 512, 8: 576, 9: 768, 10: 768, 11: 384, 12: 3072, 13: 3072, 14: 1940, 15: 1926, 16: 2580, 17: 3072, 18: 1554, 19: 3009, 20: 1175, 21: 3072, 22: 332, 23: 505})])",MACs,26630.5536,top1_acc,-78.23889179989595 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 1908, 13: 2674, 14: 3041, 15: 3043, 16: 3037, 17: 3018, 18: 789, 19: 3009, 20: 2078, 21: 1500, 22: 2844, 23: 2472})])",MACs,27635.613696,top1_acc,-77.87696924347716 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 768, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 3072, 14: 3041, 15: 1926, 16: 989, 17: 3018, 18: 3006, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,23344.644096,top1_acc,-77.9256182127258 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 512, 6: 768, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1898, 14: 3072, 15: 2662, 16: 3072, 17: 938, 18: 2363, 19: 693, 20: 2078, 21: 2913, 22: 3072, 23: 3072})])",MACs,25999.44192,top1_acc,-77.54702135760031 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 1040, 15: 1007, 16: 3037, 17: 2521, 18: 1554, 19: 2291, 20: 517, 21: 3072, 22: 332, 23: 752})])",MACs,23663.73888,top1_acc,-77.8356382639816 +"OrderedDict([(, {0: 768, 1: 768, 2: 576, 3: 576, 4: 576, 5: 512, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 384, 12: 2684, 13: 1052, 14: 1940, 15: 3043, 16: 3072, 17: 2521, 18: 789, 19: 693, 20: 1175, 21: 3072, 22: 665, 23: 1138})])",MACs,24303.69792,top1_acc,-77.62849726654707 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 768, 4: 640, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 768, 11: 768, 12: 966, 13: 3050, 14: 1940, 15: 1007, 16: 2580, 17: 1759, 18: 3006, 19: 3009, 20: 3072, 21: 3072, 22: 1287, 23: 2472})])",MACs,27474.591744,top1_acc,-77.86456719345374 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 576, 4: 640, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3043, 16: 3072, 17: 3072, 18: 3072, 19: 2291, 20: 517, 21: 3072, 22: 3072, 23: 3072})])",MACs,27466.924032,top1_acc,-78.00815603247118 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 576, 5: 768, 6: 768, 7: 512, 8: 576, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 1898, 14: 1940, 15: 1007, 16: 1807, 17: 1759, 18: 789, 19: 693, 20: 2995, 21: 1500, 22: 665, 23: 3072})])",MACs,24205.197312,top1_acc,-77.80764200223223 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 2684, 13: 1898, 14: 1040, 15: 3043, 16: 2580, 17: 2521, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 1287, 23: 752})])",MACs,24868.159488,top1_acc,-78.15558803305451 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 768, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1898, 14: 1940, 15: 2662, 16: 3072, 17: 1759, 18: 2363, 19: 3009, 20: 2995, 21: 3072, 22: 665, 23: 505})])",MACs,26785.677312,top1_acc,-78.1345488588225 +"OrderedDict([(, {0: 768, 1: 768, 2: 576, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 3072, 15: 2662, 16: 2580, 17: 2521, 18: 789, 19: 3072, 20: 517, 21: 1500, 22: 1287, 23: 2472})])",MACs,24118.493184,top1_acc,-77.38443281644783 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 384, 12: 966, 13: 2674, 14: 1940, 15: 1926, 16: 1807, 17: 2521, 18: 1554, 19: 2291, 20: 2995, 21: 653, 22: 1287, 23: 3072})])",MACs,25673.269248,top1_acc,-77.8675014771153 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 576, 5: 768, 6: 576, 7: 512, 8: 576, 9: 768, 10: 768, 11: 768, 12: 966, 13: 3050, 14: 1940, 15: 3043, 16: 3072, 17: 3018, 18: 3072, 19: 3009, 20: 517, 21: 280, 22: 2844, 23: 3072})])",MACs,28148.760576,top1_acc,-77.94077025889828 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 576, 5: 768, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3058, 13: 2674, 14: 3041, 15: 2662, 16: 3072, 17: 1759, 18: 789, 19: 2291, 20: 2995, 21: 653, 22: 665, 23: 1138})])",MACs,26611.679232,top1_acc,-78.06279601670104 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 768, 12: 3058, 13: 2674, 14: 1940, 15: 2662, 16: 3037, 17: 3018, 18: 789, 19: 1421, 20: 2078, 21: 280, 22: 665, 23: 2472})])",MACs,25536.43008,top1_acc,-78.27802214862922 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 768, 10: 768, 11: 384, 12: 966, 13: 3050, 14: 1040, 15: 1007, 16: 3072, 17: 1759, 18: 3072, 19: 3009, 20: 1175, 21: 280, 22: 3072, 23: 2472})])",MACs,24805.04832,top1_acc,-77.71558031597361 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 768, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1898, 14: 3072, 15: 2662, 16: 3072, 17: 2521, 18: 2363, 19: 2291, 20: 2078, 21: 280, 22: 332, 23: 3072})])",MACs,26695.43424,top1_acc,-78.49416307120843 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 768, 4: 768, 5: 448, 6: 576, 7: 768, 8: 768, 9: 768, 10: 768, 11: 384, 12: 3058, 13: 1898, 14: 1940, 15: 2662, 16: 2580, 17: 2521, 18: 1554, 19: 3072, 20: 2078, 21: 1500, 22: 665, 23: 2472})])",MACs,26849.378304,top1_acc,-78.04072739758426 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 576, 4: 768, 5: 448, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 768, 12: 1908, 13: 1052, 14: 3072, 15: 1926, 16: 1807, 17: 938, 18: 3006, 19: 2291, 20: 2078, 21: 2913, 22: 665, 23: 2472})])",MACs,25273.368576,top1_acc,-77.78953680667003 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 3072, 15: 3072, 16: 989, 17: 3018, 18: 2363, 19: 693, 20: 1175, 21: 653, 22: 3072, 23: 3072})])",MACs,25958.15424,top1_acc,-78.24683274758728 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 768, 10: 768, 11: 384, 12: 1908, 13: 2674, 14: 1940, 15: 1007, 16: 1807, 17: 3072, 18: 3006, 19: 693, 20: 2078, 21: 280, 22: 3072, 23: 3072})])",MACs,26123.30496,top1_acc,-77.83492220184893 +"OrderedDict([(, {0: 768, 1: 768, 2: 576, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 3072, 15: 2662, 16: 2580, 17: 2521, 18: 789, 19: 3072, 20: 517, 21: 1500, 22: 1287, 23: 752})])",MACs,24621.023232,top1_acc,-77.8245888476137 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 576, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 1040, 15: 3072, 16: 3037, 17: 3072, 18: 3072, 19: 693, 20: 1175, 21: 653, 22: 665, 23: 3072})])",MACs,25599.541248,top1_acc,-78.02376225597935 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 768, 11: 384, 12: 3058, 13: 1898, 14: 2670, 15: 2662, 16: 3072, 17: 1759, 18: 3006, 19: 3009, 20: 2078, 21: 280, 22: 332, 23: 3072})])",MACs,26717.257728,top1_acc,-78.28282745427566 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 2674, 14: 3041, 15: 1926, 16: 1807, 17: 3018, 18: 789, 19: 3072, 20: 1175, 21: 280, 22: 3072, 23: 505})])",MACs,24791.482368,top1_acc,-77.84897658014631 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 768, 11: 384, 12: 3058, 13: 1898, 14: 1940, 15: 2662, 16: 2580, 17: 2521, 18: 1554, 19: 3072, 20: 2078, 21: 1500, 22: 1287, 23: 2472})])",MACs,27216.248832,top1_acc,-78.16536972030796 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 576, 5: 448, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 1040, 15: 1007, 16: 989, 17: 3018, 18: 3072, 19: 693, 20: 1175, 21: 1500, 22: 332, 23: 1138})])",MACs,22767.796224,top1_acc,-77.34415648828099 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 576, 4: 704, 5: 768, 6: 576, 7: 512, 8: 576, 9: 768, 10: 768, 11: 384, 12: 3072, 13: 3072, 14: 1940, 15: 1926, 16: 3037, 17: 3072, 18: 1554, 19: 3009, 20: 1175, 21: 3072, 22: 332, 23: 1138})])",MACs,27273.46176,top1_acc,-78.2654357067602 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 768, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 768, 12: 3058, 13: 2674, 14: 1940, 15: 2662, 16: 3037, 17: 3018, 18: 2363, 19: 693, 20: 2078, 21: 280, 22: 3072, 23: 3072})])",MACs,28092.137472,top1_acc,-78.17221709700698 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 989, 17: 3018, 18: 3006, 19: 693, 20: 1175, 21: 653, 22: 3072, 23: 3072})])",MACs,26723.155968,top1_acc,-78.27164899868205 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 576, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 384, 12: 1908, 13: 1898, 14: 1040, 15: 3072, 16: 3037, 17: 2521, 18: 3072, 19: 693, 20: 1175, 21: 653, 22: 665, 23: 3072})])",MACs,24682.364928,top1_acc,-78.02476754981885 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 768, 4: 576, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3058, 13: 3050, 14: 3072, 15: 2662, 16: 2580, 17: 938, 18: 789, 19: 2291, 20: 3072, 21: 280, 22: 1287, 23: 2472})])",MACs,26962.034688,top1_acc,-78.0456488952168 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 1040, 15: 1007, 16: 2580, 17: 938, 18: 1554, 19: 2291, 20: 517, 21: 3072, 22: 332, 23: 752})])",MACs,22932.35712,top1_acc,-77.43936836139619 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,20471.021568,top1_acc,-78.19753103893949 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1052, 14: 3041, 15: 1007, 16: 2580, 17: 3018, 18: 3072, 19: 693, 20: 1175, 21: 280, 22: 3072, 23: 2472})])",MACs,27400.27392,top1_acc,-77.98506043799317 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 2670, 15: 3043, 16: 989, 17: 1759, 18: 3006, 19: 2291, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,26414.088192,top1_acc,-78.27613942234026 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 384, 12: 966, 13: 2674, 14: 1940, 15: 1926, 16: 1807, 17: 2521, 18: 1554, 19: 2291, 20: 2995, 21: 653, 22: 1287, 23: 3072})])",MACs,26333.872128,top1_acc,-77.91021961766769 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 704, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1898, 14: 1940, 15: 3043, 16: 2580, 17: 2521, 18: 3006, 19: 3072, 20: 2995, 21: 280, 22: 1287, 23: 3072})])",MACs,28575.203328,top1_acc,-78.61168643485765 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 2363, 19: 693, 20: 1175, 21: 653, 22: 3072, 23: 3072})])",MACs,28063.236096,top1_acc,-78.46654170611788 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 3072, 14: 3072, 15: 2662, 16: 2580, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 1500, 22: 1287, 23: 752})])",MACs,28050.849792,top1_acc,-78.3600573694138 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1898, 14: 1040, 15: 1007, 16: 3037, 17: 2521, 18: 1554, 19: 2291, 20: 517, 21: 3072, 22: 332, 23: 2472})])",MACs,23161.208832,top1_acc,-77.70897967024283 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 576, 4: 576, 5: 512, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 384, 12: 1908, 13: 1052, 14: 3072, 15: 1007, 16: 2580, 17: 2521, 18: 3072, 19: 693, 20: 1175, 21: 280, 22: 2844, 23: 2472})])",MACs,24416.944128,top1_acc,-77.72090877108256 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 966, 13: 3072, 14: 3072, 15: 1926, 16: 1807, 17: 2521, 18: 2363, 19: 2291, 20: 2078, 21: 280, 22: 332, 23: 3072})])",MACs,25068.109824,top1_acc,-78.19061716086303 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 2580, 17: 1759, 18: 3006, 19: 3009, 20: 3072, 21: 2913, 22: 3072, 23: 752})])",MACs,29343.744,top1_acc,-78.42375175520324 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 768, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 2684, 13: 1898, 14: 1040, 15: 3043, 16: 2580, 17: 2521, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 665, 23: 752})])",MACs,24501.28896,top1_acc,-78.26496446789018 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 3072, 14: 3041, 15: 1926, 16: 2580, 17: 1759, 18: 3006, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,24012.324864,top1_acc,-77.98124059544182 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 768, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 3072, 14: 3072, 15: 3043, 16: 2580, 17: 938, 18: 1554, 19: 2291, 20: 517, 21: 3072, 22: 332, 23: 505})])",MACs,23134.666752,top1_acc,-77.4740861134676 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 704, 5: 512, 6: 768, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1898, 14: 3072, 15: 2662, 16: 3072, 17: 938, 18: 789, 19: 1421, 20: 2078, 21: 2913, 22: 665, 23: 2472})])",MACs,23443.734528,top1_acc,-77.56640898866473 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 1040, 15: 3043, 16: 989, 17: 1759, 18: 2363, 19: 2291, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,24687.673344,top1_acc,-77.88585143771611 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 3041, 15: 1926, 16: 3037, 17: 3018, 18: 3006, 19: 693, 20: 1175, 21: 280, 22: 2844, 23: 505})])",MACs,24133.238784,top1_acc,-77.87572143546193 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 768, 12: 2684, 13: 2674, 14: 1940, 15: 2662, 16: 3037, 17: 3018, 18: 2363, 19: 1421, 20: 2078, 21: 3072, 22: 665, 23: 2472})])",MACs,27891.007488,top1_acc,-78.24811062317897 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 2662, 16: 3037, 17: 2521, 18: 2363, 19: 2291, 20: 3072, 21: 653, 22: 3072, 23: 752})])",MACs,25335.300096,top1_acc,-78.40505762610745 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 576, 4: 576, 5: 768, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 768, 12: 966, 13: 3072, 14: 3072, 15: 3043, 16: 3037, 17: 1759, 18: 3006, 19: 2291, 20: 517, 21: 3072, 22: 3072, 23: 1138})])",MACs,27678.081024,top1_acc,-77.76550470965897 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 576, 9: 768, 10: 768, 11: 384, 12: 3072, 13: 2674, 14: 3072, 15: 1926, 16: 2580, 17: 3072, 18: 789, 19: 3072, 20: 3072, 21: 2913, 22: 2844, 23: 752})])",MACs,28641.263616,top1_acc,-77.81966596343226 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 2684, 13: 3050, 14: 1040, 15: 3072, 16: 989, 17: 1759, 18: 3006, 19: 2291, 20: 2078, 21: 280, 22: 3072, 23: 505})])",MACs,23962.779648,top1_acc,-77.89298571888119 +"OrderedDict([(, {0: 768, 1: 768, 2: 576, 3: 576, 4: 704, 5: 512, 6: 576, 7: 512, 8: 576, 9: 768, 10: 768, 11: 384, 12: 3072, 13: 3072, 14: 1940, 15: 1926, 16: 2580, 17: 3072, 18: 1554, 19: 3009, 20: 1175, 21: 3072, 22: 332, 23: 505})])",MACs,25969.95072,top1_acc,-78.11954292669367 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 768, 7: 512, 8: 576, 9: 768, 10: 768, 11: 384, 12: 2684, 13: 1898, 14: 1040, 15: 1007, 16: 1807, 17: 1759, 18: 789, 19: 693, 20: 2078, 21: 1500, 22: 665, 23: 752})])",MACs,20498.153472,top1_acc,-77.17593387945388 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 768, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 3072, 15: 2662, 16: 989, 17: 2521, 18: 2363, 19: 2291, 20: 2078, 21: 280, 22: 332, 23: 3072})])",MACs,24590.352384,top1_acc,-78.20080428126921 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 768, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 3041, 15: 1926, 16: 989, 17: 2521, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 2472})])",MACs,19412.287488,top1_acc,-76.7054927918255 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 576, 5: 768, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 768, 12: 966, 13: 3050, 14: 1040, 15: 1007, 16: 2580, 17: 1759, 18: 3006, 19: 3009, 20: 3072, 21: 653, 22: 665, 23: 3072})])",MACs,24843.38688,top1_acc,-77.70056129642998 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 576, 4: 640, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1898, 14: 1940, 15: 3072, 16: 3037, 17: 2521, 18: 3072, 19: 693, 20: 1175, 21: 3072, 22: 1287, 23: 1138})])",MACs,25583.026176,top1_acc,-78.05667289550004 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 576, 5: 448, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1898, 14: 1040, 15: 1007, 16: 1807, 17: 3018, 18: 3072, 19: 693, 20: 1175, 21: 1500, 22: 332, 23: 505})])",MACs,22310.682624,top1_acc,-77.62489361916187 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 704, 5: 512, 6: 768, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 3072, 14: 3072, 15: 2662, 16: 3072, 17: 3072, 18: 789, 19: 1421, 20: 2078, 21: 2913, 22: 665, 23: 2472})])",MACs,25677.98784,top1_acc,-77.65770387913935 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 576, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3072, 14: 3041, 15: 1926, 16: 2580, 17: 1759, 18: 3006, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,25247.41632,top1_acc,-77.82395122642511 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 768, 11: 384, 12: 966, 13: 1898, 14: 2670, 15: 2662, 16: 3072, 17: 1759, 18: 3006, 19: 3009, 20: 517, 21: 280, 22: 332, 23: 3072})])",MACs,24751.374336,top1_acc,-77.78774416256988 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 704, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1898, 14: 1940, 15: 2662, 16: 2580, 17: 2521, 18: 3006, 19: 3072, 20: 2995, 21: 280, 22: 665, 23: 3072})])",MACs,27700.494336,top1_acc,-78.54458300887298 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 576, 4: 640, 5: 768, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 3072, 14: 1040, 15: 1007, 16: 3037, 17: 938, 18: 1554, 19: 2291, 20: 517, 21: 3072, 22: 332, 23: 1138})])",MACs,21850.03008,top1_acc,-77.49302483829638 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 1759, 18: 3006, 19: 2291, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,28116.91008,top1_acc,-78.48251143144982 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 768, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 2684, 13: 1898, 14: 3072, 15: 3043, 16: 2580, 17: 2521, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 665, 23: 3072})])",MACs,27351.318528,top1_acc,-78.36514407667666 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 2580, 17: 938, 18: 2363, 19: 2291, 20: 3072, 21: 653, 22: 3072, 23: 752})])",MACs,25016.795136,top1_acc,-78.36915887714079 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 768, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 384, 12: 1908, 13: 3072, 14: 1040, 15: 3072, 16: 1807, 17: 2521, 18: 3072, 19: 693, 20: 2078, 21: 653, 22: 665, 23: 3072})])",MACs,24710.086656,top1_acc,-78.11713137218885 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 768, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 3072, 14: 3072, 15: 3043, 16: 3037, 17: 3018, 18: 789, 19: 2291, 20: 517, 21: 280, 22: 332, 23: 1138})])",MACs,23000.776704,top1_acc,-77.50918140808929 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 768, 11: 384, 12: 2684, 13: 1898, 14: 1040, 15: 2662, 16: 3072, 17: 1759, 18: 3072, 19: 693, 20: 2078, 21: 280, 22: 332, 23: 3072})])",MACs,24208.146432,top1_acc,-77.85548412893947 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3043, 16: 989, 17: 1759, 18: 3006, 19: 2291, 20: 2078, 21: 280, 22: 1287, 23: 752})])",MACs,25598.3616,top1_acc,-78.27775755232359 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 384, 12: 2684, 13: 3050, 14: 3041, 15: 3072, 16: 989, 17: 1759, 18: 2363, 19: 2291, 20: 2078, 21: 280, 22: 3072, 23: 505})])",MACs,25046.87616,top1_acc,-77.9910911588125 +"OrderedDict([(, {0: 768, 1: 768, 2: 576, 3: 576, 4: 576, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 1040, 15: 1007, 16: 2580, 17: 1759, 18: 3072, 19: 693, 20: 2078, 21: 1500, 22: 332, 23: 1138})])",MACs,23024.369664,top1_acc,-77.71422477334346 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1898, 14: 1040, 15: 1007, 16: 3037, 17: 2521, 18: 1554, 19: 2291, 20: 1175, 21: 3072, 22: 3072, 23: 2472})])",MACs,25165.430784,top1_acc,-77.82208630378702 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,20928.135168,top1_acc,-78.140317191191 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 576, 4: 704, 5: 768, 6: 576, 7: 512, 8: 576, 9: 768, 10: 768, 11: 384, 12: 3072, 13: 1898, 14: 1940, 15: 1926, 16: 2580, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 3072, 22: 332, 23: 505})])",MACs,24396.300288,top1_acc,-77.88112882411048 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 1759, 18: 3006, 19: 3009, 20: 1175, 21: 280, 22: 3072, 23: 505})])",MACs,23136.436224,top1_acc,-78.20346127582795 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 3058, 13: 1052, 14: 3041, 15: 1926, 16: 989, 17: 2521, 18: 789, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 2472})])",MACs,21378.17088,top1_acc,-77.47726646344098 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 768, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 768, 12: 3058, 13: 2674, 14: 1940, 15: 3043, 16: 3037, 17: 3018, 18: 789, 19: 1421, 20: 2078, 21: 280, 22: 1287, 23: 2472})])",MACs,26411.139072,top1_acc,-78.13701621331874 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 768, 4: 576, 5: 768, 6: 768, 7: 512, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 3072, 15: 3043, 16: 2580, 17: 1759, 18: 3072, 19: 693, 20: 1175, 21: 1500, 22: 332, 23: 1138})])",MACs,25363.021824,top1_acc,-77.92036055542833 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 2670, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 693, 20: 1175, 21: 280, 22: 3072, 23: 3072})])",MACs,26360.414208,top1_acc,-78.28888512746433 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 768, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1898, 14: 1040, 15: 2662, 16: 3072, 17: 2521, 18: 2363, 19: 2291, 20: 2078, 21: 280, 22: 332, 23: 752})])",MACs,23845.404672,top1_acc,-78.17825915967687 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 640, 5: 768, 6: 768, 7: 512, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 2662, 16: 2580, 17: 1759, 18: 3006, 19: 3009, 20: 3072, 21: 2913, 22: 3072, 23: 752})])",MACs,28930.8672,top1_acc,-78.40569750397506 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 640, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1898, 14: 3072, 15: 1926, 16: 3037, 17: 2521, 18: 2363, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 3072})])",MACs,25040.388096,top1_acc,-78.09308033250382 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 768, 12: 3058, 13: 2674, 14: 1940, 15: 2662, 16: 3037, 17: 938, 18: 1554, 19: 1421, 20: 2078, 21: 3072, 22: 665, 23: 2472})])",MACs,26313.228288,top1_acc,-78.00808432146668 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 768, 7: 512, 8: 576, 9: 768, 10: 768, 11: 384, 12: 3058, 13: 1898, 14: 2670, 15: 1007, 16: 1807, 17: 1759, 18: 789, 19: 3009, 20: 2078, 21: 1500, 22: 665, 23: 752})])",MACs,23046.193152,top1_acc,-77.97677326349819 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 3072, 14: 2670, 15: 2662, 16: 2580, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 1500, 22: 3072, 23: 752})])",MACs,28866.576384,top1_acc,-78.34216627412434 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 1940, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 693, 20: 1175, 21: 653, 22: 3072, 23: 3072})])",MACs,27491.69664,top1_acc,-78.27705512749117 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 768, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 3072, 14: 3041, 15: 1926, 16: 2580, 17: 1759, 18: 3006, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,24423.432192,top1_acc,-78.11037746706666 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 989, 17: 3018, 18: 3006, 19: 693, 20: 517, 21: 653, 22: 332, 23: 3072})])",MACs,24718.934016,top1_acc,-78.05198186793311 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1898, 14: 3041, 15: 3043, 16: 1807, 17: 2521, 18: 1554, 19: 1421, 20: 3072, 21: 280, 22: 332, 23: 2472})])",MACs,23786.422272,top1_acc,-77.95961129312956 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 640, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1898, 14: 3072, 15: 3043, 16: 3037, 17: 938, 18: 1554, 19: 2291, 20: 517, 21: 3072, 22: 332, 23: 2472})])",MACs,24626.921472,top1_acc,-77.53792031988783 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 768, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1898, 14: 3072, 15: 2662, 16: 3072, 17: 938, 18: 2363, 19: 2291, 20: 2078, 21: 280, 22: 332, 23: 2472})])",MACs,25030.361088,top1_acc,-78.16668441929754 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 768, 12: 3058, 13: 3072, 14: 3072, 15: 3043, 16: 2580, 17: 938, 18: 1554, 19: 2291, 20: 517, 21: 1500, 22: 332, 23: 505})])",MACs,23535.747072,top1_acc,-77.73914134246671 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 1926, 16: 2580, 17: 1759, 18: 2363, 19: 2291, 20: 2078, 21: 280, 22: 332, 23: 3072})])",MACs,26222.395392,top1_acc,-78.35334869061231 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 3072, 14: 1040, 15: 1007, 16: 3037, 17: 2521, 18: 1554, 19: 2291, 20: 517, 21: 3072, 22: 332, 23: 1138})])",MACs,22311.862272,top1_acc,-77.59304878242682 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 704, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1898, 14: 3072, 15: 2662, 16: 3072, 17: 2521, 18: 789, 19: 1421, 20: 2078, 21: 2913, 22: 665, 23: 3072})])",MACs,25108.80768,top1_acc,-77.83055042180594 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 576, 5: 768, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 384, 12: 966, 13: 1898, 14: 1040, 15: 1007, 16: 989, 17: 3018, 18: 3072, 19: 693, 20: 1175, 21: 3072, 22: 332, 23: 1138})])",MACs,22366.715904,top1_acc,-77.19795199066033 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 576, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 1807, 17: 1759, 18: 3006, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,22405.644288,top1_acc,-78.29176207766042 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 576, 5: 512, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 2363, 19: 2291, 20: 2078, 21: 1500, 22: 3072, 23: 752})])",MACs,22931.767296,top1_acc,-77.8266145238085 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 704, 5: 448, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1898, 14: 1040, 15: 1007, 16: 1807, 17: 3018, 18: 3072, 19: 3009, 20: 2078, 21: 1500, 22: 1287, 23: 505})])",MACs,24961.35168,top1_acc,-78.01748107231435 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 989, 17: 2521, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 2472})])",MACs,23451.40224,top1_acc,-78.15285154152146 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 704, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 1898, 14: 1940, 15: 3043, 16: 2580, 17: 2521, 18: 3006, 19: 3072, 20: 2995, 21: 280, 22: 1287, 23: 3072})])",MACs,27537.113088,top1_acc,-78.3785740018932 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 1807, 17: 1759, 18: 3006, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,24152.702976,top1_acc,-78.19046328893202 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,25314.066432,top1_acc,-78.6514470628762 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 3072, 14: 3041, 15: 1926, 16: 989, 17: 3018, 18: 3006, 19: 693, 20: 2078, 21: 3072, 22: 332, 23: 752})])",MACs,24582.684672,top1_acc,-77.61647707570668 +"OrderedDict([(, {0: 768, 1: 768, 2: 576, 3: 576, 4: 768, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3072, 14: 3041, 15: 1007, 16: 2580, 17: 1759, 18: 3072, 19: 693, 20: 2078, 21: 1500, 22: 332, 23: 1138})])",MACs,25180.176384,top1_acc,-77.77797839056821 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 1759, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,20846.149632,top1_acc,-78.12626513511245 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1898, 14: 3041, 15: 2662, 16: 2580, 17: 2521, 18: 789, 19: 693, 20: 2995, 21: 653, 22: 332, 23: 3072})])",MACs,25379.536896,top1_acc,-77.7169681863635 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 768, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 3050, 14: 1040, 15: 2662, 16: 3072, 17: 2521, 18: 3006, 19: 2291, 20: 2078, 21: 280, 22: 1287, 23: 752})])",MACs,25467.420672,top1_acc,-78.34330518623062 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 768, 6: 576, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 3072, 14: 3041, 15: 3043, 16: 3037, 17: 2521, 18: 1554, 19: 1421, 20: 517, 21: 280, 22: 332, 23: 2472})])",MACs,23980.474368,top1_acc,-77.83473666732272 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1898, 14: 1940, 15: 3043, 16: 2580, 17: 2521, 18: 3006, 19: 693, 20: 1175, 21: 280, 22: 1287, 23: 3072})])",MACs,25909.788672,top1_acc,-77.89556911508659 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 576, 4: 640, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 966, 13: 3072, 14: 1040, 15: 1007, 16: 3037, 17: 1759, 18: 1554, 19: 2291, 20: 517, 21: 3072, 22: 332, 23: 1138})])",MACs,23466.737664,top1_acc,-77.71196878301035 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 3072, 15: 3072, 16: 3037, 17: 2521, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 3072, 23: 3072})])",MACs,27272.282112,top1_acc,-78.15396264890484 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,29320.15104,top1_acc,-78.84002229647037 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,21462.515712,top1_acc,-78.23145260383573 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1898, 14: 3041, 15: 2662, 16: 1807, 17: 2521, 18: 1554, 19: 1421, 20: 3072, 21: 280, 22: 3072, 23: 2472})])",MACs,24517.214208,top1_acc,-77.97718797269793 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 576, 9: 768, 10: 768, 11: 768, 12: 2684, 13: 1898, 14: 1040, 15: 2662, 16: 2580, 17: 1759, 18: 789, 19: 693, 20: 3072, 21: 653, 22: 665, 23: 752})])",MACs,22583.181312,top1_acc,-77.53357842882484 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 3072, 14: 3072, 15: 2662, 16: 2580, 17: 3018, 18: 3006, 19: 1421, 20: 1175, 21: 1500, 22: 332, 23: 752})])",MACs,25792.413696,top1_acc,-78.1021620654469 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,16889.020416,top1_acc,-76.83128504760958 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 2684, 13: 1898, 14: 3072, 15: 3043, 16: 2580, 17: 2521, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 665, 23: 3072})])",MACs,28389.408768,top1_acc,-78.52216513984783 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,24435.228672,top1_acc,-78.31528599348421 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 2670, 15: 2662, 16: 989, 17: 938, 18: 2363, 19: 693, 20: 3072, 21: 280, 22: 3072, 23: 3072})])",MACs,25650.266112,top1_acc,-78.01282846708037 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1898, 14: 1040, 15: 1007, 16: 3037, 17: 2521, 18: 1554, 19: 2291, 20: 517, 21: 653, 22: 332, 23: 2472})])",MACs,21923.168256,top1_acc,-77.63286685594899 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 576, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1898, 14: 1040, 15: 1926, 16: 2580, 17: 1759, 18: 3006, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,21856.518144,top1_acc,-78.09718639939125 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 3006, 19: 3009, 20: 1175, 21: 280, 22: 3072, 23: 505})])",MACs,23218.42176,top1_acc,-78.26060781834441 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 704, 5: 768, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 1926, 16: 989, 17: 2521, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 665, 23: 2472})])",MACs,23699.12832,top1_acc,-78.01135260629086 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 3072, 15: 3043, 16: 989, 17: 1759, 18: 2363, 19: 2291, 20: 2078, 21: 280, 22: 332, 23: 752})])",MACs,23976.3456,top1_acc,-77.98840620577775 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1898, 14: 1040, 15: 1007, 16: 1807, 17: 2521, 18: 1554, 19: 2291, 20: 3072, 21: 3072, 22: 332, 23: 1138})])",MACs,22117.810176,top1_acc,-77.79473540773985 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 2670, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 3072, 20: 2995, 21: 280, 22: 3072, 23: 3072})])",MACs,29025.828864,top1_acc,-78.71797205833272 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 576, 4: 576, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1898, 14: 1040, 15: 1007, 16: 2580, 17: 938, 18: 3072, 19: 693, 20: 2078, 21: 1500, 22: 332, 23: 1138})])",MACs,21407.66208,top1_acc,-77.62469539772765 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1898, 14: 1040, 15: 1007, 16: 3072, 17: 3018, 18: 2363, 19: 2291, 20: 517, 21: 3072, 22: 332, 23: 2472})])",MACs,23952.162816,top1_acc,-77.75779452807832 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 3072, 14: 3072, 15: 2662, 16: 2580, 17: 1759, 18: 3006, 19: 2291, 20: 2078, 21: 1500, 22: 1287, 23: 752})])",MACs,26847.608832,top1_acc,-78.19122356609537 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 2521, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 2472})])",MACs,18420.793344,top1_acc,-76.82623022276856 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 576, 4: 640, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1898, 14: 1040, 15: 1007, 16: 3072, 17: 2521, 18: 2363, 19: 2291, 20: 517, 21: 3072, 22: 332, 23: 752})])",MACs,22172.663808,top1_acc,-77.70882804189473 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 768, 6: 576, 7: 512, 8: 576, 9: 768, 10: 768, 11: 384, 12: 3058, 13: 3072, 14: 1040, 15: 2662, 16: 3037, 17: 938, 18: 1554, 19: 2291, 20: 2078, 21: 280, 22: 332, 23: 1138})])",MACs,23522.770944,top1_acc,-77.99213009301502 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 1040, 15: 2662, 16: 989, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,23314.563072,top1_acc,-77.91680370513131 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 576, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 3072, 19: 693, 20: 1175, 21: 1500, 22: 332, 23: 505})])",MACs,19924.25472,top1_acc,-77.63965462816525 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 2662, 16: 989, 17: 2521, 18: 2363, 19: 2291, 20: 3072, 21: 653, 22: 332, 23: 752})])",MACs,21850.619904,top1_acc,-78.03151315977648 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1898, 14: 3072, 15: 3043, 16: 2580, 17: 2521, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 1287, 23: 3072})])",MACs,29079.502848,top1_acc,-78.68123830743802 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 2662, 16: 2580, 17: 2521, 18: 2363, 19: 693, 20: 3072, 21: 653, 22: 332, 23: 2472})])",MACs,22853.910528,top1_acc,-77.71935781291954 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 1040, 15: 3043, 16: 989, 17: 1759, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,26668.302336,top1_acc,-78.28118307618752 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,24294.260736,top1_acc,-78.42980845233825 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,29170.335744,top1_acc,-78.69849238835438 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,21917.85984,top1_acc,-78.28085130935372 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 768, 4: 576, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1898, 14: 1040, 15: 1007, 16: 1807, 17: 1759, 18: 3006, 19: 693, 20: 1175, 21: 1500, 22: 332, 23: 752})])",MACs,21108.621312,top1_acc,-77.70834704849071 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 576, 4: 576, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1898, 14: 1040, 15: 1007, 16: 2580, 17: 1759, 18: 3072, 19: 693, 20: 2078, 21: 1500, 22: 665, 23: 1138})])",MACs,22088.318976,top1_acc,-77.85946862514541 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 2684, 13: 1052, 14: 3041, 15: 3043, 16: 2580, 17: 1759, 18: 3006, 19: 3009, 20: 3072, 21: 280, 22: 3072, 23: 3072})])",MACs,29391.519744,top1_acc,-78.48743997397817 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 2521, 18: 2363, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,22653.370368,top1_acc,-78.13854775945585 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 3050, 14: 3072, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,23131.127808,top1_acc,-77.97238981115294 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 768, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 768, 12: 966, 13: 1052, 14: 3041, 15: 1926, 16: 989, 17: 2521, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 2472})])",MACs,19978.518528,top1_acc,-76.72007204094567 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 2291, 20: 517, 21: 653, 22: 3072, 23: 505})])",MACs,22241.673216,top1_acc,-77.9707700219879 +"OrderedDict([(, {0: 576, 1: 768, 2: 576, 3: 576, 4: 576, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 1898, 14: 1940, 15: 3043, 16: 2580, 17: 938, 18: 3072, 19: 3072, 20: 2078, 21: 1500, 22: 332, 23: 1138})])",MACs,25117.065216,top1_acc,-78.2824582070509 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 768, 10: 768, 11: 384, 12: 3058, 13: 1052, 14: 3041, 15: 1926, 16: 3037, 17: 2521, 18: 789, 19: 693, 20: 2078, 21: 653, 22: 3072, 23: 2472})])",MACs,24862.851072,top1_acc,-77.76420674893168 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 2684, 13: 1898, 14: 1940, 15: 3043, 16: 2580, 17: 2521, 18: 3006, 19: 3072, 20: 2995, 21: 280, 22: 665, 23: 3072})])",MACs,27885.109248,top1_acc,-78.35054377115078 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 768, 5: 448, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 2291, 20: 517, 21: 653, 22: 3072, 23: 752})])",MACs,20170.801152,top1_acc,-77.55737927479676 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 2670, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 2291, 20: 2995, 21: 280, 22: 3072, 23: 3072})])",MACs,27810.2016,top1_acc,-78.53422701894199 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 448, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 2521, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 2472})])",MACs,19553.255424,top1_acc,-76.83487552621993 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 576, 4: 640, 5: 768, 6: 576, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 3072, 14: 1040, 15: 1007, 16: 3037, 17: 938, 18: 1554, 19: 2291, 20: 517, 21: 3072, 22: 332, 23: 752})])",MACs,21999.845376,top1_acc,-77.57283843439733 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 1138})])",MACs,15442.182144,top1_acc,-76.76916882561892 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1926, 16: 2580, 17: 938, 18: 3072, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 505})])",MACs,20672.151552,top1_acc,-77.44865052239214 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 768, 7: 512, 8: 576, 9: 768, 10: 768, 11: 384, 12: 2684, 13: 1898, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 2078, 21: 1500, 22: 332, 23: 752})])",MACs,19817.496576,top1_acc,-77.34367320624702 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 1898, 14: 1940, 15: 2662, 16: 2580, 17: 2521, 18: 3006, 19: 3072, 20: 2078, 21: 2913, 22: 665, 23: 752})])",MACs,28854.19008,top1_acc,-78.32413239561521 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 2662, 16: 3037, 17: 1759, 18: 1554, 19: 2291, 20: 3072, 21: 280, 22: 3072, 23: 752})])",MACs,23528.07936,top1_acc,-78.38946739057134 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,26660.0448,top1_acc,-78.73945747935844 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,16322.789376,top1_acc,-76.76852622011144 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 576, 4: 640, 5: 768, 6: 768, 7: 512, 8: 576, 9: 320, 10: 768, 11: 768, 12: 966, 13: 3072, 14: 1040, 15: 1007, 16: 3037, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 3072, 22: 332, 23: 1138})])",MACs,24043.585536,top1_acc,-77.98079925207654 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 704, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 1040, 15: 1007, 16: 2580, 17: 2521, 18: 3006, 19: 693, 20: 2995, 21: 280, 22: 1287, 23: 3072})])",MACs,24865.800192,top1_acc,-77.81203154897382 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 768, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 2684, 13: 1898, 14: 3041, 15: 3043, 16: 2580, 17: 2521, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 665, 23: 3072})])",MACs,28182.380544,top1_acc,-78.17751062428619 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 704, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 2662, 16: 2580, 17: 1759, 18: 3006, 19: 3072, 20: 2995, 21: 280, 22: 665, 23: 3072})])",MACs,29083.041792,top1_acc,-78.43509323083939 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 576, 5: 768, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1898, 14: 1040, 15: 1926, 16: 2580, 17: 2521, 18: 3006, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 3072})])",MACs,23391.240192,top1_acc,-77.84632484920735 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 576, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 1500, 22: 332, 23: 505})])",MACs,21473.722368,top1_acc,-78.0351138824875 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 768, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 2521, 18: 3006, 19: 2291, 20: 1175, 21: 280, 22: 3072, 23: 752})])",MACs,26218.266624,top1_acc,-78.52270622157017 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,16570.515456,top1_acc,-76.85482514051004 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1898, 14: 1940, 15: 1926, 16: 2580, 17: 2521, 18: 2363, 19: 2291, 20: 2078, 21: 280, 22: 332, 23: 3072})])",MACs,24839.847936,top1_acc,-78.00162602879831 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 576, 5: 768, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 3072, 15: 2662, 16: 989, 17: 1759, 18: 2363, 19: 2291, 20: 2078, 21: 280, 22: 332, 23: 752})])",MACs,23055.630336,top1_acc,-78.16995335928566 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 989, 17: 1759, 18: 3072, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,19296.681984,top1_acc,-77.71633535260403 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 768, 5: 768, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 3072, 20: 2995, 21: 653, 22: 1287, 23: 3072})])",MACs,27671.003136,top1_acc,-78.714870635587 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 3072, 17: 3072, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,25590.104064,top1_acc,-78.57704019720346 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 2580, 17: 938, 18: 2363, 19: 693, 20: 3072, 21: 280, 22: 332, 23: 752})])",MACs,21955.018752,top1_acc,-77.99042679865357 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 2291, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,17513.054208,top1_acc,-77.13032663104829 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,20051.06688,top1_acc,-78.22677176965368 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,17151.492096,top1_acc,-77.05241877666758 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 768, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1898, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 3006, 19: 3072, 20: 2995, 21: 653, 22: 1287, 23: 3072})])",MACs,28899.606528,top1_acc,-78.64284876235192 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 2684, 13: 1898, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,19223.543808,top1_acc,-77.25234343287727 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 3009, 20: 1175, 21: 280, 22: 3072, 23: 3072})])",MACs,26602.242048,top1_acc,-78.37246986808775 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1898, 14: 1940, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2995, 21: 653, 22: 3072, 23: 3072})])",MACs,30542.856192,top1_acc,-78.63408085682 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 768, 4: 576, 5: 512, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 384, 12: 2684, 13: 1898, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 2078, 21: 1500, 22: 332, 23: 752})])",MACs,20855.586816,top1_acc,-77.1542439058713 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 768, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1898, 14: 1040, 15: 1926, 16: 989, 17: 2521, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 3072})])",MACs,19273.678848,top1_acc,-76.69688321304395 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 3072, 15: 2662, 16: 3072, 17: 938, 18: 2363, 19: 3009, 20: 2078, 21: 280, 22: 332, 23: 505})])",MACs,25811.877888,top1_acc,-78.3540769081781 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 3072, 17: 938, 18: 789, 19: 3009, 20: 517, 21: 653, 22: 3072, 23: 505})])",MACs,23394.189312,top1_acc,-77.80030788280789 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,15756.558336,top1_acc,-76.81642600873026 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,18291.032064,top1_acc,-77.59262728933587 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,22291.218432,top1_acc,-78.29557767496303 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 938, 18: 3006, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,28056.158208,top1_acc,-78.31951598858294 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 768, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 989, 17: 1759, 18: 3072, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 1138})])",MACs,22358.458368,top1_acc,-77.99558141865563 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 2662, 16: 3037, 17: 2521, 18: 2363, 19: 693, 20: 3072, 21: 653, 22: 3072, 23: 752})])",MACs,24392.761344,top1_acc,-78.34794590245313 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 517, 21: 280, 22: 332, 23: 1138})])",MACs,16742.744064,top1_acc,-76.92635232063543 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 3072, 19: 693, 20: 517, 21: 1500, 22: 332, 23: 505})])",MACs,18214.944768,top1_acc,-77.47733338513804 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 768, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 2684, 13: 1898, 14: 1040, 15: 3043, 16: 2580, 17: 2521, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 665, 23: 752})])",MACs,23272.685568,top1_acc,-78.265435908996 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 448, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 2521, 18: 789, 19: 693, 20: 517, 21: 1500, 22: 332, 23: 2472})])",MACs,20147.208192,top1_acc,-77.02085366189513 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 1759, 18: 1554, 19: 3072, 20: 2995, 21: 280, 22: 332, 23: 1138})])",MACs,23269.736448,top1_acc,-78.25768622090199 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 2580, 17: 2521, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 665, 23: 752})])",MACs,23817.682944,top1_acc,-78.32234572252675 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 3072, 19: 693, 20: 1175, 21: 1500, 22: 332, 23: 505})])",MACs,18886.16448,top1_acc,-77.58854304664416 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 704, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 1052, 14: 2670, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 3072, 20: 2995, 21: 280, 22: 3072, 23: 2472})])",MACs,28181.200896,top1_acc,-78.50332453420378 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 2521, 18: 1554, 19: 2291, 20: 2078, 21: 653, 22: 3072, 23: 3072})])",MACs,25318.785024,top1_acc,-78.4013193081582 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,17222.8608,top1_acc,-77.41540504691936 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 989, 17: 1759, 18: 3072, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,20429.144064,top1_acc,-77.56578602021848 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 693, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,18750.50496,top1_acc,-77.54284995085929 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,15068.823552,top1_acc,-76.75271547386292 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 576, 9: 768, 10: 768, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 2662, 16: 2580, 17: 938, 18: 2363, 19: 2291, 20: 3072, 21: 653, 22: 3072, 23: 752})])",MACs,25170.149376,top1_acc,-78.29251470949728 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,18473.28768,top1_acc,-77.39596642742349 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1898, 14: 1940, 15: 3043, 16: 2580, 17: 2521, 18: 3072, 19: 3072, 20: 2995, 21: 280, 22: 1287, 23: 3072})])",MACs,28897.247232,top1_acc,-78.70452345506658 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 448, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 2521, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 2472})])",MACs,18987.024384,top1_acc,-76.92720595659841 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,18867.879936,top1_acc,-77.97550134677836 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 989, 17: 1759, 18: 3006, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,18974.63808,top1_acc,-77.54706312357824 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 2472})])",MACs,17015.242752,top1_acc,-76.86144696625041 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 2521, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 1138})])",MACs,16847.732736,top1_acc,-76.72481220674392 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,21682.520064,top1_acc,-78.44295737646502 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,21347.500032,top1_acc,-78.21717607855369 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 966, 13: 1898, 14: 1040, 15: 3043, 16: 989, 17: 3018, 18: 789, 19: 693, 20: 2995, 21: 653, 22: 332, 23: 1138})])",MACs,21773.35296,top1_acc,-77.42521813292142 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 768, 5: 768, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 3072, 20: 2995, 21: 653, 22: 3072, 23: 3072})])",MACs,28723.838976,top1_acc,-78.7044420941177 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 2472})])",MACs,17109.614592,top1_acc,-76.82345111081733 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 768, 12: 966, 13: 1052, 14: 1940, 15: 1926, 16: 989, 17: 938, 18: 3072, 19: 1421, 20: 2995, 21: 653, 22: 332, 23: 1138})])",MACs,20657.405952,top1_acc,-77.52034068817896 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 3050, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 3072, 23: 505})])",MACs,17863.409664,top1_acc,-77.35333502140196 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 989, 17: 1759, 18: 3072, 19: 2291, 20: 1175, 21: 280, 22: 3072, 23: 1138})])",MACs,22044.082176,top1_acc,-77.78191660364617 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 3072})])",MACs,31443.51744,top1_acc,-78.7648563012301 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 1759, 18: 3072, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,19873.529856,top1_acc,-77.83926941133595 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,19056.623616,top1_acc,-77.80319524031965 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1898, 14: 1940, 15: 3043, 16: 2580, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 3072})])",MACs,19681.837056,top1_acc,-77.34515610255724 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 3018, 18: 3006, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,20816.068608,top1_acc,-77.7530590882161 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 2291, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,19623.44448,top1_acc,-78.0691912882812 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3072, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,20661.53472,top1_acc,-78.13639502327537 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 1926, 16: 3072, 17: 938, 18: 1554, 19: 3072, 20: 517, 21: 653, 22: 3072, 23: 505})])",MACs,22976.59392,top1_acc,-78.0004860742962 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,19831.062528,top1_acc,-78.24592280756991 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,18166.5792,top1_acc,-77.41754417552072 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 704, 5: 448, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 2670, 15: 1926, 16: 989, 17: 938, 18: 2363, 19: 3072, 20: 517, 21: 280, 22: 3072, 23: 3072})])",MACs,24141.49632,top1_acc,-77.81261614954856 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 2662, 16: 3037, 17: 1759, 18: 1554, 19: 2291, 20: 3072, 21: 280, 22: 1287, 23: 752})])",MACs,22475.24352,top1_acc,-78.34313247612644 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,16228.417536,top1_acc,-76.84613485571143 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 704, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 1898, 14: 1940, 15: 3043, 16: 2580, 17: 2521, 18: 789, 19: 3072, 20: 517, 21: 280, 22: 1287, 23: 3072})])",MACs,25239.748608,top1_acc,-78.23555445013551 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,26525.564928,top1_acc,-78.38309810538458 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,22566.66624,top1_acc,-78.21757173705544 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 2670, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 3072, 20: 2995, 21: 280, 22: 3072, 23: 752})])",MACs,26902.462464,top1_acc,-78.52182896993705 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 576, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 989, 17: 1759, 18: 3006, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,21828.796416,top1_acc,-78.06885650371234 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,16700.276736,top1_acc,-76.95530441768108 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 768, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 2521, 18: 3072, 19: 3072, 20: 2995, 21: 280, 22: 1287, 23: 1138})])",MACs,24657.59232,top1_acc,-78.22497797039871 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,23066.836992,top1_acc,-78.21617260934369 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,17940.676608,top1_acc,-77.3707605552837 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 1040, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 3009, 20: 2995, 21: 653, 22: 1287, 23: 3072})])",MACs,27480.489984,top1_acc,-78.69559994929239 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 3072, 18: 789, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,18936.29952,top1_acc,-77.37018885513305 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 1898, 14: 1040, 15: 3043, 16: 2580, 17: 938, 18: 2363, 19: 3072, 20: 2995, 21: 653, 22: 332, 23: 2472})])",MACs,23958.061056,top1_acc,-78.2089801079466 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 2580, 17: 2521, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 665, 23: 1138})])",MACs,24611.586048,top1_acc,-78.309307419769 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,25502.810112,top1_acc,-78.64834520052264 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 768, 5: 768, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1940, 15: 1926, 16: 989, 17: 3018, 18: 789, 19: 693, 20: 517, 21: 653, 22: 1287, 23: 3072})])",MACs,20728.184832,top1_acc,-76.88411382333055 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 2291, 20: 517, 21: 653, 22: 332, 23: 752})])",MACs,16719.151104,top1_acc,-77.20660004301871 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,26471.30112,top1_acc,-78.54149983732098 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,19938.410496,top1_acc,-77.97450715697126 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 1287, 23: 505})])",MACs,18247.385088,top1_acc,-77.15867985191612 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 3072, 19: 2291, 20: 1175, 21: 1500, 22: 332, 23: 1138})])",MACs,21469.5936,top1_acc,-78.22611513535827 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 3072, 23: 505})])",MACs,22455.779328,top1_acc,-78.07398714410215 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,27226.27584,top1_acc,-78.71599389821127 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,20147.208192,top1_acc,-77.83210248350746 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 2580, 17: 3018, 18: 789, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,22152.019968,top1_acc,-77.88336740914414 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 768, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1898, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,20927.545344,top1_acc,-78.02763196898238 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,26110.328832,top1_acc,-78.57644780721675 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 693, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,21743.86176,top1_acc,-78.07945236052316 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 2662, 16: 1807, 17: 3018, 18: 3006, 19: 3009, 20: 2078, 21: 280, 22: 332, 23: 505})])",MACs,25323.503616,top1_acc,-78.45750723056842 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 1926, 16: 989, 17: 1759, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 3072, 23: 505})])",MACs,22177.3824,top1_acc,-77.93515562540608 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 3041, 15: 1926, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,19023.593472,top1_acc,-77.113233198754 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,27509.39136,top1_acc,-78.64810229760846 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,19980.288,top1_acc,-78.20013230097362 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 2670, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 3072, 20: 2995, 21: 653, 22: 3072, 23: 3072})])",MACs,29245.833216,top1_acc,-78.6990581755079 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 989, 17: 938, 18: 2363, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,21055.537152,top1_acc,-78.08191067428515 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,16368.795648,top1_acc,-77.29614555319023 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,21776.891904,top1_acc,-78.35675790996193 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 517, 21: 280, 22: 332, 23: 1138})])",MACs,16176.513024,top1_acc,-77.10013235174155 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,17200.447488,top1_acc,-77.49220955048149 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 1926, 16: 989, 17: 938, 18: 2363, 19: 693, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,20313.53856,top1_acc,-77.5816592663101 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 3009, 20: 2995, 21: 653, 22: 1287, 23: 3072})])",MACs,26604.01152,top1_acc,-78.60601180611319 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 3050, 14: 1940, 15: 3072, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 2078, 21: 280, 22: 3072, 23: 505})])",MACs,23553.441792,top1_acc,-78.11828116902451 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 1759, 18: 3072, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 2472})])",MACs,20660.355072,top1_acc,-77.83698514024852 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 3041, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 505})])",MACs,19773.259776,top1_acc,-77.73876551840432 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 3050, 14: 1040, 15: 3072, 16: 3072, 17: 938, 18: 789, 19: 3072, 20: 1175, 21: 653, 22: 3072, 23: 3072})])",MACs,25951.076352,top1_acc,-78.07700838215649 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 3037, 17: 938, 18: 1554, 19: 2291, 20: 3072, 21: 280, 22: 332, 23: 752})])",MACs,20218.576896,top1_acc,-77.99208359413008 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19359.203328,top1_acc,-77.92349149675906 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,24653.463552,top1_acc,-78.51673190476535 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 1138})])",MACs,16385.900544,top1_acc,-76.69415836967669 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,29100.146688,top1_acc,-78.87995104019924 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 2662, 16: 2580, 17: 3018, 18: 789, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,22549.561344,top1_acc,-77.81129028322314 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 3072, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,17977.83552,top1_acc,-77.69489468913235 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,21255.487488,top1_acc,-78.12590721097891 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 3072, 15: 3072, 16: 989, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,28083.290112,top1_acc,-78.53411662844837 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 1926, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,18739.298304,top1_acc,-77.3979831098809 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 2662, 16: 3037, 17: 1759, 18: 1554, 19: 2291, 20: 3072, 21: 1500, 22: 3072, 23: 752})])",MACs,24436.40832,top1_acc,-78.22834396436203 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 2291, 20: 517, 21: 280, 22: 332, 23: 1138})])",MACs,16195.977216,top1_acc,-77.20680755098213 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2995, 21: 280, 22: 3072, 23: 3072})])",MACs,30262.689792,top1_acc,-78.8661233113096 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,18012.045312,top1_acc,-77.607044946814 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 2291, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,29142.614016,top1_acc,-78.64977223286314 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 2078, 21: 280, 22: 332, 23: 1138})])",MACs,17841.586176,top1_acc,-77.51843856952614 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 938, 18: 3006, 19: 3072, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,21225.406464,top1_acc,-77.82417660476925 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,21011.300352,top1_acc,-77.97732761929427 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 3072, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18480.955392,top1_acc,-77.66893196922712 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 2291, 20: 517, 21: 653, 22: 332, 23: 752})])",MACs,17285.382144,top1_acc,-77.11590277592806 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19276.627968,top1_acc,-77.81984711178856 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,24842.207232,top1_acc,-78.67793975940958 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 768, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 1807, 17: 938, 18: 789, 19: 3072, 20: 2995, 21: 653, 22: 3072, 23: 3072})])",MACs,25263.341568,top1_acc,-78.31344972766144 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 3006, 19: 3072, 20: 517, 21: 280, 22: 332, 23: 752})])",MACs,19057.803264,top1_acc,-77.38051836457113 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 3072, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,19343.867904,top1_acc,-77.81901694626069 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,22060.007424,top1_acc,-78.39373470069667 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2995, 21: 653, 22: 3072, 23: 3072})])",MACs,31145.066496,top1_acc,-78.67871283603706 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,17004.62592,top1_acc,-77.23340251896809 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,19770.310656,top1_acc,-78.0251053376717 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3072, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,29233.446912,top1_acc,-78.88281302119101 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18249.15456,top1_acc,-77.75308279352778 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 3018, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,23446.683648,top1_acc,-78.31898047247827 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,20502.28224,top1_acc,-78.24415229109488 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 1138})])",MACs,15253.438464,top1_acc,-76.88589795627858 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 1138})])",MACs,16008.413184,top1_acc,-76.79773476523428 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,25314.066432,top1_acc,-78.5267382813592 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 704, 5: 448, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1898, 14: 2670, 15: 1007, 16: 989, 17: 3018, 18: 2363, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,20131.282944,top1_acc,-77.5411722114769 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 789, 19: 693, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,23237.296128,top1_acc,-78.14597056489272 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,15834.415104,top1_acc,-77.02958249554321 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,18584.764416,top1_acc,-77.86220841432129 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,25777.668096,top1_acc,-78.62817050297392 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 789, 19: 2291, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,18941.607936,top1_acc,-77.54118040106134 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,16289.169408,top1_acc,-76.90599994745618 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,15662.186496,top1_acc,-76.82665085090973 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,24765.530112,top1_acc,-78.28943995390838 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,18022.07232,top1_acc,-77.57183952205641 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 1926, 16: 989, 17: 938, 18: 2363, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,19970.260992,top1_acc,-77.79887306966371 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 3072})])",MACs,32009.74848,top1_acc,-78.72433387193273 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 3072, 19: 693, 20: 2078, 21: 280, 22: 332, 23: 505})])",MACs,18982.305792,top1_acc,-77.73658088995523 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 768, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 3072, 15: 3072, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,18480.365568,top1_acc,-76.63531180080984 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 3018, 18: 3006, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,22399.156224,top1_acc,-78.31417578555032 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,20360.72448,top1_acc,-77.73281570962881 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 2580, 17: 3018, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,24211.685376,top1_acc,-78.5256134448819 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,16634.216448,top1_acc,-77.49770438191729 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,16218.390528,top1_acc,-77.45766628234638 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,19705.430016,top1_acc,-77.99123496998509 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 3072, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,18260.95104,top1_acc,-77.6246298077557 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 938, 18: 3006, 19: 693, 20: 2078, 21: 280, 22: 332, 23: 752})])",MACs,21722.038272,top1_acc,-77.93035304498476 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,23676.125184,top1_acc,-78.34180292291131 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3043, 16: 1807, 17: 3018, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,23830.659072,top1_acc,-78.42162980263775 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 505})])",MACs,21781.020672,top1_acc,-78.28895334539128 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 704, 5: 512, 6: 576, 7: 512, 8: 768, 9: 768, 10: 768, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 3018, 18: 789, 19: 693, 20: 517, 21: 653, 22: 3072, 23: 505})])",MACs,20830.814208,top1_acc,-77.18108860372695 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 517, 21: 653, 22: 3072, 23: 1138})])",MACs,20878.000128,top1_acc,-77.5863650827711 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2995, 21: 280, 22: 3072, 23: 3072})])",MACs,30828.920832,top1_acc,-78.73245011474873 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,18309.906432,top1_acc,-77.52162780701477 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 2580, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,18403.098624,top1_acc,-77.4645818535637 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 280, 22: 332, 23: 1138})])",MACs,20501.692416,top1_acc,-78.27733677696575 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,20453.916672,top1_acc,-78.12271520406631 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,16854.2208,top1_acc,-77.45917986307953 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,15288.827904,top1_acc,-76.83019539621777 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,22779.592704,top1_acc,-78.11463618537948 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 505})])",MACs,22678.142976,top1_acc,-78.24207836884328 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 2662, 16: 2580, 17: 938, 18: 2363, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,20842.610688,top1_acc,-77.97327656175884 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,20498.153472,top1_acc,-78.28637909625468 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 938, 18: 2363, 19: 3072, 20: 2995, 21: 280, 22: 332, 23: 3072})])",MACs,25721.044992,top1_acc,-78.31869230469229 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 693, 20: 2078, 21: 280, 22: 332, 23: 505})])",MACs,18669.699072,top1_acc,-77.49808420871487 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,16963.33824,top1_acc,-77.48776183470927 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 3018, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,22177.3824,top1_acc,-77.87647049343227 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19022.413824,top1_acc,-77.5045694328356 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,17824.48128,top1_acc,-77.54959508872264 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,15756.558336,top1_acc,-76.87102605861044 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,18308.13696,top1_acc,-77.85554918534362 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,18584.764416,top1_acc,-77.90928138104908 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 938, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,25716.3264,top1_acc,-78.36203533304898 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 693, 20: 2078, 21: 280, 22: 332, 23: 1138})])",MACs,18701.549568,top1_acc,-77.64312794844913 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,18935.709696,top1_acc,-77.99426507425802 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 2580, 17: 3018, 18: 3072, 19: 693, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,23881.383936,top1_acc,-78.15413975521426 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,24577.376256,top1_acc,-78.39279602081112 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,20774.780928,top1_acc,-78.09310197951929 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,18910.347264,top1_acc,-77.64647534312249 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,27603.7632,top1_acc,-78.71065763068782 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 2580, 17: 3018, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 2844, 23: 752})])",MACs,24360.321024,top1_acc,-78.35578797789258 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 2662, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,24145.625088,top1_acc,-78.483058801489 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 665, 23: 505})])",MACs,14982.119424,top1_acc,-77.03054406766542 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 1807, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,21868.314624,top1_acc,-78.22242209342078 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19841.67936,top1_acc,-78.25530912888111 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,17662.869504,top1_acc,-77.29633450560492 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,20599.6032,top1_acc,-78.00536453971029 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 938, 18: 789, 19: 693, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,19447.087104,top1_acc,-77.44561991259576 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 3072, 21: 280, 22: 3072, 23: 3072})])",MACs,30308.10624,top1_acc,-78.85705121244501 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 2291, 20: 517, 21: 653, 22: 665, 23: 752})])",MACs,21907.243008,top1_acc,-78.10061350706916 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,28216.000512,top1_acc,-78.62305713133297 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,22286.49984,top1_acc,-78.27758171285781 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,16962.748416,top1_acc,-77.30624141644194 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,21433.024512,top1_acc,-78.13034051654454 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,24747.835392,top1_acc,-78.53788911427132 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1007, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,25442.05824,top1_acc,-78.24141461692182 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,29383.262208,top1_acc,-78.73468426865634 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,16490.889216,top1_acc,-77.24512821532456 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,19207.61856,top1_acc,-77.84670955295435 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,16529.227776,top1_acc,-77.31135996946382 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 3018, 18: 3006, 19: 3072, 20: 517, 21: 280, 22: 665, 23: 752})])",MACs,22195.07712,top1_acc,-78.1770570358772 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 2580, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 3072, 23: 505})])",MACs,18388.942848,top1_acc,-77.19842547661632 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3072, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,27677.4912,top1_acc,-78.65899490173153 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,23057.399808,top1_acc,-78.57209871104413 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,16539.844608,top1_acc,-77.57767735928259 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,16222.519296,top1_acc,-77.316579583959 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,16124.018688,top1_acc,-77.59379400465647 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1040, 15: 3072, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,18153.013248,top1_acc,-77.53853477700561 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,14785.708032,top1_acc,-76.96240540010879 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 1138})])",MACs,24087.232512,top1_acc,-77.99785766861768 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 2580, 17: 938, 18: 789, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,17899.978752,top1_acc,-77.63077575852904 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 938, 18: 3006, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,25623.724032,top1_acc,-78.30864275756987 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 3018, 18: 3006, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,20249.837568,top1_acc,-77.80296089308226 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,16851.27168,top1_acc,-77.4933722888565 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 3018, 18: 789, 19: 693, 20: 517, 21: 280, 22: 3072, 23: 505})])",MACs,17911.775232,top1_acc,-77.07474111165543 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,17604.476928,top1_acc,-77.50608266549855 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 1807, 17: 3018, 18: 3072, 19: 3072, 20: 2078, 21: 280, 22: 332, 23: 752})])",MACs,25126.5024,top1_acc,-78.54768239926481 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 2291, 20: 517, 21: 653, 22: 3072, 23: 752})])",MACs,23610.064896,top1_acc,-78.12854112147335 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,22100.70528,top1_acc,-78.41433672491345 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 938, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,22628.59776,top1_acc,-78.0165066036578 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 2291, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,19140.968448,top1_acc,-77.8042493903752 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 2662, 16: 2580, 17: 938, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,21302.673408,top1_acc,-78.22431383280205 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18804.768768,top1_acc,-77.7691648063769 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,26754.41664,top1_acc,-78.70092512844904 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,25133.580288,top1_acc,-78.40256485999464 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,21742.092288,top1_acc,-78.11552094608395 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 517, 21: 280, 22: 3072, 23: 3072})])",MACs,26868.842496,top1_acc,-78.33727428548202 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 693, 20: 2078, 21: 280, 22: 3072, 23: 505})])",MACs,19189.334016,top1_acc,-77.81369629175298 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,27002.14272,top1_acc,-78.61464894798203 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 332, 23: 752})])",MACs,25719.27552,top1_acc,-78.37990487798305 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,19497.811968,top1_acc,-77.96059563885905 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 576, 5: 512, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3072, 15: 1926, 16: 3072, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,24005.8368,top1_acc,-77.99643291946123 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 1807, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 280, 22: 332, 23: 1138})])",MACs,21939.093504,top1_acc,-78.31642943126927 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 3072, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18888.523776,top1_acc,-77.69421305539883 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 704, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 789, 19: 3072, 20: 1175, 21: 280, 22: 3072, 23: 505})])",MACs,24089.001984,top1_acc,-77.83719750831027 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3072, 15: 1926, 16: 989, 17: 938, 18: 3072, 19: 693, 20: 2078, 21: 280, 22: 3072, 23: 505})])",MACs,22714.12224,top1_acc,-77.99821723408273 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 3072, 23: 505})])",MACs,20429.733888,top1_acc,-78.18637144061381 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,21231.304704,top1_acc,-78.08023004204325 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,26982.088704,top1_acc,-78.7110116626458 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 665, 23: 505})])",MACs,15076.491264,top1_acc,-76.9887280331364 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19067.830272,top1_acc,-78.04574600057983 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,24068.947968,top1_acc,-78.25398679234506 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 704, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1898, 14: 2670, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 2995, 21: 280, 22: 665, 23: 505})])",MACs,18375.96672,top1_acc,-77.25985796389628 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 2662, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,18653.773824,top1_acc,-77.35360950106893 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,24971.968512,top1_acc,-78.51401716575374 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 3072, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 3072, 23: 505})])",MACs,19920.715776,top1_acc,-77.52569971296752 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,15551.299584,top1_acc,-76.79544247825193 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 966, 13: 3050, 14: 1040, 15: 3072, 16: 989, 17: 3018, 18: 3072, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,21351.6288,top1_acc,-77.95024903510168 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 3018, 18: 3006, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,25222.643712,top1_acc,-78.49358842592319 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18951.634944,top1_acc,-77.79515669285597 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 2363, 19: 3009, 20: 2995, 21: 280, 22: 332, 23: 3072})])",MACs,22713.532416,top1_acc,-78.05096199896344 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 3050, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 789, 19: 3072, 20: 517, 21: 280, 22: 332, 23: 752})])",MACs,21588.148224,top1_acc,-77.74745929715782 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 1926, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,23133.487104,top1_acc,-78.30341891010204 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,20074.65984,top1_acc,-78.19314193179103 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,15896.346624,top1_acc,-77.54074734059057 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,15740.043264,top1_acc,-77.0771953778272 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,25597.181952,top1_acc,-78.60809878832337 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 2670, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 3072, 20: 2995, 21: 280, 22: 3072, 23: 3072})])",MACs,28742.713344,top1_acc,-78.63970430916339 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 1940, 15: 3072, 16: 1807, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,25414.336512,top1_acc,-78.43954401716532 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,17820.942336,top1_acc,-77.46722568250588 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18683.265024,top1_acc,-77.92577555829591 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 3072, 15: 2662, 16: 3072, 17: 3018, 18: 3072, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,26876.510208,top1_acc,-78.55295236037308 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,17746.034688,top1_acc,-77.69983165010207 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18925.092864,top1_acc,-77.83205885355181 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,20781.268992,top1_acc,-78.28098899128807 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,22829.727744,top1_acc,-78.53589957037666 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,25999.44192,top1_acc,-78.55171934840534 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 1807, 17: 938, 18: 2363, 19: 3009, 20: 1175, 21: 653, 22: 3072, 23: 3072})])",MACs,26516.717568,top1_acc,-78.49013130154695 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 989, 17: 3018, 18: 789, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,25997.672448,top1_acc,-78.30351650270724 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 752})])",MACs,15214.51008,top1_acc,-76.78306414850093 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,15830.286336,top1_acc,-77.23106091583311 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,22328.377344,top1_acc,-78.36988414332976 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3072, 19: 3072, 20: 2995, 21: 280, 22: 3072, 23: 3072})])",MACs,31142.7072,top1_acc,-78.80509085297578 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 789, 19: 3072, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,25197.28128,top1_acc,-78.43786908483743 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,16218.390528,top1_acc,-77.52650978796271 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,18226.151424,top1_acc,-77.66381073219989 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,15351.939072,top1_acc,-76.9978017191095 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,17262.379008,top1_acc,-77.76626748680111 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,24490.082304,top1_acc,-78.43771933033916 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 2580, 17: 938, 18: 2363, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,18130.010112,top1_acc,-77.78284718799516 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 2363, 19: 2291, 20: 517, 21: 280, 22: 3072, 23: 505})])",MACs,20356.005888,top1_acc,-77.63402157044644 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,17783.783424,top1_acc,-77.75304115756522 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 1138})])",MACs,25069.879296,top1_acc,-78.66764211829364 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,16784.621568,top1_acc,-77.58099256011783 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1898, 14: 2670, 15: 3043, 16: 989, 17: 3018, 18: 1554, 19: 3072, 20: 2995, 21: 280, 22: 332, 23: 505})])",MACs,24191.63136,top1_acc,-78.46268490375547 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 938, 18: 3072, 19: 693, 20: 517, 21: 280, 22: 665, 23: 505})])",MACs,18217.893888,top1_acc,-77.37974929772683 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,15750.660096,top1_acc,-77.57450577463406 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,18134.13888,top1_acc,-77.79034460849182 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,20270.481408,top1_acc,-78.25843515131325 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,28353.429504,top1_acc,-78.82755569790727 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3043, 16: 1807, 17: 3018, 18: 3006, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,25293.422592,top1_acc,-78.59403456717976 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 2291, 20: 517, 21: 280, 22: 332, 23: 1138})])",MACs,16101.605376,top1_acc,-77.25709688044186 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17833.918464,top1_acc,-77.76636169448905 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,15173.812224,top1_acc,-77.06765185870125 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,19132.121088,top1_acc,-77.92910353839021 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,20344.209408,top1_acc,-78.26282139386508 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 768, 5: 448, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 989, 17: 3018, 18: 789, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 505})])",MACs,22546.612224,top1_acc,-78.35173828348978 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 2580, 17: 3018, 18: 789, 19: 693, 20: 1175, 21: 653, 22: 665, 23: 752})])",MACs,19598.082048,top1_acc,-77.77756466005347 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 966, 13: 1052, 14: 3041, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19206.438912,top1_acc,-77.39395905851582 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,17472.946176,top1_acc,-77.44407931036918 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,18310.496256,top1_acc,-77.59092436289475 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,15897.526272,top1_acc,-77.31676380486402 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3043, 16: 3072, 17: 3018, 18: 3006, 19: 3009, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,26167.54176,top1_acc,-78.56139101703768 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 1807, 17: 3018, 18: 789, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,26763.264,top1_acc,-78.53620592344751 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3072, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,24874.057728,top1_acc,-78.58485169722707 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 3018, 18: 3072, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,20013.907968,top1_acc,-77.86313368547202 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 1138})])",MACs,21879.52128,top1_acc,-78.10356403442829 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,17490.051072,top1_acc,-77.78376853633611 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,26093.81376,top1_acc,-78.67757511775116 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 280, 22: 3072, 23: 1138})])",MACs,23906.156544,top1_acc,-78.30811832499914 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,23838.326784,top1_acc,-78.54925426363128 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,20397.293568,top1_acc,-78.10765707872851 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3072, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,28180.611072,top1_acc,-78.76449244974833 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,21965.635584,top1_acc,-78.45682687462798 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 3009, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,24044.17536,top1_acc,-78.30991195311422 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 3072, 20: 517, 21: 280, 22: 332, 23: 752})])",MACs,19171.049472,top1_acc,-78.01003049796898 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3072, 16: 989, 17: 3018, 18: 3006, 19: 3072, 20: 2995, 21: 280, 22: 3072, 23: 3072})])",MACs,29430.448128,top1_acc,-78.50156225601242 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 989, 17: 938, 18: 789, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,24393.351168,top1_acc,-77.75889997746367 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 332, 23: 752})])",MACs,26454.196224,top1_acc,-78.55032565902884 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17317.23264,top1_acc,-77.441857100072 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,22666.93632,top1_acc,-78.43300844467515 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 665, 23: 505})])",MACs,16145.842176,top1_acc,-77.23906108842539 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19060.752384,top1_acc,-78.00864265699215 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,27712.88064,top1_acc,-78.63356866747405 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,22546.612224,top1_acc,-78.3349878613893 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 2580, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19481.296896,top1_acc,-77.91498565066966 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17116.69248,top1_acc,-77.74975964187483 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 3072, 18: 789, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18030.329856,top1_acc,-77.41476339521925 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 3072, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,28695.527424,top1_acc,-78.90656771023961 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 3072, 20: 1175, 21: 280, 22: 3072, 23: 3072})])",MACs,25839.599616,top1_acc,-78.37692559866657 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 448, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 1926, 16: 3072, 17: 3018, 18: 3072, 19: 3072, 20: 2078, 21: 280, 22: 332, 23: 752})])",MACs,25808.928768,top1_acc,-78.51063993971425 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 768, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,17960.1408,top1_acc,-77.34900503768343 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 3072, 17: 938, 18: 789, 19: 693, 20: 2995, 21: 280, 22: 332, 23: 505})])",MACs,19455.934464,top1_acc,-77.25425640131093 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 2580, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,23230.21824,top1_acc,-78.34351453783542 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,17545.494528,top1_acc,-77.62295099861034 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3058, 13: 1898, 14: 2670, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 2995, 21: 280, 22: 332, 23: 505})])",MACs,23017.291776,top1_acc,-78.28076997672596 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3072, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 3072, 23: 505})])",MACs,18210.226176,top1_acc,-77.17462474827859 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 3041, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19074.318336,top1_acc,-77.48016640253664 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 704, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 1926, 16: 989, 17: 3018, 18: 2363, 19: 3072, 20: 1175, 21: 280, 22: 3072, 23: 3072})])",MACs,25980.567552,top1_acc,-78.26938033329448 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 1807, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,24669.3888,top1_acc,-78.65141283002174 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,15547.170816,top1_acc,-77.14345877977969 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3072, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,21062.025216,top1_acc,-77.44372456312817 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 704, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 693, 20: 2995, 21: 280, 22: 3072, 23: 3072})])",MACs,23986.372608,top1_acc,-78.08181738851654 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 1138})])",MACs,25636.110336,top1_acc,-78.48383267373796 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 3072, 23: 1138})])",MACs,19508.4288,top1_acc,-77.59361133076088 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 938, 18: 3072, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,28006.612992,top1_acc,-78.31613562877104 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,17001.086976,top1_acc,-77.51895967489043 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3072, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,20713.439232,top1_acc,-78.13999550233227 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 3050, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 3072, 23: 1138})])",MACs,22952.411136,top1_acc,-78.19900229949599 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 1926, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 3072, 23: 752})])",MACs,25901.531136,top1_acc,-78.50184374182437 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 704, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1898, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 3072})])",MACs,19544.408064,top1_acc,-77.57585365756358 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 3050, 14: 1040, 15: 3072, 16: 989, 17: 3018, 18: 789, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 1138})])",MACs,23501.53728,top1_acc,-77.68210371704363 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 3006, 19: 693, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,16596.467712,top1_acc,-77.28467287114245 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,18931.580928,top1_acc,-77.80145350819075 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 704, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 2670, 15: 3043, 16: 989, 17: 3018, 18: 1554, 19: 3072, 20: 2995, 21: 653, 22: 332, 23: 505})])",MACs,24977.866752,top1_acc,-78.33426042329788 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3072, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,20151.33696,top1_acc,-78.05639264123646 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 3006, 19: 693, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,18935.119872,top1_acc,-77.44717206861365 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 3018, 18: 2363, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,19797.44256,top1_acc,-77.73817265465667 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 1807, 17: 938, 18: 2363, 19: 2291, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,24202.838016,top1_acc,-78.54299029961118 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 505})])",MACs,19299.631104,top1_acc,-77.85709569672244 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,22909.353984,top1_acc,-78.54802966918659 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,17898.799104,top1_acc,-77.63235054655482 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 789, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,18081.05472,top1_acc,-77.82473305531869 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 3072, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 2291, 20: 2078, 21: 280, 22: 332, 23: 752})])",MACs,25723.404288,top1_acc,-78.54522998059878 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 3072, 17: 938, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 332, 23: 505})])",MACs,20586.037248,top1_acc,-77.89410170050502 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 576, 5: 448, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 2670, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 693, 20: 2995, 21: 280, 22: 3072, 23: 1138})])",MACs,25605.439488,top1_acc,-78.52134191980957 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3072, 15: 1926, 16: 3072, 17: 938, 18: 3072, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,21279.080448,top1_acc,-77.737395846747 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 789, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,24849.28512,top1_acc,-78.43228373847589 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,15865.675776,top1_acc,-77.12243087663003 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 576, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 2363, 19: 693, 20: 1175, 21: 280, 22: 3072, 23: 3072})])",MACs,19798.622208,top1_acc,-77.51777099824672 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 517, 21: 280, 22: 332, 23: 752})])",MACs,18850.77504,top1_acc,-77.88785527183938 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,23055.040512,top1_acc,-78.51614610934976 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 3072, 15: 3043, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,26388.135936,top1_acc,-78.16467347268659 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,23523.950592,top1_acc,-78.3291637128707 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 989, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,19658.83392,top1_acc,-77.91341938749923 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 3050, 14: 1040, 15: 1926, 16: 3072, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,23050.911744,top1_acc,-78.13787937701804 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,19931.922432,top1_acc,-78.15044980296982 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,24086.052864,top1_acc,-78.58935101624708 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 1926, 16: 2580, 17: 938, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,22673.424384,top1_acc,-78.15992693561373 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 1807, 17: 3018, 18: 3072, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,24316.674048,top1_acc,-78.48633224733851 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19116.19584,top1_acc,-77.88562939950315 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 2662, 16: 1807, 17: 938, 18: 3072, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,25777.078272,top1_acc,-78.53621718549601 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1898, 14: 3041, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2995, 21: 653, 22: 332, 23: 505})])",MACs,23632.478208,top1_acc,-78.24512973964022 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 2670, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 3072, 20: 1175, 21: 280, 22: 3072, 23: 3072})])",MACs,27358.98624,top1_acc,-78.54043652178835 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3043, 16: 1807, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,22141.99296,top1_acc,-78.29619431846139 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 768, 5: 512, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 3018, 18: 789, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,17560.240128,top1_acc,-77.22652507934787 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,22522.42944,top1_acc,-78.52793470535215 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,15908.143104,top1_acc,-77.65812738785716 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 3018, 18: 3072, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,25179.58656,top1_acc,-78.4879284642495 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 505})])",MACs,24938.938368,top1_acc,-78.65485094067027 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,15551.299584,top1_acc,-76.79544247825193 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,24459.411456,top1_acc,-78.64837319091714 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 448, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 752})])",MACs,17685.282816,top1_acc,-77.24438386514564 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,21351.038976,top1_acc,-78.32926280395584 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 1926, 16: 989, 17: 938, 18: 2363, 19: 2291, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,19365.101568,top1_acc,-77.64523378614022 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,19892.994048,top1_acc,-78.2003458032467 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17249.992704,top1_acc,-77.62848863095657 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 3072, 17: 938, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,23511.564288,top1_acc,-78.01908413540639 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 3050, 14: 3072, 15: 2662, 16: 3072, 17: 3018, 18: 2363, 19: 3009, 20: 1175, 21: 280, 22: 3072, 23: 752})])",MACs,27051.687936,top1_acc,-78.6088697426392 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 938, 18: 2363, 19: 2291, 20: 1175, 21: 280, 22: 3072, 23: 752})])",MACs,22829.13792,top1_acc,-78.17966189218494 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 2078, 21: 280, 22: 332, 23: 505})])",MACs,20363.6736,top1_acc,-78.13153477421469 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18710.396928,top1_acc,-77.86863493365077 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,27111.26016,top1_acc,-78.26269048522514 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3072, 19: 3009, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,27327.725568,top1_acc,-78.73891351372478 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1007, 16: 989, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,17825.660928,top1_acc,-77.80361899472925 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19606.929408,top1_acc,-78.11755331843116 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 1926, 16: 989, 17: 3018, 18: 3072, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 505})])",MACs,26333.872128,top1_acc,-78.45554774399025 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,22202.155008,top1_acc,-78.51199229160002 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 1807, 17: 3018, 18: 789, 19: 693, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,20373.110784,top1_acc,-77.82957407612925 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17494.17984,top1_acc,-77.96525651452637 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,17368.547328,top1_acc,-77.74566375232503 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 3072, 15: 2662, 16: 989, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,23867.22816,top1_acc,-78.02996779808394 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 3041, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19911.868416,top1_acc,-77.86555395332293 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 789, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,17122.000896,top1_acc,-77.47648030210392 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3072, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,28369.354752,top1_acc,-78.67493898365474 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,22774.284288,top1_acc,-78.35880943132668 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,22576.103424,top1_acc,-78.07557449481 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17804.427264,top1_acc,-77.85880523936832 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,16027.877376,top1_acc,-77.19860096002313 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,24653.463552,top1_acc,-78.51673190476535 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,20781.268992,top1_acc,-78.28098899128807 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,21341.011968,top1_acc,-78.26557067737463 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 3043, 16: 1807, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,24677.646336,top1_acc,-78.63463157277894 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 789, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,18072.797184,top1_acc,-77.78808862130207 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 3072, 16: 989, 17: 3018, 18: 3006, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,19984.416768,top1_acc,-77.90035605629542 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 989, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,20639.121408,top1_acc,-78.05728690991567 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,19826.93376,top1_acc,-78.03588313771668 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,21441.282048,top1_acc,-78.42709843776338 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,21634.154496,top1_acc,-78.43817518534364 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 3072, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,19329.122304,top1_acc,-77.8378224248896 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 789, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,26267.81184,top1_acc,-78.62935104846514 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 3072, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,28873.654272,top1_acc,-78.75839913912817 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,19441.188864,top1_acc,-78.04232025825142 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,19912.45824,top1_acc,-77.5789785626143 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 2363, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,25219.694592,top1_acc,-78.63342605184303 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 3018, 18: 789, 19: 693, 20: 517, 21: 653, 22: 3072, 23: 505})])",MACs,21451.89888,top1_acc,-77.6056940830053 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 938, 18: 789, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,22222.798848,top1_acc,-77.94646344205611 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 3041, 15: 1926, 16: 3072, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19197.591552,top1_acc,-77.21559263726385 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17270.04672,top1_acc,-77.76175417319232 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 3072, 23: 505})])",MACs,16684.941312,top1_acc,-76.94381278164906 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,28070.313984,top1_acc,-78.69268874105248 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,24122.621952,top1_acc,-78.12410365073754 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 3072, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,17459.970048,top1_acc,-77.61449282425136 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 2670, 15: 3072, 16: 3072, 17: 3018, 18: 3072, 19: 3009, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,26807.5008,top1_acc,-78.71495120215013 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,20124.79488,top1_acc,-78.17727948492183 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19260.112896,top1_acc,-77.98414906167571 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,24081.924096,top1_acc,-78.55661589138141 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3072, 16: 989, 17: 938, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 332, 23: 752})])",MACs,19993.853952,top1_acc,-78.07671975267651 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3072, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,25711.607808,top1_acc,-78.55271780662297 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3072, 20: 1175, 21: 280, 22: 3072, 23: 1138})])",MACs,22307.733504,top1_acc,-77.87059260480888 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 3072, 16: 989, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,19734.921216,top1_acc,-78.09228709893533 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 448, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 3043, 16: 989, 17: 3018, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 3072, 23: 752})])",MACs,20767.70304,top1_acc,-77.48377524847757 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,17356.750848,top1_acc,-77.76598412961778 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 448, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 3072, 15: 1926, 16: 989, 17: 938, 18: 2363, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,19704.840192,top1_acc,-77.67637663479061 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,22097.166336,top1_acc,-78.36505266704538 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 3072, 23: 1138})])",MACs,22114.271232,top1_acc,-78.31998156351472 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 3050, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 3072, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,23049.732096,top1_acc,-78.05481382237551 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 3018, 18: 3006, 19: 693, 20: 1175, 21: 653, 22: 3072, 23: 505})])",MACs,22675.78368,top1_acc,-78.17366097482953 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1926, 16: 2580, 17: 1759, 18: 2363, 19: 2291, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,19627.573248,top1_acc,-77.9956431928652 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,14691.336192,top1_acc,-76.97400486549628 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 3050, 14: 1040, 15: 3043, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,26107.379712,top1_acc,-78.44089375117169 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 1807, 17: 3018, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,21776.30208,top1_acc,-78.31570331433825 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 505})])",MACs,19928.973312,top1_acc,-77.99917675826535 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,20489.895936,top1_acc,-78.23769648377183 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 3043, 16: 1807, 17: 938, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,23262.068736,top1_acc,-78.51869842613043 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17645.174784,top1_acc,-77.85646401845841 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,25177.817088,top1_acc,-78.47054197364255 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,24632.819712,top1_acc,-78.45102957506718 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 2670, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,27323.5968,top1_acc,-78.6776839720646 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 3050, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,24361.500672,top1_acc,-78.3952532872406 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 3072, 15: 1926, 16: 3072, 17: 938, 18: 1554, 19: 693, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,22315.401216,top1_acc,-77.99644550328227 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,16818.83136,top1_acc,-77.55404427530216 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,19913.637888,top1_acc,-78.28515316061544 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,28573.433856,top1_acc,-78.9662702737156 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,22623.289344,top1_acc,-78.41087965967134 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 505})])",MACs,17094.868992,top1_acc,-77.48568179789913 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,20120.666112,top1_acc,-78.15444167997698 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19984.416768,top1_acc,-78.00358798694228 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3072, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,29516.562432,top1_acc,-78.78583811892175 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1898, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,24529.010688,top1_acc,-78.44902213174258 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 768, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 2291, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,21014.249472,top1_acc,-78.16204663182965 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19313.197056,top1_acc,-77.9564865129415 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3072, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 752})])",MACs,16267.935744,top1_acc,-77.1496832721548 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 3072, 19: 3072, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,21037.842432,top1_acc,-77.82224586771727 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1898, 14: 1940, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 1175, 21: 280, 22: 3072, 23: 752})])",MACs,25872.039936,top1_acc,-78.66427019392944 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3072, 19: 3009, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,27074.101248,top1_acc,-78.44904739388289 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 576, 5: 448, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 3050, 14: 1040, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 3072, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,22130.786304,top1_acc,-77.72974735903581 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,16222.519296,top1_acc,-77.61518039338112 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 280, 22: 3072, 23: 505})])",MACs,24759.631872,top1_acc,-78.33016033522173 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,26440.040448,top1_acc,-78.74124980895425 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,17924.161536,top1_acc,-78.03595001022882 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 789, 19: 3072, 20: 517, 21: 280, 22: 332, 23: 1138})])",MACs,19041.878016,top1_acc,-77.8542969669677 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17871.6672,top1_acc,-77.78403675150756 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,15530.655744,top1_acc,-77.58895030158253 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,19987.365888,top1_acc,-78.20110873498177 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 2674, 14: 3041, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,28903.145472,top1_acc,-78.75953775349707 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,29311.893504,top1_acc,-78.85427365242138 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,15998.386176,top1_acc,-77.48516512327161 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 989, 17: 938, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,24671.158272,top1_acc,-78.14858289886048 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,26035.421184,top1_acc,-78.7401459438801 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,15299.444736,top1_acc,-77.07530178117158 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 704, 5: 512, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 3018, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,18373.607424,top1_acc,-77.05565942110756 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 517, 21: 653, 22: 665, 23: 505})])",MACs,17019.37152,top1_acc,-77.62430347311052 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,15079.440384,top1_acc,-77.0415012823797 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17804.427264,top1_acc,-77.85880523936832 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17607.426048,top1_acc,-77.73357389005895 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 1807, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,23775.215616,top1_acc,-78.56949959920718 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1898, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 2078, 21: 280, 22: 332, 23: 505})])",MACs,17034.11712,top1_acc,-77.19069450368643 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,16836.52608,top1_acc,-77.39682254003328 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,28703.78496,top1_acc,-78.90135379952582 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,17038.835712,top1_acc,-77.47896905927324 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,20051.06688,top1_acc,-78.22677176965368 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 3072, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,24731.910144,top1_acc,-78.35601398978778 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3072, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,29528.948736,top1_acc,-78.72548389959671 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3043, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,23931.518976,top1_acc,-78.60069536581224 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19445.317632,top1_acc,-78.07995863468349 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3072, 16: 989, 17: 3018, 18: 3006, 19: 3072, 20: 2078, 21: 280, 22: 332, 23: 1138})])",MACs,21070.872576,top1_acc,-77.94582941479828 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17211.06432,top1_acc,-77.74266022462147 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 989, 17: 938, 18: 2363, 19: 3072, 20: 517, 21: 280, 22: 332, 23: 752})])",MACs,18771.1488,top1_acc,-77.74711562203706 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,18352.963584,top1_acc,-77.56484315157817 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 3072, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,29143.20384,top1_acc,-78.93728912783732 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,18224.381952,top1_acc,-77.74496685574326 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,17007.57504,top1_acc,-77.60542930442463 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 3072, 17: 3018, 18: 3006, 19: 3009, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,25722.22464,top1_acc,-78.5298256833923 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,27447.45984,top1_acc,-78.73740470746723 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 505})])",MACs,24372.707328,top1_acc,-78.34584588332189 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,15750.660096,top1_acc,-77.57450577463406 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,19386.925056,top1_acc,-78.00254876423463 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,15625.027584,top1_acc,-77.47664255944952 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,20527.644672,top1_acc,-78.44821485401496 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,27005.09184,top1_acc,-78.8058695587989 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3072, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,28727.967744,top1_acc,-78.84705879800184 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 3072, 23: 752})])",MACs,20916.338688,top1_acc,-77.80310740746866 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,21346.910208,top1_acc,-78.2997838078728 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 3018, 18: 789, 19: 693, 20: 2078, 21: 280, 22: 3072, 23: 505})])",MACs,21955.608576,top1_acc,-77.61388671680967 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 1421, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,20205.600768,top1_acc,-77.86217579414433 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,17476.48512,top1_acc,-77.82767039988244 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 768, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3072, 15: 3072, 16: 3072, 17: 3018, 18: 3072, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,28369.354752,top1_acc,-78.67493898365474 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17550.802944,top1_acc,-77.90741625453909 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,24653.463552,top1_acc,-78.51673190476535 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,16281.501696,top1_acc,-77.68893872755808 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18316.394496,top1_acc,-77.91332851399177 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,18713.935872,top1_acc,-77.67208070776866 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3072, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,20312.358912,top1_acc,-77.82448512652867 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,17349.67296,top1_acc,-77.51528204773992 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 2363, 19: 3009, 20: 2078, 21: 280, 22: 3072, 23: 1138})])",MACs,24499.519488,top1_acc,-78.26986307828835 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,21154.03776,top1_acc,-78.21683055780055 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3043, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,24464.130048,top1_acc,-78.6339926237069 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,14880.079872,top1_acc,-76.99239256790027 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 704, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 3043, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 3072, 23: 752})])",MACs,20344.799232,top1_acc,-78.09152414443392 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,25312.29696,top1_acc,-78.83156823403006 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,16495.017984,top1_acc,-77.77790239065897 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,27541.83168,top1_acc,-78.8005587087565 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,21454.848,top1_acc,-78.20936464531005 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,23948.623872,top1_acc,-78.5725903583423 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 3041, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,20908.081152,top1_acc,-78.0311247454983 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,27297.05472,top1_acc,-78.85624787548 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,20151.926784,top1_acc,-78.0307368432654 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 2670, 15: 3043, 16: 1807, 17: 3018, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,23003.725824,top1_acc,-78.38500047143845 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18305.777664,top1_acc,-78.12122771454476 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 1175, 21: 280, 22: 3072, 23: 752})])",MACs,25502.810112,top1_acc,-78.57500161445607 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18973.458432,top1_acc,-77.86849522854622 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3058, 13: 1898, 14: 2670, 15: 2662, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 332, 23: 752})])",MACs,26032.472064,top1_acc,-78.45097655026312 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 3072, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3009, 20: 1175, 21: 653, 22: 3072, 23: 505})])",MACs,27916.959744,top1_acc,-78.82645699892439 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,19563.282432,top1_acc,-78.11835846011415 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,28479.062016,top1_acc,-78.95856547709472 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 3041, 15: 1926, 16: 989, 17: 3018, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,19286.065152,top1_acc,-77.55685660320191 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3043, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,24068.947968,top1_acc,-78.56777306233629 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18981.715968,top1_acc,-77.86377433562714 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 768, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 3050, 14: 3072, 15: 3043, 16: 2580, 17: 3018, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,26688.356352,top1_acc,-78.58239097936298 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,19132.121088,top1_acc,-77.92910353839021 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,27730.57536,top1_acc,-78.79793009773329 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,15990.718464,top1_acc,-77.55700482118428 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 1138})])",MACs,26793.934848,top1_acc,-78.73348140542298 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1898, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 2363, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,16307.453952,top1_acc,-77.12605893067567 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,16665.47712,top1_acc,-77.45834907619903 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 3072, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,28860.08832,top1_acc,-78.82180757591021 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3043, 16: 3072, 17: 3018, 18: 789, 19: 3009, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,22632.136704,top1_acc,-78.07599180435162 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,22298.886144,top1_acc,-78.39146851245171 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 789, 19: 3072, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,26831.683584,top1_acc,-78.65973351937707 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 3072, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,29426.31936,top1_acc,-78.84753222803297 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 2363, 19: 2291, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,23312.203776,top1_acc,-78.40282011303081 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,22546.612224,top1_acc,-78.58339420932599 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 768, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3043, 16: 2580, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,23495.63904,top1_acc,-78.55615260093863 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 3041, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,27946.450944,top1_acc,-78.68817373749842 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 1040, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 517, 21: 653, 22: 3072, 23: 752})])",MACs,26313.818112,top1_acc,-78.48141302110515 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 3072, 23: 1138})])",MACs,18380.095488,top1_acc,-77.73226426743872 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 3072, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19781.517312,top1_acc,-77.9959663679459 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,27912.830976,top1_acc,-78.80972447794363 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 693, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,19751.436288,top1_acc,-78.00772086904047 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 938, 18: 789, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 505})])",MACs,18948.096,top1_acc,-77.34992680928774 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,17696.489472,top1_acc,-77.97495234846362 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 280, 22: 332, 23: 752})])",MACs,20690.436096,top1_acc,-78.07018187457909 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 3043, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,22587.899904,top1_acc,-78.3674449512811 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 3041, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,20301.152256,top1_acc,-77.88344201723562 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 3072, 15: 1926, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,27400.27392,top1_acc,-78.78679225363368 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1898, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,20970.012672,top1_acc,-77.42454085851715 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,20502.28224,top1_acc,-78.24415229109488 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,20342.439936,top1_acc,-78.17997144437751 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1940, 15: 1926, 16: 3072, 17: 938, 18: 2363, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,22979.54304,top1_acc,-78.30783604177317 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,16079.781888,top1_acc,-77.33200123942895 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 3043, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,23282.122752,top1_acc,-78.53131328148848 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 2670, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 2078, 21: 280, 22: 332, 23: 505})])",MACs,17045.323776,top1_acc,-76.91077948250833 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,20200.292352,top1_acc,-78.12130276505943 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 2662, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,24504.23808,top1_acc,-78.52543859312907 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,20397.293568,top1_acc,-78.18904489221387 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,18325.83168,top1_acc,-77.92137418009762 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 3072, 20: 1175, 21: 280, 22: 3072, 23: 752})])",MACs,22386.76992,top1_acc,-78.10981988791474 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,20307.64032,top1_acc,-78.38582163313876 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1040, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 3009, 20: 1175, 21: 653, 22: 3072, 23: 1138})])",MACs,23269.146624,top1_acc,-78.00633594089184 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 3041, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,24422.842368,top1_acc,-78.68311018160438 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 505})])",MACs,21506.162688,top1_acc,-78.31891725299393 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 3050, 14: 1040, 15: 3043, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17136.746496,top1_acc,-77.18985438008033 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 693, 20: 517, 21: 280, 22: 332, 23: 752})])",MACs,22294.757376,top1_acc,-77.67859481136809 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,21627.666432,top1_acc,-78.06026151794396 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 3041, 15: 3043, 16: 989, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,20705.77152,top1_acc,-77.63081492640127 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3043, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,25471.54944,top1_acc,-78.56095090406419 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,19233.570816,top1_acc,-77.93302813735649 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 517, 21: 280, 22: 332, 23: 752})])",MACs,15288.23808,top1_acc,-77.22722804512186 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,20755.316736,top1_acc,-78.47201977393134 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,15393.816576,top1_acc,-77.06051028371304 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,16053.829632,top1_acc,-77.67819003057824 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3043, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,25642.008576,top1_acc,-78.62378119652158 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,26768.572416,top1_acc,-78.81109229126086 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,17759.60064,top1_acc,-77.92492392054187 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 693, 20: 517, 21: 653, 22: 332, 23: 752})])",MACs,20752.95744,top1_acc,-77.71919744254149 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 512, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 2670, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 3072, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,25558.253568,top1_acc,-78.47511659585342 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,25730.482176,top1_acc,-78.44027822935608 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 3043, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,21781.610496,top1_acc,-78.3523535295526 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 3072, 15: 1926, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,27540.652032,top1_acc,-78.52502949129891 +"OrderedDict([(, {0: 768, 1: 512, 2: 576, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 3072, 23: 1138})])",MACs,22103.6544,top1_acc,-78.13247404957689 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,18734.579712,top1_acc,-78.058786018038 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,18042.71616,top1_acc,-77.93012062759051 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 280, 22: 332, 23: 1138})])",MACs,20394.934272,top1_acc,-77.8822717214041 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1898, 14: 1040, 15: 1926, 16: 3072, 17: 938, 18: 789, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 505})])",MACs,18220.253184,top1_acc,-77.13877446107868 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,16568.745984,top1_acc,-77.4037417389431 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,22028.156928,top1_acc,-78.44224618355568 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,17593.270272,top1_acc,-77.85217021236613 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,17106.075648,top1_acc,-77.70761232346662 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 3072, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 505})])",MACs,26870.611968,top1_acc,-78.75895236304312 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,17897.029632,top1_acc,-77.95243540323796 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,15456.927744,top1_acc,-77.28989035010578 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 1421, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,16557.539328,top1_acc,-77.42257243273517 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3043, 16: 3072, 17: 3018, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 752})])",MACs,19382.206464,top1_acc,-77.50123341429301 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,26070.810624,top1_acc,-78.77923491785475 +"OrderedDict([(, {0: 768, 1: 512, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,25919.225856,top1_acc,-78.75644768092879 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,21875.392512,top1_acc,-78.43248701295794 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,17477.074944,top1_acc,-77.86514599066999 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 3041, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19240.648704,top1_acc,-77.73475187365824 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 3041, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,25120.60416,top1_acc,-78.66642788878856 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 704, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,27966.50496,top1_acc,-78.89120587865287 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,20792.475648,top1_acc,-78.43359815369101 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,16338.1248,top1_acc,-77.56953565595033 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 989, 17: 938, 18: 2363, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,23015.522304,top1_acc,-78.36062673649637 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,22107.783168,top1_acc,-78.4357247131028 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 938, 18: 2363, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,22722.9696,top1_acc,-77.80073263370281 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 3041, 15: 1926, 16: 989, 17: 3018, 18: 1554, 19: 693, 20: 517, 21: 280, 22: 3072, 23: 752})])",MACs,20443.889664,top1_acc,-77.41909713072724 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 989, 17: 938, 18: 2363, 19: 3072, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,19002.949632,top1_acc,-77.75163934320658 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,17867.538432,top1_acc,-77.95099741285911 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 576, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,22587.31008,top1_acc,-78.18821861460536 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,17570.85696,top1_acc,-77.88281374320961 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 3018, 18: 1554, 19: 3072, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,19576.25856,top1_acc,-77.76219331153324 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,19267.190784,top1_acc,-78.03293021054046 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 448, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 3050, 14: 3072, 15: 1926, 16: 3072, 17: 3018, 18: 789, 19: 693, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,24831.5904,top1_acc,-78.06423245301332 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,28290.318336,top1_acc,-78.7818271793259 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 704, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1898, 14: 2670, 15: 1926, 16: 3072, 17: 938, 18: 1554, 19: 3072, 20: 517, 21: 653, 22: 332, 23: 752})])",MACs,21597.585408,top1_acc,-77.63289311023425 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3043, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,21722.038272,top1_acc,-78.45883754124276 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 2078, 21: 280, 22: 332, 23: 752})])",MACs,21123.366912,top1_acc,-78.35304942966194 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 3043, 16: 989, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,20571.291648,top1_acc,-78.00609773670165 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 3072, 15: 3043, 16: 3072, 17: 938, 18: 2363, 19: 3072, 20: 1175, 21: 280, 22: 3072, 23: 1138})])",MACs,26880.638976,top1_acc,-78.23250578989138 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 576, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 3018, 18: 2363, 19: 3072, 20: 1175, 21: 653, 22: 3072, 23: 1138})])",MACs,23459.069952,top1_acc,-78.25111166368303 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 3072, 23: 1138})])",MACs,24649.334784,top1_acc,-78.68846261588048 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 3050, 14: 3072, 15: 2662, 16: 1807, 17: 3018, 18: 2363, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,26607.550464,top1_acc,-78.67848930315913 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,18273.337344,top1_acc,-78.05345359672852 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,20930.494464,top1_acc,-78.51593711610086 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,20283.457536,top1_acc,-78.24745976257512 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 768, 7: 768, 8: 576, 9: 768, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,24396.300288,top1_acc,-78.12638003767236 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1898, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,27199.73376,top1_acc,-78.56595529146695 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 517, 21: 653, 22: 332, 23: 752})])",MACs,17450.532864,top1_acc,-77.55571076851795 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,22485.270528,top1_acc,-78.56684360548103 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 989, 17: 3018, 18: 2363, 19: 693, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,22169.714688,top1_acc,-77.86960625828685 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 3041, 15: 2662, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,22737.125376,top1_acc,-78.31407615411848 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,24496.570368,top1_acc,-78.61627301559787 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,21016.608768,top1_acc,-78.20571261423265 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 3018, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,19739.049984,top1_acc,-77.9940738230806 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 966, 13: 1052, 14: 1940, 15: 3043, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,21534.47424,top1_acc,-77.94001777744134 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,24849.874944,top1_acc,-78.47830176192389 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 3041, 15: 3043, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,26958.495744,top1_acc,-78.7620643584786 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,19730.792448,top1_acc,-78.08878637834431 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,20350.697472,top1_acc,-78.08161407013979 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,15928.786944,top1_acc,-77.35345015664008 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 704, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18869.649408,top1_acc,-77.2477629759615 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 2670, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,26685.997056,top1_acc,-78.63919907315389 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,17768.448,top1_acc,-77.85568036906864 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,22485.270528,top1_acc,-78.4707938293114 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 3018, 18: 789, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,18078.1056,top1_acc,-77.75792051660197 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1940, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,26701.922304,top1_acc,-78.81282501972142 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,19547.947008,top1_acc,-78.18251514543311 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18013.814784,top1_acc,-77.81927197834382 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,23877.255168,top1_acc,-78.39758665651976 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 704, 5: 448, 6: 576, 7: 512, 8: 768, 9: 768, 10: 384, 11: 768, 12: 966, 13: 1898, 14: 1040, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 280, 22: 332, 23: 752})])",MACs,23967.49824,top1_acc,-78.04299337987997 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,16400.646144,top1_acc,-77.67345754534325 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 2670, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 653, 22: 3072, 23: 505})])",MACs,19297.271808,top1_acc,-77.37489162956963 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,16002.514944,top1_acc,-77.66565659311577 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,17025.26976,top1_acc,-77.62273147705432 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,19453.575168,top1_acc,-78.02789739828579 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3043, 16: 3072, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 332, 23: 752})])",MACs,19713.097728,top1_acc,-77.08256564551546 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 3050, 14: 3072, 15: 3043, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,28674.29376,top1_acc,-78.74902185186043 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 448, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1940, 15: 1926, 16: 989, 17: 3018, 18: 2363, 19: 693, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,22012.821504,top1_acc,-78.03778801066193 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,15845.031936,top1_acc,-77.54417395144678 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,17647.53408,top1_acc,-77.96819310298024 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 2291, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,19575.668736,top1_acc,-78.03624917405648 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,27494.64576,top1_acc,-78.88171560107351 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,24741.937152,top1_acc,-78.3215312203983 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,17856.9216,top1_acc,-77.67700289168451 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3072, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,18693.292032,top1_acc,-77.84907182061681 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 1926, 16: 989, 17: 3018, 18: 1554, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,19169.28,top1_acc,-77.59182546625482 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 1940, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,26311.458816,top1_acc,-78.68170184475501 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 517, 21: 280, 22: 332, 23: 505})])",MACs,15236.923392,top1_acc,-77.20124545424841 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,15268.184064,top1_acc,-77.0768490676272 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18909.75744,top1_acc,-77.79614872988748 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 1175, 21: 653, 22: 3072, 23: 1138})])",MACs,25118.244864,top1_acc,-78.57197216575622 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 3072, 17: 938, 18: 1554, 19: 3072, 20: 517, 21: 653, 22: 3072, 23: 505})])",MACs,20741.16096,top1_acc,-77.75832116776853 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,17991.401472,top1_acc,-78.02388093820475 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 1138})])",MACs,16558.129152,top1_acc,-77.60141526347525 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 1421, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,15508.832256,top1_acc,-77.27540758544421 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 704, 5: 512, 6: 768, 7: 768, 8: 768, 9: 768, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,25784.15616,top1_acc,-78.8531765047891 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 517, 21: 280, 22: 665, 23: 505})])",MACs,17537.236992,top1_acc,-77.23154155495172 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 768, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 1421, 20: 1175, 21: 280, 22: 3072, 23: 752})])",MACs,22472.884224,top1_acc,-78.28860488768798 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 1007, 16: 3072, 17: 3018, 18: 1554, 19: 693, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,18706.857984,top1_acc,-77.90913734281271 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 3043, 16: 3072, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,19547.947008,top1_acc,-77.84440723569186 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 3072, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,23762.239488,top1_acc,-78.54237164254779 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,16551.641088,top1_acc,-77.54232330382281 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,16431.316992,top1_acc,-77.65720952336603 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,25916.86656,top1_acc,-78.68980916532352 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,16445.472768,top1_acc,-77.4073416038736 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,15268.184064,top1_acc,-77.09601119332092 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 517, 21: 653, 22: 332, 23: 752})])",MACs,21342.191616,top1_acc,-78.2522980649303 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 1807, 17: 938, 18: 2363, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,23926.800384,top1_acc,-78.64697945603487 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,26097.352704,top1_acc,-78.71480900346943 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 1926, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19723.71456,top1_acc,-78.08264474309313 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 3050, 14: 3072, 15: 3043, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,28382.920704,top1_acc,-78.80740758905421 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,20810.760192,top1_acc,-78.39282099436825 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 789, 19: 693, 20: 2078, 21: 280, 22: 3072, 23: 752})])",MACs,17996.709888,top1_acc,-77.22306371479931 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 517, 21: 653, 22: 332, 23: 752})])",MACs,15942.352896,top1_acc,-77.3589628589501 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,24992.022528,top1_acc,-78.74260602310304 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 938, 18: 2363, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 1138})])",MACs,21636.513792,top1_acc,-78.2545079813462 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 3072, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,21258.436608,top1_acc,-78.18177648226269 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 768, 10: 384, 11: 768, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 3072, 23: 752})])",MACs,23880.204288,top1_acc,-78.05347330720863 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1940, 15: 2662, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 505})])",MACs,19746.717696,top1_acc,-77.95855887868073 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 789, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,15823.798272,top1_acc,-77.35629627690611 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 989, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 505})])",MACs,18971.099136,top1_acc,-77.84559152894718 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 768, 9: 320, 10: 384, 11: 768, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 3072, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,27069.382656,top1_acc,-78.77668593339259 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 768, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 3041, 15: 3072, 16: 3072, 17: 3018, 18: 789, 19: 693, 20: 517, 21: 653, 22: 332, 23: 1138})])",MACs,21876.57216,top1_acc,-77.83471111766114 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,17018.191872,top1_acc,-77.84318097176025 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,19789.774848,top1_acc,-78.13953614944548 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,20936.982528,top1_acc,-78.17203491880318 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 3072, 16: 989, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,20450.377728,top1_acc,-78.01300808859253 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 1926, 16: 1807, 17: 3018, 18: 1554, 19: 3009, 20: 1175, 21: 280, 22: 332, 23: 1138})])",MACs,20101.20192,top1_acc,-78.18474650912741 +"OrderedDict([(, {0: 768, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 653, 22: 3072, 23: 752})])",MACs,22866.886656,top1_acc,-78.51092813692125 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,18571.788288,top1_acc,-77.69147873860152 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 3018, 18: 1554, 19: 693, 20: 517, 21: 653, 22: 332, 23: 505})])",MACs,16683.761664,top1_acc,-77.45002724466687 +"OrderedDict([(, {0: 576, 1: 512, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1898, 14: 2670, 15: 3043, 16: 1807, 17: 3018, 18: 2363, 19: 3072, 20: 2078, 21: 653, 22: 332, 23: 752})])",MACs,24606.867456,top1_acc,-78.62880106715556 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,19489.554432,top1_acc,-78.28679796661078 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 512, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,15845.031936,top1_acc,-77.49580056942766 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 512, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 505})])",MACs,18053.922816,top1_acc,-77.88655364456235 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 2662, 16: 1807, 17: 938, 18: 1554, 19: 3009, 20: 2078, 21: 653, 22: 332, 23: 1138})])",MACs,21158.166528,top1_acc,-78.57450649864307 +"OrderedDict([(, {0: 768, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3072, 20: 2078, 21: 280, 22: 332, 23: 505})])",MACs,18127.060992,top1_acc,-77.54104955529823 +"OrderedDict([(, {0: 576, 1: 448, 2: 768, 3: 576, 4: 640, 5: 512, 6: 576, 7: 512, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3058, 13: 1052, 14: 1940, 15: 3043, 16: 1807, 17: 938, 18: 2363, 19: 3009, 20: 2078, 21: 653, 22: 3072, 23: 505})])",MACs,23403.626496,top1_acc,-78.5397428749571 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 640, 5: 512, 6: 768, 7: 768, 8: 576, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 2662, 16: 3072, 17: 3018, 18: 1554, 19: 3072, 20: 1175, 21: 653, 22: 3072, 23: 1138})])",MACs,23165.3376,top1_acc,-78.25210914412115 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 1908, 13: 1052, 14: 1940, 15: 1926, 16: 989, 17: 938, 18: 1554, 19: 3009, 20: 1175, 21: 653, 22: 332, 23: 752})])",MACs,19103.809536,top1_acc,-77.91160031504944 +"OrderedDict([(, {0: 576, 1: 512, 2: 576, 3: 576, 4: 640, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 3072, 13: 1052, 14: 1040, 15: 2662, 16: 1807, 17: 938, 18: 789, 19: 3009, 20: 1175, 21: 280, 22: 665, 23: 505})])",MACs,19649.98656,top1_acc,-78.15775868290581 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 576, 4: 576, 5: 448, 6: 576, 7: 768, 8: 768, 9: 320, 10: 384, 11: 384, 12: 966, 13: 1052, 14: 1040, 15: 1926, 16: 3072, 17: 938, 18: 1554, 19: 693, 20: 1175, 21: 280, 22: 332, 23: 752})])",MACs,17565.548544,top1_acc,-77.42931121734983 +"OrderedDict([(, {0: 576, 1: 448, 2: 576, 3: 768, 4: 704, 5: 512, 6: 576, 7: 768, 8: 768, 9: 320, 10: 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0000000000000000000000000000000000000000..312af4ae2a74cb0b770412c06a93a31e087b666f --- /dev/null +++ b/eftnas-s1-bert-base-sst2/README.md @@ -0,0 +1,84 @@ +--- +language: +- en +license: apache-2.0 +tags: +- generated_from_trainer +datasets: +- glue +metrics: +- accuracy +model-index: +- name: first_try + results: + - task: + name: Text Classification + type: text-classification + dataset: + name: GLUE SST2 + type: glue + config: sst2 + split: validation + args: sst2 + metrics: + - name: Accuracy + type: accuracy + value: 0.9151376146788991 +--- + + + +# first_try + +This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE SST2 dataset. +It achieves the following results on the evaluation set: +- Loss: 0.3079 +- Accuracy: 0.9151 + +## Model description + +More information needed + +## Intended uses & limitations + +More information needed + +## Training and evaluation data + +More information needed + +## Training procedure + +### Training hyperparameters + +The following hyperparameters were used during training: +- learning_rate: 2e-05 +- train_batch_size: 32 +- eval_batch_size: 128 +- seed: 42 +- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 +- lr_scheduler_type: linear +- num_epochs: 6 +- mixed_precision_training: Native AMP + +### Training results + +| Training Loss | Epoch | Step | Validation Loss | Accuracy | | +|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| +| 0.1786 | 1.0 | 2105 | 0.3156 | 0.9151 | OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})]) | +| 0.1786 | 1.0 | 2105 | 0.2938 | 0.9220 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0868 | 2.0 | 4210 | 0.3035 | 0.9197 | OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})]) | +| 0.0868 | 2.0 | 4210 | 0.3008 | 0.9232 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0371 | 3.0 | 6315 | 0.3073 | 0.9151 | OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})]) | +| 0.0371 | 3.0 | 6315 | 0.2674 | 0.9289 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | +| 0.0249 | 4.0 | 8420 | 0.3040 | 0.9140 | OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})]) | +| 0.0249 | 4.0 | 8420 | 0.2658 | 0.9312 | OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 768, 5: 768, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3072, 14: 3072, 15: 3072, 16: 3072, 17: 3072, 18: 3072, 19: 3072, 20: 3072, 21: 3072, 22: 3072, 23: 3072})]) | + + +### Framework versions + +- Transformers 4.29.1 +- Pytorch 1.12.1 +- Datasets 2.13.1 +- Tokenizers 0.13.3 diff --git a/eftnas-s1-bert-base-sst2/all_results.json b/eftnas-s1-bert-base-sst2/all_results.json new file mode 100644 index 0000000000000000000000000000000000000000..c3b1ccad878d4095edfcd5ad7f925a1dac152eff --- /dev/null +++ b/eftnas-s1-bert-base-sst2/all_results.json @@ -0,0 +1,14 @@ +{ + "epoch": 4.0, + "eval_accuracy": 0.9151376146788991, + "eval_loss": 0.3078511655330658, + "eval_runtime": 0.7017, + "eval_samples": 872, + "eval_samples_per_second": 1242.727, + "eval_steps_per_second": 9.976, + "train_loss": 0.11200937262057126, + "train_runtime": 14148.7677, + "train_samples": 67349, + "train_samples_per_second": 19.04, + "train_steps_per_second": 0.595 +} \ No newline at end of file diff --git a/eftnas-s1-bert-base-sst2/cache_MACs.csv b/eftnas-s1-bert-base-sst2/cache_MACs.csv new file mode 100644 index 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1, 3)",6933.120512 +"(3, 0, 0, 2, 3, 0, 4, 1, 0, 0, 0, 1, 1, 3, 1, 4, 1, 0, 1, 4, 4, 1, 0, 1)",8758.953472 +"(0, 1, 1, 3, 3, 3, 0, 2, 0, 0, 0, 1, 0, 3, 2, 2, 2, 4, 1, 4, 0, 4, 3, 4)",7605.978624 +"(3, 2, 3, 1, 3, 2, 2, 2, 2, 0, 0, 2, 2, 3, 3, 3, 2, 3, 2, 1, 1, 2, 0, 3)",7915.308544 +"(2, 0, 0, 2, 3, 1, 1, 1, 0, 1, 0, 0, 2, 4, 1, 2, 2, 1, 0, 2, 4, 2, 3, 0)",8865.842688 +"(2, 1, 2, 4, 4, 3, 2, 1, 0, 1, 1, 2, 4, 0, 2, 4, 2, 4, 0, 3, 2, 2, 1, 3)",7091.979776 +"(2, 0, 0, 2, 0, 1, 1, 1, 1, 3, 0, 0, 3, 4, 4, 2, 2, 1, 0, 2, 1, 2, 3, 1)",8794.342912 +"(0, 1, 0, 3, 0, 2, 0, 1, 2, 2, 1, 2, 4, 1, 3, 3, 3, 3, 4, 3, 4, 1, 3, 4)",6944.654848 +"(3, 0, 0, 4, 3, 1, 3, 1, 0, 1, 1, 2, 3, 4, 2, 3, 2, 1, 1, 4, 3, 3, 0, 1)",7732.594176 +"(2, 1, 2, 1, 0, 3, 0, 3, 1, 1, 0, 1, 3, 0, 4, 0, 1, 2, 2, 2, 0, 4, 0, 2)",8255.440384 +"(3, 2, 3, 1, 3, 2, 2, 0, 0, 0, 0, 2, 2, 3, 4, 3, 2, 3, 2, 1, 3, 2, 0, 1)",8262.780416 +"(0, 2, 3, 1, 2, 1, 0, 1, 2, 3, 1, 0, 3, 1, 2, 3, 2, 1, 0, 2, 4, 0, 3, 4)",7947.290112 +"(1, 1, 0, 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2, 3, 4, 4, 0, 4, 3, 3)",6732.383744 +"(0, 2, 0, 0, 3, 1, 0, 1, 2, 3, 0, 0, 1, 1, 3, 1, 1, 1, 0, 4, 4, 1, 4, 2)",8581.285376 +"(2, 2, 0, 3, 0, 3, 3, 3, 2, 1, 1, 1, 4, 2, 2, 4, 3, 2, 1, 1, 1, 2, 4, 3)",7057.901056 +"(1, 1, 0, 3, 4, 3, 3, 2, 0, 3, 1, 1, 3, 4, 2, 3, 2, 2, 2, 4, 4, 4, 4, 3)",6297.748992 +"(3, 0, 0, 1, 3, 3, 3, 3, 2, 2, 1, 2, 4, 4, 2, 3, 3, 1, 1, 3, 4, 0, 4, 4)",6586.828288 +"(3, 1, 0, 3, 4, 0, 4, 3, 2, 2, 1, 2, 1, 4, 4, 4, 3, 3, 2, 4, 4, 1, 3, 4)",6199.772672 +"(3, 2, 0, 2, 3, 3, 0, 0, 1, 2, 1, 2, 4, 0, 4, 2, 2, 3, 3, 4, 4, 4, 1, 4)",6641.485312 +"(2, 1, 2, 4, 3, 2, 2, 2, 0, 1, 1, 2, 4, 3, 0, 4, 4, 4, 2, 3, 2, 2, 1, 3)",6785.271296 +"(0, 2, 0, 3, 0, 2, 3, 2, 1, 3, 0, 1, 1, 3, 3, 4, 3, 2, 1, 1, 0, 2, 1, 1)",8442.217984 +"(2, 1, 0, 3, 0, 1, 0, 1, 1, 1, 0, 0, 3, 1, 1, 3, 2, 3, 0, 2, 1, 1, 3, 3)",8778.745344 +"(2, 2, 1, 4, 4, 3, 1, 3, 1, 1, 0, 1, 3, 3, 2, 3, 2, 3, 2, 2, 2, 3, 4, 3)",7006.586368 +"(3, 2, 3, 1, 2, 3, 4, 3, 2, 3, 1, 0, 4, 4, 4, 4, 2, 1, 2, 2, 4, 0, 3, 4)",6449.858048 +"(3, 0, 3, 3, 4, 2, 3, 2, 2, 0, 1, 2, 0, 3, 1, 3, 4, 3, 4, 4, 2, 4, 2, 2)",6653.609472 +"(2, 2, 2, 4, 4, 3, 2, 1, 0, 3, 1, 2, 4, 1, 2, 2, 2, 4, 0, 4, 2, 2, 4, 3)",6646.728192 +"(1, 2, 2, 2, 0, 3, 4, 1, 2, 3, 1, 1, 3, 0, 3, 1, 2, 1, 2, 4, 1, 3, 1, 3)",7425.49248 +"(2, 1, 2, 3, 4, 3, 0, 3, 2, 1, 0, 1, 3, 1, 4, 1, 1, 2, 2, 4, 0, 1, 4, 3)",7400.392192 +"(3, 2, 0, 1, 3, 0, 0, 2, 2, 0, 0, 2, 2, 3, 2, 3, 2, 3, 2, 1, 3, 1, 0, 4)",8337.884672 +"(3, 2, 0, 2, 2, 3, 4, 3, 0, 3, 1, 2, 4, 4, 4, 3, 4, 3, 4, 2, 0, 4, 3, 1)",6418.400768 +"(0, 2, 0, 0, 0, 1, 0, 1, 1, 3, 0, 0, 4, 4, 3, 3, 1, 1, 4, 3, 4, 4, 4, 2)",7571.113472 +"(0, 1, 3, 3, 4, 2, 2, 1, 2, 2, 1, 2, 1, 1, 3, 3, 3, 3, 0, 4, 4, 2, 3, 4)",6641.747456 +"(0, 0, 2, 3, 3, 1, 1, 1, 1, 3, 1, 0, 3, 0, 2, 1, 3, 4, 0, 4, 0, 3, 0, 2)",8219.526656 +"(2, 0, 0, 1, 2, 3, 2, 0, 0, 2, 1, 1, 1, 3, 1, 0, 2, 3, 2, 3, 0, 2, 2, 4)",8169.588224 +"(3, 1, 0, 3, 4, 0, 4, 3, 2, 2, 1, 2, 1, 4, 4, 4, 1, 2, 2, 4, 1, 1, 3, 4)",6810.43712 +"(0, 1, 1, 2, 3, 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1, 2, 3)",8704.689664 +"(3, 2, 0, 1, 3, 3, 4, 0, 2, 3, 1, 1, 4, 0, 4, 4, 2, 1, 2, 2, 4, 0, 3, 4)",6799.689216 +"(0, 0, 1, 3, 3, 3, 1, 0, 1, 0, 0, 2, 3, 0, 4, 2, 3, 3, 2, 1, 0, 3, 0, 2)",8549.172736 +"(3, 2, 3, 1, 2, 3, 4, 3, 1, 3, 1, 0, 4, 3, 4, 3, 2, 1, 2, 1, 4, 3, 3, 2)",6803.359232 +"(3, 1, 0, 3, 4, 3, 3, 2, 0, 2, 1, 1, 1, 1, 2, 3, 4, 3, 4, 4, 4, 4, 4, 3)",6112.937472 +"(2, 1, 2, 3, 4, 3, 0, 1, 2, 1, 0, 0, 3, 0, 4, 0, 2, 3, 0, 4, 4, 4, 2, 2)",7290.226176 +"(0, 1, 1, 2, 3, 3, 0, 2, 0, 0, 0, 2, 0, 0, 0, 4, 2, 4, 3, 3, 0, 4, 1, 4)",7907.706368 +"(3, 0, 3, 3, 3, 2, 3, 2, 0, 0, 1, 2, 3, 4, 1, 3, 3, 1, 2, 4, 2, 4, 2, 3)",7019.628032 +"(3, 2, 0, 1, 2, 1, 4, 3, 0, 3, 1, 0, 3, 4, 4, 3, 2, 3, 4, 2, 0, 0, 3, 1)",7697.073664 +"(3, 1, 3, 3, 2, 3, 4, 3, 2, 3, 1, 0, 4, 4, 4, 4, 2, 1, 2, 2, 4, 3, 3, 4)",6102.976 +"(3, 0, 0, 2, 4, 1, 1, 1, 1, 3, 0, 2, 3, 4, 1, 3, 4, 3, 0, 2, 4, 4, 3, 3)",7121.143296 +"(0, 1, 0, 2, 3, 3, 0, 0, 1, 2, 0, 2, 0, 0, 0, 2, 2, 4, 3, 4, 4, 4, 3, 3)",7440.434688 +"(3, 2, 0, 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3)",7994.67264 +"(0, 2, 3, 3, 2, 2, 4, 1, 2, 2, 1, 2, 4, 4, 3, 1, 4, 3, 0, 4, 4, 3, 3, 4)",5934.024192 +"(3, 2, 0, 2, 3, 3, 0, 0, 1, 2, 0, 1, 4, 0, 4, 2, 4, 3, 3, 4, 4, 4, 1, 4)",6728.058368 +"(3, 2, 1, 1, 2, 3, 0, 3, 2, 0, 1, 0, 4, 3, 4, 4, 4, 1, 4, 3, 0, 4, 3, 4)",6537.152 +"(0, 1, 0, 3, 4, 1, 1, 1, 1, 1, 0, 1, 4, 0, 1, 2, 4, 1, 2, 4, 4, 2, 2, 3)",7676.82304 +"(2, 2, 0, 1, 4, 0, 2, 3, 2, 2, 1, 2, 1, 4, 4, 4, 3, 3, 2, 4, 0, 1, 3, 4)",6761.022976 +"(2, 1, 0, 3, 4, 3, 3, 2, 0, 3, 1, 1, 4, 4, 1, 3, 2, 2, 4, 4, 4, 4, 4, 4)",5782.83264 +"(3, 1, 0, 3, 4, 3, 3, 2, 0, 2, 1, 1, 1, 1, 2, 3, 4, 2, 4, 4, 4, 4, 4, 3)",6221.661696 +"(3, 1, 3, 2, 2, 0, 4, 3, 2, 3, 1, 2, 1, 4, 4, 4, 4, 1, 2, 2, 4, 4, 3, 4)",6046.94272 +"(3, 0, 0, 2, 4, 1, 0, 1, 1, 3, 1, 0, 3, 0, 1, 1, 2, 3, 0, 2, 4, 4, 3, 3)",7827.424768 +"(0, 2, 3, 3, 3, 2, 4, 2, 2, 2, 1, 2, 4, 4, 4, 4, 3, 3, 4, 4, 4, 3, 3, 4)",5257.823744 +"(3, 0, 0, 3, 3, 1, 0, 0, 1, 2, 1, 1, 4, 3, 4, 1, 4, 3, 4, 4, 4, 4, 3, 3)",6389.761536 +"(2, 0, 2, 2, 4, 3, 0, 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4)",6811.551232 +"(0, 0, 3, 3, 4, 1, 1, 2, 2, 3, 1, 0, 3, 4, 4, 4, 2, 4, 4, 2, 4, 2, 0, 3)",6931.875328 +"(3, 1, 3, 3, 4, 2, 2, 2, 0, 3, 1, 2, 4, 4, 4, 0, 2, 4, 4, 2, 0, 4, 3, 4)",6095.308288 +"(0, 1, 0, 3, 4, 1, 3, 3, 1, 3, 1, 2, 3, 4, 4, 3, 4, 2, 4, 4, 4, 4, 4, 4)",5582.161408 +"(3, 1, 3, 3, 4, 3, 3, 2, 2, 2, 1, 1, 4, 4, 0, 2, 4, 2, 4, 3, 4, 4, 4, 4)",5371.397632 +"(3, 2, 1, 1, 2, 3, 1, 3, 2, 0, 1, 0, 4, 3, 4, 4, 4, 1, 4, 2, 0, 4, 3, 3)",6751.12704 +"(0, 0, 0, 2, 2, 0, 1, 2, 2, 1, 1, 1, 1, 0, 4, 2, 4, 1, 2, 2, 4, 2, 3, 3)",7864.321536 +"(3, 2, 3, 3, 4, 3, 4, 1, 2, 3, 1, 0, 4, 4, 4, 3, 4, 3, 4, 4, 4, 4, 4, 4)",4992.79616 +"(3, 2, 3, 2, 4, 1, 1, 3, 1, 3, 1, 2, 4, 0, 4, 2, 4, 1, 2, 2, 4, 4, 2, 4)",6451.037696 +"(0, 0, 0, 4, 3, 1, 1, 2, 2, 1, 1, 0, 3, 1, 4, 3, 3, 4, 2, 2, 2, 3, 0, 4)",7778.338304 +"(3, 0, 3, 2, 2, 3, 4, 3, 2, 3, 1, 2, 4, 4, 2, 4, 3, 1, 2, 2, 4, 4, 3, 3)",6128.141824 +"(0, 0, 1, 3, 4, 3, 1, 2, 2, 3, 1, 1, 3, 4, 4, 3, 4, 3, 4, 4, 4, 4, 0, 3)",6069.093888 +"(0, 0, 3, 3, 2, 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4)",7303.9232 +"(2, 2, 2, 4, 4, 3, 3, 2, 2, 3, 1, 2, 4, 4, 4, 0, 4, 4, 2, 4, 4, 4, 1, 3)",5474.420224 +"(0, 2, 3, 3, 2, 0, 1, 2, 2, 0, 1, 0, 1, 0, 4, 2, 4, 4, 2, 2, 2, 2, 0, 3)",8118.404608 +"(3, 2, 3, 3, 4, 3, 4, 2, 2, 3, 1, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4)",4423.419392 +"(2, 2, 3, 2, 4, 0, 1, 2, 2, 1, 1, 2, 4, 0, 4, 2, 4, 1, 4, 2, 4, 4, 4, 4)",6069.55264 +"(3, 2, 3, 3, 2, 3, 3, 3, 2, 3, 1, 2, 4, 4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 4)",4671.66976 +"(0, 0, 3, 4, 3, 0, 4, 3, 2, 3, 1, 0, 3, 4, 4, 4, 4, 1, 2, 2, 2, 3, 0, 4)",7074.612736 +"(3, 0, 0, 3, 3, 1, 1, 3, 2, 3, 1, 2, 4, 0, 4, 4, 4, 1, 4, 2, 2, 3, 2, 4)",6753.158656 +"(0, 2, 3, 2, 2, 3, 3, 2, 2, 1, 1, 2, 1, 4, 4, 4, 4, 4, 2, 2, 4, 2, 3, 3)",6144.26368 +"(3, 0, 2, 3, 3, 3, 1, 3, 2, 1, 1, 1, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 2, 4)",5544.084992 +"(3, 1, 3, 3, 3, 3, 3, 2, 2, 3, 1, 2, 4, 4, 4, 4, 4, 4, 2, 2, 4, 4, 3, 4)",5147.067904 +"(0, 0, 3, 3, 2, 1, 1, 2, 2, 0, 1, 0, 1, 0, 4, 4, 3, 4, 2, 2, 2, 2, 0, 3)",8164.869632 +"(3, 1, 2, 4, 2, 2, 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4)",5842.667008 +"(0, 2, 3, 3, 3, 0, 1, 2, 2, 1, 1, 1, 3, 0, 4, 2, 4, 1, 2, 2, 4, 3, 2, 4)",7005.931008 +"(0, 2, 0, 3, 2, 0, 1, 2, 2, 0, 1, 2, 1, 0, 4, 2, 4, 1, 4, 2, 4, 4, 0, 3)",7578.322432 +"(0, 1, 3, 3, 3, 3, 3, 3, 2, 3, 1, 2, 4, 4, 4, 4, 4, 4, 2, 2, 4, 3, 0, 4)",5748.295168 +"(3, 0, 3, 3, 3, 0, 1, 2, 2, 3, 1, 1, 4, 4, 4, 4, 4, 4, 2, 3, 4, 4, 3, 4)",5687.346688 +"(3, 0, 0, 3, 4, 3, 1, 3, 1, 3, 1, 2, 4, 4, 4, 4, 3, 1, 2, 4, 2, 4, 4, 4)",6028.396032 +"(0, 2, 3, 2, 3, 0, 1, 3, 2, 1, 1, 0, 3, 4, 4, 4, 3, 4, 2, 3, 4, 2, 4, 4)",6386.484736 +"(3, 0, 3, 4, 3, 1, 1, 2, 2, 1, 1, 0, 3, 4, 4, 4, 3, 4, 4, 2, 2, 4, 3, 4)",6297.093632 +"(0, 2, 3, 3, 2, 3, 1, 2, 2, 0, 1, 0, 1, 4, 4, 4, 3, 1, 2, 2, 2, 3, 0, 4)",7519.340032 +"(0, 0, 0, 2, 3, 0, 1, 2, 2, 1, 1, 1, 3, 0, 4, 2, 4, 1, 2, 2, 4, 2, 4, 3)",7490.37312 +"(0, 2, 3, 3, 4, 0, 1, 2, 2, 3, 1, 1, 4, 4, 4, 2, 4, 1, 2, 2, 4, 4, 4, 3)",6212.290048 +"(3, 2, 3, 3, 4, 3, 4, 2, 2, 3, 1, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4)",4396.156416 +"(0, 2, 3, 3, 4, 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4)",6172.313088 +"(3, 2, 3, 3, 4, 3, 0, 3, 2, 3, 1, 1, 4, 4, 4, 4, 4, 4, 2, 3, 4, 4, 4, 4)",5037.03296 +"(0, 2, 3, 2, 4, 0, 1, 2, 2, 3, 1, 1, 4, 4, 4, 2, 4, 1, 2, 2, 4, 4, 4, 3)",6266.816 +"(3, 0, 3, 3, 3, 3, 1, 2, 2, 1, 1, 1, 3, 4, 4, 4, 4, 1, 2, 2, 4, 4, 4, 4)",5891.098112 +"(3, 1, 3, 3, 4, 3, 1, 3, 2, 1, 1, 0, 4, 4, 4, 4, 4, 3, 4, 2, 4, 4, 4, 4)",5401.282048 +"(3, 2, 3, 3, 4, 3, 3, 2, 2, 3, 1, 2, 4, 0, 4, 4, 3, 1, 4, 2, 4, 4, 4, 4)",5379.917312 +"(0, 2, 3, 4, 3, 1, 1, 3, 2, 1, 1, 0, 1, 4, 4, 4, 4, 4, 4, 2, 4, 3, 3, 4)",6150.751744 +"(0, 0, 3, 3, 3, 0, 1, 2, 2, 0, 1, 0, 3, 4, 4, 4, 3, 1, 2, 2, 4, 2, 2, 4)",7430.342144 +"(0, 1, 3, 3, 4, 3, 1, 2, 2, 3, 1, 1, 4, 4, 4, 4, 4, 1, 4, 2, 4, 4, 4, 4)",5454.038528 +"(2, 0, 3, 2, 4, 0, 4, 2, 2, 1, 1, 1, 1, 4, 4, 4, 3, 4, 4, 2, 4, 4, 4, 4)",5683.807744 +"(0, 2, 3, 2, 3, 0, 1, 2, 2, 1, 1, 0, 1, 4, 4, 4, 3, 4, 2, 3, 4, 2, 4, 4)",6573.590016 +"(3, 1, 3, 3, 4, 1, 1, 3, 2, 3, 1, 2, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4)",5118.428672 +"(3, 1, 1, 4, 4, 3, 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4)",4450.682368 +"(0, 2, 3, 3, 4, 3, 1, 2, 2, 3, 1, 0, 4, 4, 4, 4, 4, 4, 2, 2, 4, 4, 4, 4)",5614.536192 +"(3, 2, 3, 3, 3, 0, 1, 2, 2, 0, 1, 1, 4, 4, 4, 4, 3, 4, 2, 2, 4, 3, 4, 4)",5946.410496 +"(0, 2, 3, 3, 4, 3, 3, 2, 2, 3, 1, 1, 4, 4, 4, 2, 4, 2, 2, 4, 4, 4, 4, 3)",5442.504192 +"(3, 2, 3, 3, 3, 3, 0, 3, 2, 3, 1, 1, 4, 4, 4, 4, 4, 1, 2, 3, 4, 4, 3, 4)",5510.53056 +"(3, 2, 3, 3, 4, 3, 0, 2, 2, 3, 1, 1, 4, 4, 4, 4, 4, 4, 2, 3, 4, 2, 4, 4)",5321.065984 +"(0, 2, 3, 2, 4, 0, 3, 2, 2, 3, 1, 1, 4, 4, 4, 4, 3, 4, 2, 3, 4, 4, 4, 4)",5430.969856 +"(0, 2, 3, 2, 4, 3, 1, 3, 2, 1, 1, 2, 3, 4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 4)",5179.57376 +"(3, 2, 3, 3, 3, 3, 4, 3, 2, 3, 1, 1, 4, 4, 4, 4, 4, 4, 2, 4, 4, 4, 4, 4)",4679.730688 +"(0, 2, 0, 2, 3, 0, 1, 2, 2, 1, 1, 1, 1, 0, 4, 2, 3, 1, 2, 2, 4, 2, 4, 3)",7553.418752 +"(3, 1, 1, 4, 4, 3, 2, 3, 2, 3, 1, 0, 3, 4, 4, 3, 4, 4, 2, 3, 4, 4, 4, 4)",5471.471104 +"(3, 2, 3, 3, 3, 0, 0, 3, 2, 3, 1, 1, 4, 4, 4, 4, 4, 3, 2, 2, 4, 4, 3, 3)",5835.326976 +"(3, 2, 3, 4, 3, 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4)",4757.52192 +"(3, 2, 3, 4, 4, 3, 3, 3, 2, 3, 1, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4)",4368.89344 +"(3, 2, 3, 4, 4, 3, 1, 3, 2, 3, 1, 2, 4, 4, 4, 4, 4, 4, 2, 3, 4, 4, 4, 4)",4955.244032 +"(3, 2, 3, 4, 4, 3, 1, 2, 2, 3, 1, 2, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4)",4900.914688 +"(3, 2, 3, 3, 3, 3, 0, 2, 2, 3, 1, 1, 4, 4, 4, 4, 4, 4, 2, 3, 4, 2, 4, 4)",5375.591936 +"(3, 2, 3, 3, 4, 3, 0, 3, 2, 3, 1, 1, 4, 4, 4, 4, 4, 3, 2, 3, 4, 4, 3, 4)",5294.196224 +"(0, 2, 3, 3, 3, 3, 3, 3, 2, 0, 1, 0, 1, 4, 4, 4, 3, 4, 4, 4, 4, 3, 4, 4)",5722.932736 +"(3, 2, 3, 3, 3, 3, 1, 3, 2, 3, 1, 1, 4, 4, 4, 4, 4, 4, 2, 4, 4, 4, 4, 4)",4925.097472 +"(0, 2, 3, 2, 4, 0, 1, 2, 2, 1, 1, 0, 0, 4, 4, 3, 3, 4, 2, 3, 4, 3, 3, 4)",6647.055872 +"(3, 0, 3, 3, 4, 0, 1, 2, 2, 3, 1, 2, 4, 4, 4, 4, 4, 4, 2, 2, 4, 4, 2, 4)",5848.761856 +"(3, 1, 3, 4, 4, 3, 2, 3, 2, 3, 1, 2, 4, 4, 4, 4, 4, 4, 2, 3, 4, 4, 4, 4)",4873.455104 +"(3, 2, 1, 4, 4, 0, 1, 3, 2, 1, 1, 0, 1, 4, 4, 4, 3, 4, 2, 2, 4, 2, 4, 4)",6387.72992 +"(3, 2, 3, 4, 4, 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4)",5873.075712 +"(3, 2, 3, 3, 3, 0, 0, 2, 2, 0, 1, 0, 1, 4, 4, 4, 3, 3, 2, 2, 4, 4, 4, 4)",6528.435712 +"(3, 2, 3, 4, 3, 3, 3, 2, 2, 1, 1, 1, 4, 4, 4, 4, 4, 4, 2, 4, 4, 4, 4, 4)",4761.519616 +"(3, 2, 3, 3, 4, 0, 0, 2, 2, 3, 1, 1, 4, 4, 4, 4, 4, 3, 2, 3, 4, 4, 4, 4)",5434.5088 +"(3, 1, 3, 4, 4, 3, 3, 3, 2, 3, 1, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4)",4423.419392 +"(0, 2, 3, 3, 3, 0, 4, 3, 2, 1, 1, 1, 3, 4, 4, 4, 4, 4, 2, 3, 4, 2, 4, 4)",5692.655104 +"(0, 2, 3, 2, 4, 0, 0, 2, 2, 1, 1, 0, 1, 4, 4, 4, 3, 3, 2, 3, 4, 2, 3, 4)",6803.490304 +"(3, 2, 3, 3, 4, 3, 1, 3, 2, 3, 1, 1, 4, 4, 4, 4, 4, 4, 2, 3, 4, 4, 3, 4)",5142.087168 +"(3, 2, 3, 2, 4, 3, 1, 3, 2, 3, 1, 0, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4)",4968.678912 +"(3, 2, 3, 3, 3, 3, 1, 3, 2, 3, 1, 1, 4, 4, 4, 4, 4, 4, 2, 3, 4, 4, 4, 4)",5064.295936 +"(3, 2, 3, 3, 4, 0, 1, 3, 2, 0, 1, 1, 1, 4, 4, 4, 4, 4, 2, 2, 4, 4, 4, 4)",5900.600832 +"(3, 2, 3, 3, 3, 3, 0, 2, 2, 1, 1, 1, 4, 4, 4, 4, 3, 4, 2, 2, 4, 4, 3, 4)",5541.0048 +"(3, 1, 3, 3, 4, 3, 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"324 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"330 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"333 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"334 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"339 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"340 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"342 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"343 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"344 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"347 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"348 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"349 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "359 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"359 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"360 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "361 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"361 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "362 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"362 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "363 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"363 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"364 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"365 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"366 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "367 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"367 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"368 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"369 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"370 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"371 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"372 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "373 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"373 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"374 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"375 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"376 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "377 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"377 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"378 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"379 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"380 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"381 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"382 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "393 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"383 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"384 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"385 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "386 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"386 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "387 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"387 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "395 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"388 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"389 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"390 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "391 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"391 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "392 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"392 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"393 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "394 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"394 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"395 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"396 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "397 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"397 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "398 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"398 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "399 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"399 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "400 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"400 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"401 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "402 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"402 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "403 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"403 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "404 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"404 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"405 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"406 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"407 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "408 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"408 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"409 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"410 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"411 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"412 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"413 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "414 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"414 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"415 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"416 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"417 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "418 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"418 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"419 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"420 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"421 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"422 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"423 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "434 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"424 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"425 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"426 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "427 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"427 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "428 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"428 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "436 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"429 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"430 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"431 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "432 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"432 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "433 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"433 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"434 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "435 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"435 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"436 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"437 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "438 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"438 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "439 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"439 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "440 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"440 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "441 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"441 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"442 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "443 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"443 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "444 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"444 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "445 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"445 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"446 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"447 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"448 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "449 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"449 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"450 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"451 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"452 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"453 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072,) \n0 -> 2", style=solid]; +"454 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "455 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"455 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"456 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 3072) \n0 -> 1", style=solid]; +"457 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"458 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "459 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"459 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"460 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" -> "461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"461 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "491 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"462 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"463 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"464 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "475 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"465 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"466 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"467 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "468 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"468 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "469 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"469 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "477 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"470 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"471 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"472 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "473 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"473 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "474 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"474 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "483 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"475 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "476 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"476 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "478 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"477 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "478 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"478 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "479 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"479 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "480 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"480 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "481 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"481 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "482 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"482 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "483 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"483 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "484 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"484 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "485 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"485 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "486 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"486 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "489 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"487 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "489 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768, 768) \n0 -> 1", style=solid]; +"488 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_1" -> "489 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(768,) \n0 -> 2", style=solid]; +"489 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "490 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"490 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "491 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"491 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "492 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"492 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "495 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"492 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "501 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"493 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/NNCFLinear[dense]/ModuleDict[pre_ops]/UpdateWeightAndBias[0]/MovementSparsifier[op]/apply_binary_mask_0" -> "495 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(3072, 768) \n0 -> 1", style=solid]; +"494 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "14 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"14 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "20 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"15 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "16 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"16 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "17 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"17 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "26 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"18 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "19 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"19 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "21 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"20 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "21 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"21 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "22 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"22 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "23 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"23 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "24 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"24 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "25 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"25 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "26 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"26 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "27 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"27 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "28 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"28 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "29 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"29 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "30 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"30 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "31 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"31 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "32 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"32 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "33 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"35 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "36 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"36 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "37 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"37 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "38 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"38 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/__add___0" -> "39 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"39 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "40 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"39 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "41 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"39 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "44 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; 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BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"42 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "43 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"43 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"44 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"45 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "46 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"46 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"47 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"48 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"49 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"50 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"51 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "52 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"52 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "53 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"53 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"54 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"55 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "56 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"56 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"57 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"58 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"59 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"60 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"61 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"62 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"63 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"64 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"65 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"66 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"67 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/__add___0" -> "68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"68 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"69 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"70 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"71 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"72 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"73 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"74 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"75 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"76 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"77 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"78 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"79 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"80 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"81 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"82 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"83 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"84 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"85 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"86 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"87 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"88 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"89 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"90 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"91 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"92 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"93 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"94 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"95 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"96 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/__add___0" -> "97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"97 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"98 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"99 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"100 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"101 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"102 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"103 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"104 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"105 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"106 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"107 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"108 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"109 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"110 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"111 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"112 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"113 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"114 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"115 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"116 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"117 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"118 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"119 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"120 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"121 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"122 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"123 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"124 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"125 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/__add___0" -> "126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"126 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"127 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"128 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"129 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"130 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"131 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"132 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"133 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"134 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"135 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"136 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"137 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"138 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"139 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"140 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"141 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"142 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"143 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"144 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"145 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"146 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"147 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"148 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"149 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"150 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"151 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"152 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"153 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"154 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/__add___0" -> "155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"155 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"156 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"157 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"158 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"159 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"160 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"161 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"162 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"163 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"164 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"165 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"166 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"167 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"168 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"169 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"170 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"171 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"172 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"173 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"174 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"175 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"176 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"177 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"178 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"179 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"180 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"181 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"182 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"183 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/__add___0" -> "184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"184 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"185 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"186 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"187 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"188 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"189 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"190 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"191 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"192 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"193 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"194 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"195 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"196 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"197 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"198 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"199 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"200 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"201 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"202 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"203 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"204 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"205 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"206 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"207 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"208 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"209 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"210 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"211 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"212 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/__add___0" -> "213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"213 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"214 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"215 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"216 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"217 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"218 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"219 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"220 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"221 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"222 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"223 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"224 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"225 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"226 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"227 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"228 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"229 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"230 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"231 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"232 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"233 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"234 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"235 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"236 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"237 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"238 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"239 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"240 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"241 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/__add___0" -> "242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"242 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"243 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"244 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"245 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"246 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"247 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"248 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"249 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"250 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"251 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"252 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"253 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"254 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"255 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"256 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"257 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"258 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"259 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"260 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"261 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"262 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"263 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"264 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"265 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"266 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"267 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"268 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"269 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"270 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/__add___0" -> "271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"271 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"272 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"273 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"274 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"275 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"276 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"277 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"278 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"279 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"280 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"281 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"282 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"283 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"284 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"285 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"286 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"287 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"288 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"289 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"290 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"291 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"292 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"293 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"294 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"295 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"296 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"297 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"298 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"299 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/__add___0" -> "300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"300 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"301 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"302 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"303 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"304 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"305 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"306 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"307 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"308 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"309 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"310 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"311 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"312 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"313 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"314 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/softmax_0" -> "315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"315 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/Dropout[dropout]/dropout_0" -> "316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"316 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"317 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"318 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"319 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/view_3" -> "320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"320 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0" -> "321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"321 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"322 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "324 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"323 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"324 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"325 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"326 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"327 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"328 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/__add___0" -> "329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "330 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "334 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"329 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"330 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0" -> "337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"331 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0" -> "332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"332 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_0" -> "333 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"333 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_0" -> "339 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"334 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0" -> "335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_1" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"335 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_1" -> "336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_1" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"336 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_1" -> "345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" [label="(1, 12, 128, 64) \n0 -> 1", style=solid]; +"337 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/view_2" -> "338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_2" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"338 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_2" -> "340 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"339 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/transpose_0" -> "340 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" [label="(1, 12, 64, 128) \n0 -> 1", style=solid]; +"340 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_0" -> "341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"341 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__truediv___0" -> "342 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__add___0" [label="(1, 12, 128, 128) \n0 -> 0", style=solid]; +"342 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/__add___0" -> "343 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style=solid]; +"345 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/matmul_1" -> "346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_3" [label="(1, 12, 128, 64) \n0 -> 0", style=solid]; +"346 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/permute_3" -> "347 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" [label="(1, 128, 12, 64) \n0 -> 0", style=solid]; +"347 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/contiguous_0" -> "348 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style=solid]; +"350 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/Dropout[dropout]/dropout_0" -> "351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"351 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/__add___0" -> "352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"352 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 1", style=solid]; +"353 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0" -> "354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"354 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/GELUActivation[intermediate_act_fn]/gelu_0" -> "355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/NNCFLinear[dense]/linear_0" [label="(1, 128, 3072) \n0 -> 0", style=solid]; +"355 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/NNCFLinear[dense]/linear_0" -> "356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/Dropout[dropout]/dropout_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"356 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/Dropout[dropout]/dropout_0" -> "357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/__add___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/__add___0" -> "358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0" -> "359 BertForSequenceClassification/BertModel[bert]/BertPooler[pooler]/__getitem___0" [label="(1, 128, 768) \n0 -> 0", style=solid]; +"359 BertForSequenceClassification/BertModel[bert]/BertPooler[pooler]/__getitem___0" -> "360 BertForSequenceClassification/BertModel[bert]/BertPooler[pooler]/NNCFLinear[dense]/linear_0" [label="(1, 768) \n0 -> 0", style=solid]; +"360 BertForSequenceClassification/BertModel[bert]/BertPooler[pooler]/NNCFLinear[dense]/linear_0" -> "361 BertForSequenceClassification/BertModel[bert]/BertPooler[pooler]/Tanh[activation]/tanh_0" [label="(1, 768) \n0 -> 0", style=solid]; +"361 BertForSequenceClassification/BertModel[bert]/BertPooler[pooler]/Tanh[activation]/tanh_0" -> "362 BertForSequenceClassification/Dropout[dropout]/dropout_0" [label="(1, 768) \n0 -> 0", style=solid]; +"362 BertForSequenceClassification/Dropout[dropout]/dropout_0" -> "363 BertForSequenceClassification/NNCFLinear[classifier]/linear_0" [label="(1, 768) \n0 -> 0", style=solid]; +"363 BertForSequenceClassification/NNCFLinear[classifier]/linear_0" -> "364 /nncf_model_output_0" [label="(1, 2) \n0 -> 0", style=solid]; +} diff --git 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0000000000000000000000000000000000000000..0aad07030d41f83f5d1194ceb2651c4da443c979 --- /dev/null +++ b/eftnas-s1-bert-base-sst2/search_progression.csv @@ -0,0 +1,1000 @@ +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 768, 5: 576, 6: 768, 7: 512, 8: 256, 9: 192, 10: 768, 11: 768, 12: 1585, 13: 3036, 14: 2362, 15: 3042, 16: 3043, 17: 3038, 18: 1621, 19: 2114, 20: 1188, 21: 2924, 22: 828, 23: 1966})])",MACs,8312.718848,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 768, 2: 384, 3: 256, 4: 256, 5: 384, 6: 192, 7: 512, 8: 256, 9: 768, 10: 128, 11: 64, 12: 3072, 13: 3072, 14: 3046, 15: 3042, 16: 1679, 17: 2215, 18: 2786, 19: 1406, 20: 3072, 21: 930, 22: 2158, 23: 1966})])",MACs,7419.528704,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 576, 1: 384, 2: 320, 3: 384, 4: 768, 5: 576, 6: 768, 7: 512, 8: 448, 9: 768, 10: 768, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 2791, 16: 2296, 17: 3072, 18: 1621, 19: 2114, 20: 2506, 21: 930, 22: 2158, 23: 3072})])",MACs,8137.278976,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 384, 4: 768, 5: 192, 6: 128, 7: 768, 8: 256, 9: 320, 10: 128, 11: 128, 12: 2727, 13: 3036, 14: 2362, 15: 2791, 16: 3043, 17: 1580, 18: 3072, 19: 3072, 20: 2994, 21: 3072, 22: 1501, 23: 1966})])",MACs,8264.418816,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 768, 4: 576, 5: 576, 6: 384, 7: 320, 8: 256, 9: 768, 10: 768, 11: 768, 12: 3040, 13: 1570, 14: 3046, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 3072, 22: 1501, 23: 654})])",MACs,7793.47712,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 512, 4: 384, 5: 192, 6: 192, 7: 768, 8: 768, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 2795, 15: 2314, 16: 2296, 17: 3038, 18: 3032, 19: 2114, 20: 1188, 21: 3072, 22: 828, 23: 2812})])",MACs,7420.052992,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 384, 2: 320, 3: 768, 4: 576, 5: 768, 6: 128, 7: 320, 8: 448, 9: 256, 10: 768, 11: 128, 12: 1585, 13: 2712, 14: 3046, 15: 1717, 16: 2764, 17: 1580, 18: 2786, 19: 2114, 20: 2994, 21: 2924, 22: 2158, 23: 1301})])",MACs,7651.198464,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 384, 4: 384, 5: 768, 6: 768, 7: 768, 8: 448, 9: 256, 10: 128, 11: 768, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 3072, 17: 3072, 18: 1621, 19: 2114, 20: 1188, 21: 2924, 22: 2868, 23: 654})])",MACs,7874.348544,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 576, 1: 384, 2: 256, 3: 384, 4: 768, 5: 192, 6: 384, 7: 768, 8: 448, 9: 768, 10: 128, 11: 128, 12: 3072, 13: 3072, 14: 3046, 15: 1717, 16: 3043, 17: 2768, 18: 1621, 19: 3034, 20: 3072, 21: 2924, 22: 3072, 23: 1301})])",MACs,8449.623552,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 768, 5: 576, 6: 192, 7: 768, 8: 256, 9: 768, 10: 768, 11: 64, 12: 3072, 13: 2190, 14: 2362, 15: 2791, 16: 3072, 17: 2215, 18: 3032, 19: 2114, 20: 3072, 21: 930, 22: 828, 23: 3072})])",MACs,8106.7392,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 576, 1: 256, 2: 768, 3: 384, 4: 768, 5: 384, 6: 192, 7: 768, 8: 448, 9: 256, 10: 768, 11: 768, 12: 2727, 13: 3036, 14: 3046, 15: 3042, 16: 3043, 17: 1580, 18: 3032, 19: 2694, 20: 2506, 21: 2924, 22: 2868, 23: 2812})])",MACs,9248.638464,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 512, 8: 448, 9: 768, 10: 768, 11: 768, 12: 3072, 13: 3036, 14: 2362, 15: 1717, 16: 3043, 17: 3038, 18: 1621, 19: 2694, 20: 1896, 21: 930, 22: 1501, 23: 654})])",MACs,7916.553728,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 768, 5: 384, 6: 192, 7: 320, 8: 448, 9: 256, 10: 128, 11: 768, 12: 2227, 13: 3072, 14: 2795, 15: 3072, 16: 1679, 17: 2768, 18: 1621, 19: 2694, 20: 2994, 21: 3072, 22: 3072, 23: 1966})])",MACs,8419.083776,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 512, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 3042, 16: 2764, 17: 2215, 18: 2786, 19: 1406, 20: 3072, 21: 930, 22: 1501, 23: 2812})])",MACs,6713.312768,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 384, 4: 576, 5: 192, 6: 192, 7: 768, 8: 768, 9: 256, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 3046, 15: 3072, 16: 2764, 17: 1580, 18: 1621, 19: 2114, 20: 3072, 21: 1585, 22: 2158, 23: 654})])",MACs,7265.322496,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 256, 4: 768, 5: 384, 6: 192, 7: 320, 8: 448, 9: 192, 10: 768, 11: 768, 12: 3040, 13: 2190, 14: 1775, 15: 2791, 16: 2296, 17: 3038, 18: 3032, 19: 3072, 20: 3072, 21: 2236, 22: 2868, 23: 2812})])",MACs,8843.888128,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 768, 9: 192, 10: 768, 11: 768, 12: 1585, 13: 1570, 14: 3046, 15: 3072, 16: 3072, 17: 3072, 18: 2786, 19: 1406, 20: 3072, 21: 3072, 22: 3072, 23: 3072})])",MACs,8889.042432,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 448, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 2190, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 1621, 19: 3034, 20: 2506, 21: 1585, 22: 3072, 23: 1966})])",MACs,7789.54496,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 704, 7: 512, 8: 448, 9: 320, 10: 768, 11: 768, 12: 2227, 13: 1570, 14: 3046, 15: 2791, 16: 2764, 17: 3038, 18: 3072, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,8228.505088,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 576, 1: 384, 2: 256, 3: 256, 4: 768, 5: 576, 6: 192, 7: 512, 8: 256, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 2190, 14: 2795, 15: 3072, 16: 2296, 17: 2768, 18: 3032, 19: 3034, 20: 3072, 21: 1585, 22: 828, 23: 1301})])",MACs,7671.449088,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 192, 4: 256, 5: 192, 6: 384, 7: 512, 8: 768, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 2795, 15: 2791, 16: 2764, 17: 1580, 18: 3072, 19: 1406, 20: 2506, 21: 2236, 22: 2868, 23: 1301})])",MACs,7163.938304,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 512, 4: 384, 5: 384, 6: 384, 7: 384, 8: 256, 9: 768, 10: 768, 11: 64, 12: 2727, 13: 2190, 14: 2362, 15: 2314, 16: 2764, 17: 2215, 18: 2786, 19: 3034, 20: 1896, 21: 2236, 22: 3072, 23: 654})])",MACs,7572.227584,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 384, 4: 384, 5: 768, 6: 128, 7: 512, 8: 768, 9: 768, 10: 768, 11: 128, 12: 3040, 13: 2190, 14: 3046, 15: 3072, 16: 3043, 17: 3072, 18: 3032, 19: 1406, 20: 1188, 21: 2924, 22: 3072, 23: 2812})])",MACs,8807.253504,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 384, 1: 768, 2: 384, 3: 256, 4: 256, 5: 768, 6: 192, 7: 512, 8: 256, 9: 192, 10: 768, 11: 768, 12: 2727, 13: 3036, 14: 2795, 15: 3072, 16: 2296, 17: 1580, 18: 2786, 19: 3034, 20: 1896, 21: 1585, 22: 2158, 23: 1966})])",MACs,8033.273344,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 384, 2: 384, 3: 512, 4: 704, 5: 576, 6: 704, 7: 768, 8: 768, 9: 192, 10: 128, 11: 128, 12: 2727, 13: 2190, 14: 2795, 15: 3042, 16: 3043, 17: 1580, 18: 2268, 19: 2694, 20: 1188, 21: 1585, 22: 2868, 23: 1966})])",MACs,8057.718272,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 576, 1: 768, 2: 384, 3: 384, 4: 384, 5: 768, 6: 384, 7: 512, 8: 256, 9: 320, 10: 768, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 3072, 16: 2296, 17: 3072, 18: 3032, 19: 2114, 20: 1188, 21: 3072, 22: 2868, 23: 654})])",MACs,7856.195072,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 576, 1: 384, 2: 768, 3: 512, 4: 768, 5: 192, 6: 192, 7: 384, 8: 768, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 2795, 15: 3072, 16: 2764, 17: 2768, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 3072, 23: 1966})])",MACs,7894.40256,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 576, 1: 256, 2: 384, 3: 192, 4: 768, 5: 384, 6: 704, 7: 512, 8: 768, 9: 768, 10: 768, 11: 128, 12: 2227, 13: 2190, 14: 2795, 15: 2791, 16: 2764, 17: 2215, 18: 3072, 19: 2694, 20: 2506, 21: 1585, 22: 2868, 23: 1966})])",MACs,8479.049216,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 576, 1: 256, 2: 384, 3: 384, 4: 768, 5: 192, 6: 128, 7: 512, 8: 768, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 2362, 15: 2314, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 2994, 21: 1585, 22: 2868, 23: 2812})])",MACs,7738.492416,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 256, 4: 704, 5: 192, 6: 384, 7: 768, 8: 768, 9: 768, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 3072, 15: 1717, 16: 3043, 17: 2768, 18: 1621, 19: 2114, 20: 1896, 21: 3072, 22: 3072, 23: 2812})])",MACs,8703.510016,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 576, 1: 384, 2: 256, 3: 768, 4: 768, 5: 384, 6: 384, 7: 768, 8: 448, 9: 320, 10: 128, 11: 64, 12: 2727, 13: 2190, 14: 1775, 15: 2314, 16: 3072, 17: 3038, 18: 1621, 19: 2694, 20: 1188, 21: 3072, 22: 3072, 23: 2812})])",MACs,8050.836992,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 256, 5: 768, 6: 768, 7: 512, 8: 256, 9: 256, 10: 128, 11: 64, 12: 3040, 13: 3036, 14: 2795, 15: 2314, 16: 2296, 17: 2215, 18: 3072, 19: 1406, 20: 1188, 21: 2924, 22: 1501, 23: 654})])",MACs,7407.404544,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 384, 4: 704, 5: 384, 6: 704, 7: 512, 8: 768, 9: 256, 10: 768, 11: 128, 12: 3040, 13: 2712, 14: 3072, 15: 3072, 16: 3072, 17: 2768, 18: 2786, 19: 3034, 20: 3072, 21: 930, 22: 1501, 23: 654})])",MACs,8214.283776,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 384, 2: 384, 3: 256, 4: 384, 5: 192, 6: 768, 7: 384, 8: 768, 9: 768, 10: 768, 11: 128, 12: 3072, 13: 2190, 14: 3072, 15: 1717, 16: 1679, 17: 1580, 18: 3032, 19: 2114, 20: 3072, 21: 930, 22: 1501, 23: 654})])",MACs,7375.160832,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 768, 4: 704, 5: 384, 6: 128, 7: 320, 8: 448, 9: 256, 10: 128, 11: 128, 12: 3072, 13: 2712, 14: 2795, 15: 1717, 16: 2764, 17: 2768, 18: 3072, 19: 3072, 20: 2506, 21: 2924, 22: 1501, 23: 1966})])",MACs,7841.777152,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 576, 1: 256, 2: 768, 3: 768, 4: 768, 5: 384, 6: 768, 7: 320, 8: 256, 9: 320, 10: 768, 11: 64, 12: 2727, 13: 2190, 14: 2362, 15: 2314, 16: 3043, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 3072, 22: 2868, 23: 1301})])",MACs,8126.334464,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 768, 4: 768, 5: 576, 6: 192, 7: 512, 8: 448, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 3072, 17: 1580, 18: 2268, 19: 2114, 20: 1896, 21: 3072, 22: 2158, 23: 1966})])",MACs,7917.602304,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 256, 4: 256, 5: 576, 6: 384, 7: 320, 8: 768, 9: 192, 10: 768, 11: 768, 12: 2227, 13: 2190, 14: 2362, 15: 1717, 16: 3043, 17: 3072, 18: 1621, 19: 3034, 20: 1896, 21: 3072, 22: 3072, 23: 2812})])",MACs,8348.435968,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 192, 6: 768, 7: 320, 8: 768, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 2712, 14: 2795, 15: 1717, 16: 2764, 17: 2768, 18: 3072, 19: 2114, 20: 3072, 21: 1585, 22: 3072, 23: 1301})])",MACs,7976.912384,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 384, 2: 320, 3: 256, 4: 384, 5: 192, 6: 768, 7: 320, 8: 768, 9: 320, 10: 768, 11: 128, 12: 2727, 13: 3072, 14: 1775, 15: 2314, 16: 3043, 17: 2768, 18: 2786, 19: 1406, 20: 3072, 21: 930, 22: 828, 23: 3072})])",MACs,7755.007488,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 576, 1: 256, 2: 384, 3: 768, 4: 768, 5: 576, 6: 192, 7: 512, 8: 768, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 3072, 17: 3038, 18: 2268, 19: 2694, 20: 1896, 21: 3072, 22: 2158, 23: 1966})])",MACs,8536.393216,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 512, 4: 576, 5: 192, 6: 192, 7: 768, 8: 768, 9: 256, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 3046, 15: 3072, 16: 2764, 17: 1580, 18: 2786, 19: 2114, 20: 3072, 21: 1585, 22: 2158, 23: 654})])",MACs,7548.896768,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 256, 4: 576, 5: 768, 6: 704, 7: 320, 8: 448, 9: 256, 10: 768, 11: 768, 12: 1585, 13: 2712, 14: 3046, 15: 2314, 16: 2764, 17: 1580, 18: 2786, 19: 2114, 20: 2506, 21: 1585, 22: 3072, 23: 1301})])",MACs,8243.38176,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 384, 5: 576, 6: 704, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 2727, 13: 3072, 14: 3046, 15: 2791, 16: 2764, 17: 3038, 18: 3072, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 3072})])",MACs,9324.72576,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 768, 4: 576, 5: 384, 6: 192, 7: 320, 8: 256, 9: 768, 10: 768, 11: 768, 12: 3040, 13: 2190, 14: 3046, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 3072, 22: 2868, 23: 1301})])",MACs,8147.764736,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 192, 4: 384, 5: 192, 6: 192, 7: 512, 8: 768, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 2795, 15: 2314, 16: 2764, 17: 3038, 18: 3032, 19: 1406, 20: 1188, 21: 2236, 22: 828, 23: 2812})])",MACs,7017.661952,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 768, 5: 384, 6: 704, 7: 512, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2227, 13: 2190, 14: 2795, 15: 2791, 16: 2296, 17: 3072, 18: 3032, 19: 2694, 20: 2506, 21: 2924, 22: 2868, 23: 1966})])",MACs,8974.501376,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 576, 1: 384, 2: 256, 3: 384, 4: 384, 5: 192, 6: 768, 7: 512, 8: 768, 9: 192, 10: 768, 11: 768, 12: 2227, 13: 2190, 14: 2795, 15: 3072, 16: 2764, 17: 2768, 18: 3072, 19: 2114, 20: 3072, 21: 1585, 22: 828, 23: 1301})])",MACs,7999.391232,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 256, 4: 768, 5: 384, 6: 192, 7: 384, 8: 448, 9: 192, 10: 768, 11: 768, 12: 3040, 13: 2190, 14: 2362, 15: 2791, 16: 2296, 17: 3038, 18: 3032, 19: 3072, 20: 3072, 21: 2236, 22: 2868, 23: 2812})])",MACs,8986.56,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 576, 1: 384, 2: 256, 3: 384, 4: 768, 5: 768, 6: 192, 7: 512, 8: 256, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 2190, 14: 2795, 15: 3072, 16: 2296, 17: 2768, 18: 3032, 19: 2114, 20: 3072, 21: 1585, 22: 828, 23: 1301})])",MACs,7626.884608,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 512, 4: 256, 5: 768, 6: 384, 7: 384, 8: 256, 9: 768, 10: 768, 11: 64, 12: 2727, 13: 2190, 14: 2795, 15: 2314, 16: 2764, 17: 2215, 18: 2786, 19: 3034, 20: 1896, 21: 2236, 22: 3072, 23: 654})])",MACs,7766.410752,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 768, 4: 768, 5: 768, 6: 192, 7: 320, 8: 448, 9: 256, 10: 768, 11: 768, 12: 3040, 13: 2712, 14: 1775, 15: 2791, 16: 2764, 17: 3038, 18: 3032, 19: 3072, 20: 3072, 21: 2236, 22: 2868, 23: 2812})])",MACs,9502.00064,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 384, 1: 384, 2: 384, 3: 192, 4: 256, 5: 192, 6: 384, 7: 512, 8: 768, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 2795, 15: 2791, 16: 2764, 17: 1580, 18: 3072, 19: 1406, 20: 2506, 21: 2236, 22: 2868, 23: 2812})])",MACs,7488.275968,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 512, 4: 768, 5: 384, 6: 192, 7: 512, 8: 768, 9: 768, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 2795, 15: 3072, 16: 2764, 17: 2768, 18: 2786, 19: 2694, 20: 3072, 21: 930, 22: 3072, 23: 1966})])",MACs,8810.071552,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 768, 4: 576, 5: 192, 6: 384, 7: 320, 8: 256, 9: 768, 10: 768, 11: 64, 12: 3040, 13: 1570, 14: 3046, 15: 3042, 16: 2296, 17: 2215, 18: 2786, 19: 1406, 20: 3072, 21: 930, 22: 1501, 23: 2812})])",MACs,7767.131648,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 384, 4: 768, 5: 576, 6: 704, 7: 512, 8: 448, 9: 320, 10: 768, 11: 768, 12: 2227, 13: 3072, 14: 3046, 15: 2791, 16: 2764, 17: 3038, 18: 3072, 19: 2694, 20: 2994, 21: 2236, 22: 1501, 23: 1301})])",MACs,9096.98816,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 384, 2: 384, 3: 256, 4: 384, 5: 192, 6: 768, 7: 384, 8: 768, 9: 768, 10: 768, 11: 128, 12: 3072, 13: 3072, 14: 3072, 15: 1717, 16: 1679, 17: 1580, 18: 3032, 19: 2114, 20: 3072, 21: 930, 22: 1501, 23: 654})])",MACs,7548.569088,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 768, 5: 576, 6: 704, 7: 768, 8: 768, 9: 768, 10: 768, 11: 64, 12: 2227, 13: 2190, 14: 2795, 15: 2791, 16: 2764, 17: 2215, 18: 3072, 19: 2694, 20: 2506, 21: 930, 22: 2868, 23: 1966})])",MACs,8350.270976,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 384, 4: 768, 5: 192, 6: 128, 7: 512, 8: 448, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 2362, 15: 2314, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 2994, 21: 1585, 22: 2868, 23: 2812})])",MACs,7119.701504,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 3042, 16: 2764, 17: 2215, 18: 1621, 19: 1406, 20: 3072, 21: 930, 22: 1501, 23: 2812})])",MACs,6429.738496,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 768, 4: 384, 5: 576, 6: 128, 7: 384, 8: 448, 9: 768, 10: 128, 11: 128, 12: 2227, 13: 2190, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 3034, 20: 2994, 21: 2924, 22: 2158, 23: 1966})])",MACs,7197.361664,top1_acc,-91.5137614678899 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 448, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 3043, 17: 2768, 18: 2786, 19: 1406, 20: 3072, 21: 930, 22: 828, 23: 1301})])",MACs,6658.786816,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 576, 1: 256, 2: 768, 3: 768, 4: 768, 5: 576, 6: 768, 7: 320, 8: 256, 9: 320, 10: 768, 11: 64, 12: 2727, 13: 1570, 14: 2362, 15: 2314, 16: 3043, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 3072, 22: 1501, 23: 654})])",MACs,7690.25792,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 384, 2: 320, 3: 512, 4: 256, 5: 192, 6: 384, 7: 768, 8: 768, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 2795, 15: 2791, 16: 2296, 17: 1580, 18: 3072, 19: 2114, 20: 2506, 21: 3072, 22: 2868, 23: 1301})])",MACs,7566.329344,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 576, 1: 384, 2: 768, 3: 384, 4: 384, 5: 768, 6: 768, 7: 768, 8: 448, 9: 256, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 3072, 17: 2215, 18: 2268, 19: 2114, 20: 1188, 21: 1585, 22: 2868, 23: 654})])",MACs,7406.224896,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 768, 5: 576, 6: 192, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 2712, 14: 2795, 15: 1717, 16: 2296, 17: 2768, 18: 3032, 19: 3034, 20: 3072, 21: 1585, 22: 3072, 23: 1301})])",MACs,7648.97024,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 512, 4: 384, 5: 384, 6: 384, 7: 320, 8: 256, 9: 768, 10: 768, 11: 64, 12: 2727, 13: 2190, 14: 1775, 15: 2314, 16: 2764, 17: 2215, 18: 2786, 19: 3034, 20: 1896, 21: 2236, 22: 3072, 23: 654})])",MACs,7429.555712,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 576, 1: 768, 2: 384, 3: 256, 4: 384, 5: 576, 6: 384, 7: 512, 8: 256, 9: 320, 10: 768, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 3072, 16: 2296, 17: 3072, 18: 3032, 19: 3034, 20: 1188, 21: 3072, 22: 2868, 23: 654})])",MACs,7900.759552,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 384, 5: 384, 6: 768, 7: 512, 8: 256, 9: 256, 10: 128, 11: 64, 12: 3040, 13: 3036, 14: 2362, 15: 2314, 16: 2296, 17: 2215, 18: 3072, 19: 1406, 20: 1188, 21: 2924, 22: 1501, 23: 654})])",MACs,7213.221376,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 256, 4: 576, 5: 384, 6: 128, 7: 320, 8: 448, 9: 192, 10: 768, 11: 128, 12: 1585, 13: 2190, 14: 3046, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 2994, 21: 2924, 22: 2158, 23: 1301})])",MACs,6993.085952,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 384, 4: 768, 5: 192, 6: 128, 7: 512, 8: 768, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 2362, 15: 2314, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 2994, 21: 1585, 22: 2868, 23: 1301})])",MACs,7414.154752,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 384, 2: 384, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 3072, 13: 3072, 14: 3046, 15: 3042, 16: 1679, 17: 2215, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 2158, 23: 1966})])",MACs,6503.859712,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 512, 4: 576, 5: 576, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2764, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 3072, 22: 1501, 23: 654})])",MACs,6739.65824,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 256, 5: 384, 6: 192, 7: 320, 8: 448, 9: 256, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 2795, 15: 3072, 16: 1679, 17: 2768, 18: 1621, 19: 2694, 20: 1188, 21: 3072, 22: 3072, 23: 1966})])",MACs,7550.600704,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 384, 2: 320, 3: 256, 4: 384, 5: 192, 6: 768, 7: 320, 8: 768, 9: 320, 10: 768, 11: 128, 12: 2727, 13: 2190, 14: 1775, 15: 2314, 16: 3043, 17: 2768, 18: 2786, 19: 1406, 20: 3072, 21: 930, 22: 828, 23: 3072})])",MACs,7581.599232,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 256, 4: 768, 5: 384, 6: 192, 7: 512, 8: 256, 9: 768, 10: 768, 11: 128, 12: 3072, 13: 2190, 14: 2362, 15: 2791, 16: 3072, 17: 2215, 18: 3032, 19: 2114, 20: 3072, 21: 1585, 22: 828, 23: 3072})])",MACs,8317.306368,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 384, 5: 192, 6: 768, 7: 320, 8: 768, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 2712, 14: 2795, 15: 3072, 16: 2764, 17: 2215, 18: 3072, 19: 2114, 20: 3072, 21: 1585, 22: 3072, 23: 1301})])",MACs,7916.488192,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 192, 4: 256, 5: 192, 6: 384, 7: 512, 8: 768, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 3072, 15: 1717, 16: 1679, 17: 1580, 18: 3072, 19: 2114, 20: 2506, 21: 2236, 22: 2868, 23: 1301})])",MACs,6933.120512,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 384, 4: 384, 5: 768, 6: 128, 7: 512, 8: 768, 9: 768, 10: 768, 11: 128, 12: 3040, 13: 2190, 14: 3046, 15: 1717, 16: 3043, 17: 3072, 18: 3032, 19: 1406, 20: 1188, 21: 2924, 22: 3072, 23: 2812})])",MACs,8758.953472,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 384, 2: 384, 3: 256, 4: 384, 5: 192, 6: 768, 7: 384, 8: 768, 9: 768, 10: 768, 11: 128, 12: 3072, 13: 2190, 14: 2795, 15: 2791, 16: 2764, 17: 1580, 18: 3032, 19: 1406, 20: 3072, 21: 930, 22: 1501, 23: 654})])",MACs,7605.978624,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 512, 4: 384, 5: 384, 6: 384, 7: 384, 8: 256, 9: 768, 10: 768, 11: 64, 12: 2727, 13: 2190, 14: 2362, 15: 2314, 16: 2764, 17: 2215, 18: 2786, 19: 3034, 20: 2994, 21: 2236, 22: 3072, 23: 1301})])",MACs,7915.308544,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 384, 4: 384, 5: 576, 6: 704, 7: 512, 8: 768, 9: 320, 10: 768, 11: 768, 12: 2727, 13: 1570, 14: 3046, 15: 2791, 16: 2764, 17: 3038, 18: 3072, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 3072})])",MACs,8865.842688,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 192, 4: 256, 5: 192, 6: 384, 7: 512, 8: 768, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 2795, 15: 1717, 16: 2764, 17: 1580, 18: 3072, 19: 2114, 20: 2506, 21: 2236, 22: 2868, 23: 1301})])",MACs,7091.979776,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 384, 4: 768, 5: 576, 6: 704, 7: 512, 8: 448, 9: 192, 10: 768, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 2791, 16: 2764, 17: 3038, 18: 3072, 19: 2694, 20: 2994, 21: 2236, 22: 1501, 23: 2812})])",MACs,8794.342912,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 768, 5: 384, 6: 768, 7: 512, 8: 256, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 3036, 14: 2362, 15: 2314, 16: 2296, 17: 2215, 18: 1621, 19: 2114, 20: 1188, 21: 2924, 22: 1501, 23: 654})])",MACs,6944.654848,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 384, 5: 576, 6: 192, 7: 512, 8: 768, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 2795, 15: 2314, 16: 2764, 17: 3038, 18: 3032, 19: 1406, 20: 1896, 21: 1585, 22: 3072, 23: 2812})])",MACs,7732.594176,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 512, 4: 768, 5: 192, 6: 768, 7: 320, 8: 448, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 3072, 16: 3043, 17: 2768, 18: 2786, 19: 2694, 20: 3072, 21: 930, 22: 3072, 23: 1966})])",MACs,8255.440384,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 512, 4: 384, 5: 384, 6: 384, 7: 768, 8: 768, 9: 768, 10: 768, 11: 64, 12: 2727, 13: 2190, 14: 1775, 15: 2314, 16: 2764, 17: 2215, 18: 2786, 19: 3034, 20: 1896, 21: 2236, 22: 3072, 23: 2812})])",MACs,8262.780416,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 512, 4: 576, 5: 576, 6: 768, 7: 512, 8: 256, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 3036, 14: 2795, 15: 2314, 16: 2764, 17: 3038, 18: 3072, 19: 2694, 20: 1188, 21: 3072, 22: 1501, 23: 654})])",MACs,7947.290112,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 576, 1: 384, 2: 768, 3: 384, 4: 576, 5: 768, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 3042, 16: 3072, 17: 2215, 18: 1621, 19: 2114, 20: 3072, 21: 1585, 22: 1501, 23: 2812})])",MACs,7194.47808,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 512, 4: 256, 5: 192, 6: 384, 7: 512, 8: 256, 9: 768, 10: 768, 11: 64, 12: 2727, 13: 3072, 14: 2362, 15: 2314, 16: 2764, 17: 2215, 18: 3072, 19: 3034, 20: 1896, 21: 2236, 22: 3072, 23: 654})])",MACs,7720.0768,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 768, 5: 576, 6: 192, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 2712, 14: 2795, 15: 2791, 16: 2296, 17: 3038, 18: 3032, 19: 3072, 20: 3072, 21: 1585, 22: 3072, 23: 1301})])",MACs,8193.312256,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 256, 5: 768, 6: 704, 7: 512, 8: 256, 9: 256, 10: 128, 11: 64, 12: 3040, 13: 3072, 14: 2795, 15: 2791, 16: 2296, 17: 3038, 18: 3072, 19: 1406, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,7725.64736,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 576, 1: 384, 2: 320, 3: 256, 4: 768, 5: 384, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 2791, 16: 3043, 17: 2768, 18: 3072, 19: 1406, 20: 3072, 21: 930, 22: 2868, 23: 1966})])",MACs,8131.249664,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 384, 4: 768, 5: 576, 6: 128, 7: 512, 8: 768, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 2362, 15: 2314, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 2994, 21: 1585, 22: 2868, 23: 1301})])",MACs,7703.954944,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 256, 4: 384, 5: 576, 6: 704, 7: 512, 8: 448, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 3072, 14: 1775, 15: 3042, 16: 2296, 17: 1580, 18: 2786, 19: 3034, 20: 3072, 21: 1585, 22: 3072, 23: 1966})])",MACs,8555.464192,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 768, 4: 768, 5: 576, 6: 768, 7: 512, 8: 256, 9: 320, 10: 768, 11: 768, 12: 1585, 13: 3072, 14: 2362, 15: 3042, 16: 3043, 17: 3038, 18: 1621, 19: 2114, 20: 1188, 21: 2924, 22: 2868, 23: 1966})])",MACs,8829.92896,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 256, 4: 576, 5: 384, 6: 128, 7: 320, 8: 448, 9: 192, 10: 768, 11: 128, 12: 1585, 13: 2190, 14: 3046, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1896, 21: 2924, 22: 2158, 23: 654})])",MACs,6650.004992,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 704, 7: 512, 8: 448, 9: 320, 10: 768, 11: 768, 12: 2227, 13: 3072, 14: 3046, 15: 2791, 16: 2764, 17: 3038, 18: 3072, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,8687.38816,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 192, 4: 256, 5: 192, 6: 384, 7: 512, 8: 768, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 3072, 15: 2791, 16: 1679, 17: 1580, 18: 3072, 19: 1406, 20: 2506, 21: 2236, 22: 2868, 23: 1301})])",MACs,7005.07904,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 3072, 14: 3046, 15: 3042, 16: 2764, 17: 2215, 18: 1621, 19: 1406, 20: 3072, 21: 930, 22: 1501, 23: 1301})])",MACs,6732.383744,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 384, 5: 576, 6: 768, 7: 512, 8: 256, 9: 192, 10: 768, 11: 768, 12: 3040, 13: 3036, 14: 2362, 15: 3042, 16: 3043, 17: 3038, 18: 3072, 19: 1406, 20: 1188, 21: 2924, 22: 828, 23: 1966})])",MACs,8581.285376,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 256, 4: 768, 5: 192, 6: 192, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 2712, 14: 2795, 15: 1717, 16: 2296, 17: 2768, 18: 3032, 19: 3034, 20: 2994, 21: 2236, 22: 828, 23: 1301})])",MACs,7057.901056,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 576, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 768, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 2795, 15: 2314, 16: 2764, 17: 2768, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,6297.748992,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 512, 4: 384, 5: 192, 6: 192, 7: 320, 8: 256, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 2795, 15: 2314, 16: 2296, 17: 3038, 18: 3032, 19: 2114, 20: 1188, 21: 3072, 22: 828, 23: 654})])",MACs,6586.828288,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 256, 5: 768, 6: 128, 7: 320, 8: 256, 9: 256, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 2786, 19: 1406, 20: 1188, 21: 2924, 22: 1501, 23: 654})])",MACs,6199.772672,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 192, 6: 768, 7: 768, 8: 448, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 2764, 17: 2215, 18: 2268, 19: 1406, 20: 1188, 21: 930, 22: 2868, 23: 654})])",MACs,6641.485312,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 192, 4: 384, 5: 384, 6: 384, 7: 384, 8: 768, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 2190, 14: 3072, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 2506, 21: 2236, 22: 2868, 23: 1301})])",MACs,6785.271296,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 256, 4: 768, 5: 384, 6: 192, 7: 384, 8: 448, 9: 192, 10: 768, 11: 128, 12: 3040, 13: 2190, 14: 2362, 15: 1717, 16: 2296, 17: 2768, 18: 3032, 19: 3034, 20: 3072, 21: 2236, 22: 2868, 23: 2812})])",MACs,8442.217984,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 384, 1: 384, 2: 768, 3: 256, 4: 768, 5: 576, 6: 768, 7: 512, 8: 448, 9: 320, 10: 768, 11: 768, 12: 2227, 13: 3036, 14: 3046, 15: 2314, 16: 2764, 17: 2215, 18: 3072, 19: 2694, 20: 2994, 21: 2924, 22: 1501, 23: 1301})])",MACs,8778.745344,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 192, 4: 256, 5: 192, 6: 704, 7: 320, 8: 448, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 2190, 14: 2795, 15: 2314, 16: 2764, 17: 2215, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 828, 23: 1301})])",MACs,7006.586368,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 512, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2764, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 3072, 22: 1501, 23: 654})])",MACs,6449.858048,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 256, 5: 384, 6: 192, 7: 384, 8: 256, 9: 768, 10: 128, 11: 64, 12: 3072, 13: 2190, 14: 3046, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 2506, 21: 930, 22: 2158, 23: 1966})])",MACs,6653.609472,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 192, 6: 384, 7: 512, 8: 768, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 3036, 14: 2795, 15: 2791, 16: 2764, 17: 1580, 18: 3072, 19: 1406, 20: 2506, 21: 2236, 22: 828, 23: 1301})])",MACs,6646.728192,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 384, 4: 768, 5: 192, 6: 128, 7: 512, 8: 256, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 2362, 15: 3042, 16: 2764, 17: 3038, 18: 2786, 19: 1406, 20: 2994, 21: 1585, 22: 2868, 23: 1301})])",MACs,7425.49248,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 3036, 14: 1775, 15: 3042, 16: 3043, 17: 2768, 18: 2786, 19: 1406, 20: 3072, 21: 2924, 22: 828, 23: 1301})])",MACs,7400.392192,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 512, 4: 384, 5: 768, 6: 768, 7: 384, 8: 256, 9: 768, 10: 768, 11: 64, 12: 2727, 13: 2190, 14: 2795, 15: 2314, 16: 2764, 17: 2215, 18: 2786, 19: 3034, 20: 1896, 21: 2924, 22: 3072, 23: 654})])",MACs,8337.884672,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 576, 5: 192, 6: 128, 7: 320, 8: 768, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 2694, 20: 3072, 21: 930, 22: 1501, 23: 2812})])",MACs,6418.400768,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 768, 4: 768, 5: 576, 6: 768, 7: 512, 8: 448, 9: 192, 10: 768, 11: 768, 12: 1585, 13: 1570, 14: 2362, 15: 2314, 16: 3043, 17: 3038, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 1966})])",MACs,7571.113472,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 256, 5: 384, 6: 384, 7: 512, 8: 256, 9: 256, 10: 128, 11: 64, 12: 3040, 13: 3036, 14: 2362, 15: 2314, 16: 2296, 17: 2215, 18: 3072, 19: 1406, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6641.747456,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 256, 4: 384, 5: 576, 6: 704, 7: 512, 8: 448, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 3072, 14: 2795, 15: 3042, 16: 2296, 17: 1580, 18: 3072, 19: 1406, 20: 3072, 21: 1585, 22: 3072, 23: 1966})])",MACs,8219.526656,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 512, 4: 576, 5: 192, 6: 384, 7: 768, 8: 768, 9: 256, 10: 128, 11: 128, 12: 3040, 13: 2190, 14: 3046, 15: 3072, 16: 2764, 17: 2215, 18: 2786, 19: 2114, 20: 3072, 21: 2236, 22: 2158, 23: 654})])",MACs,8169.588224,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 256, 5: 768, 6: 128, 7: 320, 8: 256, 9: 256, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 3043, 17: 2768, 18: 2786, 19: 1406, 20: 2994, 21: 2924, 22: 1501, 23: 654})])",MACs,6810.43712,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 768, 1: 384, 2: 384, 3: 384, 4: 384, 5: 192, 6: 768, 7: 384, 8: 768, 9: 768, 10: 768, 11: 128, 12: 3072, 13: 2190, 14: 3072, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 3072, 21: 930, 22: 1501, 23: 654})])",MACs,7152.272896,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 384, 4: 256, 5: 768, 6: 768, 7: 512, 8: 448, 9: 320, 10: 768, 11: 768, 12: 2227, 13: 1570, 14: 3046, 15: 2791, 16: 2764, 17: 3038, 18: 3072, 19: 2694, 20: 1188, 21: 2236, 22: 2868, 23: 1301})])",MACs,8688.109056,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 256, 4: 576, 5: 384, 6: 128, 7: 320, 8: 448, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 3046, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 2994, 21: 2924, 22: 2158, 23: 654})])",MACs,6593.250816,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 576, 1: 384, 2: 768, 3: 192, 4: 768, 5: 576, 6: 768, 7: 512, 8: 768, 9: 768, 10: 768, 11: 768, 12: 2227, 13: 2190, 14: 2795, 15: 2791, 16: 2764, 17: 2215, 18: 3072, 19: 2694, 20: 2506, 21: 1585, 22: 2868, 23: 1966})])",MACs,9078.834688,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 576, 5: 576, 6: 128, 7: 512, 8: 448, 9: 320, 10: 768, 11: 768, 12: 2227, 13: 2190, 14: 3046, 15: 1717, 16: 2296, 17: 3038, 18: 3072, 19: 2114, 20: 1896, 21: 2924, 22: 2158, 23: 654})])",MACs,8018.789888,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 384, 2: 384, 3: 512, 4: 768, 5: 192, 6: 192, 7: 384, 8: 448, 9: 192, 10: 128, 11: 64, 12: 3072, 13: 3072, 14: 3046, 15: 3042, 16: 3043, 17: 2768, 18: 2786, 19: 2694, 20: 3072, 21: 930, 22: 3072, 23: 1966})])",MACs,8093.042176,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 576, 1: 256, 2: 320, 3: 384, 4: 768, 5: 192, 6: 128, 7: 512, 8: 768, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 2362, 15: 2314, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 2994, 21: 3072, 22: 2868, 23: 1301})])",MACs,7706.510848,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 384, 5: 192, 6: 192, 7: 512, 8: 768, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 2795, 15: 2314, 16: 2764, 17: 2768, 18: 2786, 19: 1406, 20: 3072, 21: 930, 22: 3072, 23: 1966})])",MACs,7948.928512,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 768, 4: 768, 5: 576, 6: 768, 7: 512, 8: 256, 9: 192, 10: 768, 11: 768, 12: 1585, 13: 3036, 14: 2362, 15: 3042, 16: 3043, 17: 3038, 18: 1621, 19: 2114, 20: 3072, 21: 2924, 22: 828, 23: 1966})])",MACs,8274.18368,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 768, 4: 256, 5: 576, 6: 768, 7: 512, 8: 448, 9: 320, 10: 768, 11: 768, 12: 2227, 13: 3072, 14: 3046, 15: 2791, 16: 2764, 17: 3038, 18: 3072, 19: 2694, 20: 1188, 21: 2924, 22: 1501, 23: 1301})])",MACs,9013.495296,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 384, 2: 320, 3: 256, 4: 256, 5: 768, 6: 128, 7: 320, 8: 256, 9: 256, 10: 128, 11: 64, 12: 3040, 13: 2190, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 2924, 22: 2158, 23: 654})])",MACs,6399.19872,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 576, 6: 768, 7: 768, 8: 448, 9: 256, 10: 128, 11: 768, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 2764, 17: 2215, 18: 2268, 19: 1406, 20: 2506, 21: 1585, 22: 2868, 23: 654})])",MACs,7619.085824,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 512, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 256, 10: 128, 11: 64, 12: 3072, 13: 2190, 14: 2795, 15: 2314, 16: 1679, 17: 2215, 18: 3032, 19: 2114, 20: 1188, 21: 3072, 22: 828, 23: 1966})])",MACs,6921.389568,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 576, 5: 192, 6: 128, 7: 512, 8: 768, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 2795, 15: 3042, 16: 2764, 17: 2215, 18: 1621, 19: 1406, 20: 3072, 21: 2236, 22: 1501, 23: 2812})])",MACs,7186.94144,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 192, 4: 256, 5: 192, 6: 384, 7: 512, 8: 768, 9: 768, 10: 128, 11: 64, 12: 1585, 13: 3036, 14: 1775, 15: 2791, 16: 2764, 17: 1580, 18: 2786, 19: 3034, 20: 2506, 21: 2236, 22: 828, 23: 1301})])",MACs,6982.665728,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 256, 5: 384, 6: 192, 7: 512, 8: 256, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 3036, 14: 2362, 15: 2314, 16: 2296, 17: 1580, 18: 3072, 19: 1406, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6021.056,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 3036, 14: 1775, 15: 3042, 16: 2296, 17: 2215, 18: 2786, 19: 1406, 20: 1896, 21: 2924, 22: 828, 23: 1301})])",MACs,6913.590784,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 3042, 16: 2764, 17: 2215, 18: 3032, 19: 1406, 20: 3072, 21: 930, 22: 1501, 23: 2812})])",MACs,6652.626432,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 384, 1: 384, 2: 768, 3: 384, 4: 384, 5: 576, 6: 704, 7: 768, 8: 448, 9: 256, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 3072, 17: 2215, 18: 2268, 19: 2114, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6946.620928,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 192, 6: 768, 7: 768, 8: 448, 9: 256, 10: 768, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 2764, 17: 2215, 18: 2268, 19: 1406, 20: 1188, 21: 930, 22: 2868, 23: 1301})])",MACs,7041.320448,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 768, 4: 768, 5: 384, 6: 704, 7: 512, 8: 256, 9: 320, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 2362, 15: 3042, 16: 3043, 17: 3038, 18: 1621, 19: 2114, 20: 1188, 21: 2924, 22: 2868, 23: 1966})])",MACs,8230.143488,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 384, 4: 256, 5: 384, 6: 704, 7: 320, 8: 448, 9: 192, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 2764, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,7318.603264,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 3072, 16: 1679, 17: 2215, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 2158, 23: 1966})])",MACs,6666.25792,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 512, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2764, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6157.501952,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 576, 1: 768, 2: 384, 3: 256, 4: 256, 5: 576, 6: 704, 7: 384, 8: 448, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 3042, 16: 2296, 17: 1580, 18: 2786, 19: 3034, 20: 1188, 21: 1585, 22: 828, 23: 1301})])",MACs,6904.284672,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 384, 4: 704, 5: 384, 6: 704, 7: 512, 8: 768, 9: 256, 10: 768, 11: 128, 12: 3040, 13: 2712, 14: 3072, 15: 3072, 16: 3072, 17: 2768, 18: 2786, 19: 3034, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,8252.818944,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 384, 4: 768, 5: 576, 6: 704, 7: 512, 8: 256, 9: 320, 10: 768, 11: 768, 12: 1585, 13: 3072, 14: 2362, 15: 3042, 16: 3043, 17: 3038, 18: 1621, 19: 2114, 20: 1188, 21: 2236, 22: 2868, 23: 1966})])",MACs,8503.821824,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 576, 5: 384, 6: 128, 7: 320, 8: 448, 9: 192, 10: 768, 11: 128, 12: 1585, 13: 1570, 14: 3046, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 1406, 20: 1896, 21: 2924, 22: 1501, 23: 654})])",MACs,6450.578944,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 384, 8: 448, 9: 768, 10: 128, 11: 64, 12: 1585, 13: 2190, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 1621, 19: 3034, 20: 1188, 21: 930, 22: 3072, 23: 1966})])",MACs,6811.944448,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 384, 5: 384, 6: 192, 7: 384, 8: 256, 9: 768, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 3046, 15: 2314, 16: 2296, 17: 3038, 18: 1621, 19: 1406, 20: 2506, 21: 930, 22: 2158, 23: 654})])",MACs,6319.048192,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 192, 6: 384, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 3036, 14: 1775, 15: 2791, 16: 2764, 17: 1580, 18: 3072, 19: 1406, 20: 2506, 21: 930, 22: 828, 23: 1301})])",MACs,5889.525248,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 768, 4: 768, 5: 384, 6: 704, 7: 512, 8: 448, 9: 192, 10: 768, 11: 128, 12: 1585, 13: 3036, 14: 3046, 15: 1717, 16: 3043, 17: 1580, 18: 2786, 19: 2114, 20: 1896, 21: 2924, 22: 2158, 23: 1966})])",MACs,8039.040512,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 576, 1: 768, 2: 256, 3: 256, 4: 256, 5: 384, 6: 192, 7: 384, 8: 256, 9: 768, 10: 128, 11: 64, 12: 3072, 13: 2190, 14: 3046, 15: 2314, 16: 2764, 17: 2215, 18: 2786, 19: 1406, 20: 2506, 21: 930, 22: 2158, 23: 1966})])",MACs,7205.029376,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 256, 4: 576, 5: 576, 6: 192, 7: 320, 8: 256, 9: 192, 10: 768, 11: 768, 12: 1585, 13: 2190, 14: 2362, 15: 3042, 16: 2296, 17: 3038, 18: 1621, 19: 2114, 20: 1188, 21: 2924, 22: 828, 23: 654})])",MACs,6923.683328,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 768, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 2795, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5746.329088,top1_acc,-91.39908256880734 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 256, 5: 768, 6: 704, 7: 512, 8: 448, 9: 256, 10: 128, 11: 768, 12: 3040, 13: 3072, 14: 3046, 15: 2791, 16: 2764, 17: 3038, 18: 3072, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,8629.126656,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 704, 7: 512, 8: 256, 9: 320, 10: 768, 11: 64, 12: 2227, 13: 3072, 14: 2795, 15: 2791, 16: 2296, 17: 3038, 18: 3072, 19: 1406, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,7783.908864,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 512, 4: 256, 5: 768, 6: 128, 7: 320, 8: 256, 9: 256, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 2786, 19: 1406, 20: 1188, 21: 2924, 22: 1501, 23: 654})])",MACs,6254.298624,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 576, 5: 192, 6: 128, 7: 320, 8: 768, 9: 320, 10: 128, 11: 768, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 2764, 17: 3038, 18: 1621, 19: 2694, 20: 3072, 21: 2236, 22: 1501, 23: 2812})])",MACs,7984.645632,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 384, 4: 384, 5: 192, 6: 768, 7: 384, 8: 768, 9: 768, 10: 768, 11: 128, 12: 1585, 13: 2190, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2114, 20: 3072, 21: 930, 22: 2868, 23: 654})])",MACs,6753.158656,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 576, 1: 384, 2: 320, 3: 384, 4: 576, 5: 768, 6: 768, 7: 768, 8: 448, 9: 256, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 3046, 15: 2791, 16: 3072, 17: 2215, 18: 2268, 19: 2114, 20: 1188, 21: 2924, 22: 2868, 23: 654})])",MACs,7636.911616,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 192, 4: 256, 5: 384, 6: 384, 7: 384, 8: 768, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 3072, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 2868, 23: 1301})])",MACs,6399.657472,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 2190, 14: 1775, 15: 3072, 16: 2764, 17: 2768, 18: 2786, 19: 1406, 20: 3072, 21: 2924, 22: 2158, 23: 1301})])",MACs,7801.01376,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 448, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 3036, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 1621, 19: 3034, 20: 2506, 21: 1585, 22: 3072, 23: 1966})])",MACs,7955.875328,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 448, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 3042, 16: 2296, 17: 2768, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,6175.589888,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 512, 4: 576, 5: 192, 6: 384, 7: 768, 8: 768, 9: 256, 10: 768, 11: 128, 12: 3040, 13: 2190, 14: 3046, 15: 3072, 16: 2764, 17: 2215, 18: 2786, 19: 2114, 20: 3072, 21: 2924, 22: 2158, 23: 1301})])",MACs,8704.689664,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 512, 4: 384, 5: 192, 6: 128, 7: 768, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 2764, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 3072, 22: 1501, 23: 654})])",MACs,6799.689216,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 256, 4: 384, 5: 192, 6: 704, 7: 768, 8: 448, 9: 768, 10: 768, 11: 64, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 2296, 17: 2215, 18: 2786, 19: 3034, 20: 3072, 21: 1585, 22: 3072, 23: 1966})])",MACs,8549.172736,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 512, 4: 576, 5: 192, 6: 128, 7: 320, 8: 448, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 2190, 14: 1775, 15: 2314, 16: 2764, 17: 3038, 18: 2786, 19: 3034, 20: 1188, 21: 1585, 22: 1501, 23: 1966})])",MACs,6803.359232,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 768, 9: 256, 10: 128, 11: 128, 12: 3040, 13: 3036, 14: 2795, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,6112.937472,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 256, 4: 256, 5: 192, 6: 768, 7: 512, 8: 256, 9: 320, 10: 768, 11: 768, 12: 2227, 13: 3072, 14: 1775, 15: 3072, 16: 2764, 17: 2215, 18: 3072, 19: 1406, 20: 1188, 21: 930, 22: 2158, 23: 1966})])",MACs,7290.226176,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 384, 2: 384, 3: 384, 4: 384, 5: 192, 6: 768, 7: 384, 8: 768, 9: 768, 10: 768, 11: 64, 12: 3072, 13: 3072, 14: 3072, 15: 1717, 16: 2764, 17: 1580, 18: 2268, 19: 2114, 20: 3072, 21: 930, 22: 2868, 23: 654})])",MACs,7907.706368,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 384, 5: 384, 6: 192, 7: 384, 8: 768, 9: 768, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 3046, 15: 2314, 16: 2296, 17: 3038, 18: 2786, 19: 1406, 20: 2506, 21: 930, 22: 2158, 23: 1301})])",MACs,7019.628032,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 512, 4: 576, 5: 576, 6: 128, 7: 320, 8: 768, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 2764, 17: 2215, 18: 1621, 19: 2694, 20: 3072, 21: 3072, 22: 1501, 23: 2812})])",MACs,7697.073664,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2764, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6102.976,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 704, 7: 512, 8: 448, 9: 192, 10: 768, 11: 64, 12: 2227, 13: 1570, 14: 3046, 15: 2314, 16: 1679, 17: 2215, 18: 3072, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,7121.143296,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 384, 4: 384, 5: 192, 6: 768, 7: 768, 8: 448, 9: 256, 10: 768, 11: 64, 12: 3072, 13: 3072, 14: 3072, 15: 2791, 16: 2764, 17: 1580, 18: 2268, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,7440.434688,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 384, 5: 384, 6: 128, 7: 320, 8: 448, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 2994, 21: 1585, 22: 2158, 23: 654})])",MACs,6362.564096,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 256, 4: 384, 5: 192, 6: 768, 7: 320, 8: 256, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 2190, 14: 3072, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 1406, 20: 2506, 21: 2236, 22: 2158, 23: 1966})])",MACs,7051.871744,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 512, 4: 576, 5: 192, 6: 384, 7: 768, 8: 768, 9: 256, 10: 128, 11: 128, 12: 3040, 13: 3036, 14: 3046, 15: 3042, 16: 3043, 17: 2215, 18: 2786, 19: 2114, 20: 3072, 21: 2236, 22: 828, 23: 654})])",MACs,7768.966656,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 256, 5: 384, 6: 192, 7: 512, 8: 256, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 2190, 14: 2362, 15: 2314, 16: 2296, 17: 1580, 18: 3072, 19: 1406, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,5854.725632,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 576, 1: 384, 2: 384, 3: 256, 4: 256, 5: 576, 6: 704, 7: 384, 8: 768, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 2795, 15: 2314, 16: 2764, 17: 1580, 18: 2786, 19: 3034, 20: 1188, 21: 1585, 22: 828, 23: 1301})])",MACs,7026.443776,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 384, 1: 384, 2: 320, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3036, 14: 1775, 15: 3042, 16: 3043, 17: 2768, 18: 2786, 19: 1406, 20: 3072, 21: 2236, 22: 828, 23: 654})])",MACs,6865.290752,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 384, 1: 384, 2: 256, 3: 384, 4: 576, 5: 576, 6: 704, 7: 320, 8: 448, 9: 256, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 3072, 17: 2215, 18: 2268, 19: 2114, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6596.78976,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 576, 6: 768, 7: 512, 8: 448, 9: 256, 10: 128, 11: 768, 12: 1585, 13: 3072, 14: 1775, 15: 3042, 16: 2764, 17: 1580, 18: 2268, 19: 1406, 20: 1188, 21: 930, 22: 2868, 23: 1301})])",MACs,7047.611904,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7143.68768,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 256, 5: 384, 6: 384, 7: 512, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 2362, 15: 2314, 16: 2296, 17: 2768, 18: 3072, 19: 1406, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6275.139072,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 704, 7: 320, 8: 448, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 3072, 14: 3046, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,8063.419904,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 192, 6: 768, 7: 768, 8: 448, 9: 256, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 1775, 15: 2791, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5886.05184,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 576, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 2795, 15: 2314, 16: 2764, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5597.169152,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5460.985344,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 384, 4: 576, 5: 384, 6: 128, 7: 320, 8: 448, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 2190, 14: 3046, 15: 1717, 16: 2764, 17: 1580, 18: 3072, 19: 2114, 20: 2994, 21: 2924, 22: 1501, 23: 654})])",MACs,7065.69984,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 576, 5: 384, 6: 128, 7: 512, 8: 256, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 2362, 15: 3042, 16: 2296, 17: 2215, 18: 3072, 19: 1406, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6055.331328,top1_acc,-91.39908256880734 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 384, 5: 384, 6: 192, 7: 384, 8: 768, 9: 768, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 3046, 15: 2314, 16: 2296, 17: 3038, 18: 1621, 19: 1406, 20: 2506, 21: 930, 22: 2158, 23: 654})])",MACs,6881.478144,top1_acc,-91.1697247706422 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 256, 5: 576, 6: 704, 7: 512, 8: 448, 9: 320, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 2158, 23: 1301})])",MACs,8214.939136,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 384, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 3036, 14: 1775, 15: 2314, 16: 2764, 17: 1580, 18: 1621, 19: 1406, 20: 3072, 21: 930, 22: 1501, 23: 2812})])",MACs,6395.463168,top1_acc,-91.5137614678899 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 2795, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5183.899136,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 768, 1: 384, 2: 320, 3: 256, 4: 256, 5: 384, 6: 384, 7: 384, 8: 768, 9: 768, 10: 128, 11: 768, 12: 1585, 13: 3072, 14: 1775, 15: 3072, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 2868, 23: 1301})])",MACs,7195.264512,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 384, 5: 576, 6: 704, 7: 512, 8: 448, 9: 768, 10: 768, 11: 64, 12: 2227, 13: 1570, 14: 3046, 15: 2314, 16: 1679, 17: 2215, 18: 3072, 19: 3034, 20: 2506, 21: 1585, 22: 1501, 23: 1301})])",MACs,8066.631168,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 512, 4: 384, 5: 576, 6: 704, 7: 768, 8: 448, 9: 320, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 1717, 16: 2764, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 3072, 22: 1501, 23: 1301})])",MACs,7994.67264,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 576, 5: 384, 6: 128, 7: 512, 8: 256, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 2362, 15: 3042, 16: 1679, 17: 2215, 18: 3072, 19: 1406, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,5934.024192,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 192, 6: 768, 7: 768, 8: 448, 9: 256, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 2215, 18: 2268, 19: 1406, 20: 1188, 21: 930, 22: 2868, 23: 654})])",MACs,6728.058368,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 512, 4: 576, 5: 192, 6: 768, 7: 320, 8: 256, 9: 768, 10: 128, 11: 768, 12: 1585, 13: 2190, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2114, 20: 3072, 21: 930, 22: 1501, 23: 654})])",MACs,6537.152,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 256, 5: 576, 6: 704, 7: 512, 8: 448, 9: 320, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 2236, 22: 2158, 23: 1301})])",MACs,7676.82304,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 384, 1: 256, 2: 768, 3: 512, 4: 256, 5: 768, 6: 384, 7: 320, 8: 256, 9: 256, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 2786, 19: 1406, 20: 3072, 21: 2924, 22: 1501, 23: 654})])",MACs,6761.022976,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 384, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 768, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 3046, 15: 2314, 16: 2764, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5782.83264,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 768, 9: 256, 10: 128, 11: 128, 12: 3040, 13: 3036, 14: 2795, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,6221.661696,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 384, 4: 576, 5: 768, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6046.94272,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 768, 7: 512, 8: 448, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 3072, 14: 3046, 15: 3042, 16: 2764, 17: 2215, 18: 3072, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,7827.424768,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 384, 5: 384, 6: 128, 7: 384, 8: 256, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,5257.823744,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 768, 7: 768, 8: 448, 9: 256, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 1775, 15: 3042, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,6389.761536,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 384, 1: 768, 2: 320, 3: 384, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 3036, 14: 3046, 15: 3042, 16: 1679, 17: 2768, 18: 2786, 19: 2694, 20: 2994, 21: 2924, 22: 1501, 23: 1301})])",MACs,7970.42432,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 256, 4: 384, 5: 576, 6: 704, 7: 512, 8: 448, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 2190, 14: 1775, 15: 3042, 16: 2296, 17: 1580, 18: 2786, 19: 3034, 20: 2506, 21: 1585, 22: 3072, 23: 1966})])",MACs,8270.775808,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 384, 4: 576, 5: 192, 6: 768, 7: 384, 8: 256, 9: 768, 10: 768, 11: 128, 12: 3072, 13: 2190, 14: 3072, 15: 1717, 16: 1679, 17: 2215, 18: 3032, 19: 1406, 20: 3072, 21: 930, 22: 1501, 23: 2812})])",MACs,7866.87744,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2114, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,6348.08064,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 256, 5: 576, 6: 704, 7: 384, 8: 448, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 2190, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 3072, 23: 1966})])",MACs,6844.057088,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6868.43648,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5582.29248,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 192, 6: 768, 7: 768, 8: 448, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 2190, 14: 1775, 15: 2791, 16: 2764, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,6199.31392,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 384, 4: 384, 5: 192, 6: 128, 7: 384, 8: 768, 9: 192, 10: 768, 11: 128, 12: 3072, 13: 1570, 14: 3072, 15: 1717, 16: 2764, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6772.622848,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 2795, 15: 2314, 16: 2296, 17: 2768, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5722.015232,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 512, 4: 576, 5: 192, 6: 128, 7: 768, 8: 768, 9: 256, 10: 128, 11: 128, 12: 3040, 13: 2190, 14: 3046, 15: 3072, 16: 2764, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 2158, 23: 654})])",MACs,7662.863872,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 512, 4: 576, 5: 192, 6: 384, 7: 768, 8: 256, 9: 256, 10: 128, 11: 128, 12: 3040, 13: 2190, 14: 2795, 15: 3072, 16: 2764, 17: 2215, 18: 2786, 19: 2114, 20: 3072, 21: 2236, 22: 2158, 23: 654})])",MACs,7983.924736,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 768, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 2795, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5637.604864,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 2786, 19: 1406, 20: 1188, 21: 2924, 22: 1501, 23: 654})])",MACs,5613.815296,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 576, 6: 704, 7: 512, 8: 448, 9: 256, 10: 768, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 2268, 19: 1406, 20: 1188, 21: 930, 22: 2868, 23: 1301})])",MACs,6341.330432,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 576, 5: 576, 6: 704, 7: 512, 8: 256, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 2362, 15: 3042, 16: 2296, 17: 1580, 18: 3072, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7941.195264,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 576, 1: 256, 2: 384, 3: 384, 4: 256, 5: 192, 6: 704, 7: 384, 8: 448, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 2296, 17: 1580, 18: 2786, 19: 3034, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,6400.574976,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 256, 5: 576, 6: 704, 7: 320, 8: 448, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 3043, 17: 3038, 18: 2786, 19: 1406, 20: 1896, 21: 2236, 22: 828, 23: 1301})])",MACs,7617.250816,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 448, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 3072, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 1621, 19: 3034, 20: 3072, 21: 1585, 22: 3072, 23: 1966})])",MACs,8074.233344,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 384, 5: 192, 6: 128, 7: 320, 8: 768, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 3042, 16: 2764, 17: 1580, 18: 1621, 19: 2114, 20: 3072, 21: 930, 22: 1501, 23: 654})])",MACs,5938.021888,top1_acc,-91.39908256880734 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 256, 4: 256, 5: 192, 6: 384, 7: 384, 8: 768, 9: 768, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 3042, 16: 2764, 17: 2768, 18: 2786, 19: 1406, 20: 1188, 21: 2236, 22: 828, 23: 1301})])",MACs,6987.843072,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 512, 4: 576, 5: 192, 6: 384, 7: 768, 8: 256, 9: 256, 10: 128, 11: 128, 12: 3040, 13: 2190, 14: 3046, 15: 3072, 16: 2296, 17: 2215, 18: 2786, 19: 2114, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,7620.199936,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 512, 8: 448, 9: 768, 10: 768, 11: 768, 12: 2227, 13: 2190, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 1621, 19: 3034, 20: 2506, 21: 1585, 22: 3072, 23: 1966})])",MACs,8116.700672,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 384, 1: 256, 2: 384, 3: 192, 4: 256, 5: 192, 6: 192, 7: 512, 8: 448, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 3036, 14: 1775, 15: 2791, 16: 2296, 17: 1580, 18: 2786, 19: 3034, 20: 2506, 21: 930, 22: 828, 23: 1301})])",MACs,6170.412544,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 768, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2764, 17: 1580, 18: 1621, 19: 2694, 20: 3072, 21: 2236, 22: 3072, 23: 654})])",MACs,7693.075968,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 256, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 2158, 23: 1301})])",MACs,7887.783424,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 384, 4: 384, 5: 576, 6: 768, 7: 768, 8: 448, 9: 320, 10: 768, 11: 64, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 3043, 17: 2215, 18: 2268, 19: 1406, 20: 1896, 21: 930, 22: 2868, 23: 1301})])",MACs,7606.961664,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 384, 5: 384, 6: 128, 7: 384, 8: 768, 9: 256, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 2795, 15: 1717, 16: 2296, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 1585, 22: 1501, 23: 1301})])",MACs,5830.936064,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 576, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 2795, 15: 2314, 16: 2296, 17: 2768, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5831.067136,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 256, 5: 384, 6: 192, 7: 768, 8: 256, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 3036, 14: 2362, 15: 2314, 16: 2296, 17: 1580, 18: 3072, 19: 1406, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6130.107904,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 576, 5: 576, 6: 704, 7: 320, 8: 768, 9: 768, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2764, 17: 1580, 18: 1621, 19: 2694, 20: 3072, 21: 2236, 22: 1501, 23: 654})])",MACs,7012.61568,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 512, 4: 576, 5: 192, 6: 768, 7: 320, 8: 768, 9: 768, 10: 128, 11: 768, 12: 1585, 13: 2190, 14: 2795, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2114, 20: 3072, 21: 930, 22: 1501, 23: 1301})])",MACs,7301.105152,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 3072, 15: 1717, 16: 1679, 17: 2768, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5132.977664,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 256, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 2236, 22: 2158, 23: 1301})])",MACs,8146.912768,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 512, 8: 256, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 2362, 15: 3042, 16: 2296, 17: 1580, 18: 3072, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7859.406336,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 2158, 23: 1301})])",MACs,8214.939136,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 384, 5: 576, 6: 704, 7: 384, 8: 768, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 3072, 23: 1301})])",MACs,7760.905728,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 256, 5: 384, 6: 192, 7: 384, 8: 256, 9: 256, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 2795, 15: 2314, 16: 2764, 17: 2768, 18: 3072, 19: 1406, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6116.279808,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 384, 4: 256, 5: 576, 6: 192, 7: 320, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 3046, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,7409.10848,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 256, 4: 384, 5: 384, 6: 768, 7: 768, 8: 256, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 2764, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 1585, 22: 2868, 23: 654})])",MACs,6484.06784,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 384, 4: 576, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 2795, 15: 2314, 16: 2296, 17: 2768, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,5881.595392,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 576, 5: 576, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 3046, 15: 1717, 16: 2764, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6208.685568,top1_acc,-91.39908256880734 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 576, 5: 576, 6: 704, 7: 512, 8: 256, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 2362, 15: 3042, 16: 2296, 17: 3038, 18: 3072, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 1301})])",MACs,8136.951296,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 512, 4: 576, 5: 192, 6: 128, 7: 384, 8: 768, 9: 256, 10: 128, 11: 128, 12: 3040, 13: 2190, 14: 3046, 15: 1717, 16: 2764, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 2158, 23: 654})])",MACs,7108.036096,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 448, 9: 256, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 2764, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 2236, 22: 828, 23: 1301})])",MACs,7051.6096,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5173.216768,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5351.93344,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 384, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 3072, 23: 654})])",MACs,6262.752768,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4873.651712,top1_acc,-91.39908256880734 +"OrderedDict([(, {0: 768, 1: 384, 2: 384, 3: 384, 4: 384, 5: 192, 6: 768, 7: 384, 8: 768, 9: 768, 10: 768, 11: 128, 12: 3072, 13: 2190, 14: 2795, 15: 2314, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 3072, 21: 930, 22: 1501, 23: 1301})])",MACs,7203.194368,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 1585, 22: 3072, 23: 654})])",MACs,6088.951296,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 576, 5: 576, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7225.476608,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 256, 5: 576, 6: 704, 7: 512, 8: 448, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 3046, 15: 2314, 16: 1679, 17: 2215, 18: 3072, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,6793.987584,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 384, 1: 384, 2: 256, 3: 256, 4: 256, 5: 384, 6: 384, 7: 384, 8: 768, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 3072, 16: 2764, 17: 1580, 18: 1621, 19: 2114, 20: 3072, 21: 930, 22: 2868, 23: 654})])",MACs,6331.827712,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 576, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 512, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 3036, 14: 2362, 15: 2314, 16: 2296, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5501.945344,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 768, 11: 128, 12: 1585, 13: 1570, 14: 2795, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5838.21056,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 384, 5: 192, 6: 128, 7: 384, 8: 448, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 2268, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5415.241216,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 768, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5447.026176,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 512, 4: 256, 5: 192, 6: 704, 7: 512, 8: 448, 9: 320, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 2158, 23: 1301})])",MACs,7625.639424,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 512, 4: 384, 5: 576, 6: 704, 7: 768, 8: 448, 9: 320, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 1717, 16: 2764, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 3072, 22: 1501, 23: 654})])",MACs,7798.916608,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 384, 2: 384, 3: 384, 4: 384, 5: 192, 6: 768, 7: 768, 8: 768, 9: 768, 10: 768, 11: 128, 12: 3072, 13: 2190, 14: 3072, 15: 3072, 16: 1679, 17: 2215, 18: 1621, 19: 2114, 20: 3072, 21: 930, 22: 1501, 23: 654})])",MACs,7707.100672,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 256, 5: 192, 6: 128, 7: 768, 8: 448, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 2786, 19: 1406, 20: 1188, 21: 2924, 22: 1501, 23: 654})])",MACs,5886.445056,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 384, 4: 384, 5: 576, 6: 768, 7: 768, 8: 448, 9: 256, 10: 768, 11: 64, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 2764, 17: 2215, 18: 2268, 19: 1406, 20: 1188, 21: 930, 22: 2868, 23: 1301})])",MACs,7576.487424,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 384, 4: 576, 5: 768, 6: 128, 7: 320, 8: 256, 9: 320, 10: 128, 11: 64, 12: 3040, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 2158, 23: 1301})])",MACs,6653.15072,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 192, 6: 768, 7: 320, 8: 256, 9: 256, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 1775, 15: 2791, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5613.42208,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 448, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 3043, 17: 3038, 18: 2786, 19: 1406, 20: 1896, 21: 2236, 22: 828, 23: 654})])",MACs,6682.248704,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 512, 8: 256, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 2362, 15: 3042, 16: 2296, 17: 1580, 18: 3072, 19: 2114, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7718.11072,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 512, 4: 576, 5: 192, 6: 128, 7: 768, 8: 768, 9: 256, 10: 128, 11: 128, 12: 3040, 13: 2190, 14: 3046, 15: 3072, 16: 2764, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 2158, 23: 654})])",MACs,7824.672256,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 256, 5: 576, 6: 192, 7: 384, 8: 256, 9: 320, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 2158, 23: 1301})])",MACs,6783.501824,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 384, 4: 576, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 2795, 15: 2314, 16: 2296, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5778.179584,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 704, 7: 320, 8: 448, 9: 320, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,8058.504704,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 512, 4: 576, 5: 576, 6: 768, 7: 320, 8: 256, 9: 320, 10: 768, 11: 768, 12: 1585, 13: 2190, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 1621, 19: 2114, 20: 1896, 21: 2236, 22: 1501, 23: 654})])",MACs,7019.234816,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 384, 4: 576, 5: 768, 6: 128, 7: 320, 8: 448, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,6591.415808,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 512, 8: 256, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 3072, 23: 654})])",MACs,6273.3696,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 576, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 512, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 3036, 14: 2362, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5384.570368,top1_acc,-91.5137614678899 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 256, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 3036, 14: 3046, 15: 3072, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 2236, 22: 2158, 23: 1301})])",MACs,8195.081728,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 2296, 17: 3038, 18: 1621, 19: 2694, 20: 1188, 21: 2236, 22: 2158, 23: 1301})])",MACs,7713.261056,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 512, 4: 576, 5: 192, 6: 128, 7: 512, 8: 448, 9: 256, 10: 128, 11: 64, 12: 3040, 13: 2190, 14: 3046, 15: 3072, 16: 2764, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 2158, 23: 654})])",MACs,7390.234112,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 256, 5: 576, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 3072, 15: 1717, 16: 1679, 17: 2768, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 2158, 23: 654})])",MACs,5966.9888,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 576, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5641.733632,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 576, 1: 768, 2: 768, 3: 256, 4: 256, 5: 576, 6: 192, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 2362, 15: 2791, 16: 2296, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 2236, 22: 2158, 23: 1301})])",MACs,6684.476928,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 256, 4: 576, 5: 192, 6: 704, 7: 320, 8: 768, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 3042, 16: 1679, 17: 3038, 18: 3072, 19: 2694, 20: 2506, 21: 930, 22: 828, 23: 654})])",MACs,6848.644608,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 512, 8: 256, 9: 768, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 2362, 15: 3042, 16: 2296, 17: 1580, 18: 3072, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7395.935744,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 384, 8: 768, 9: 768, 10: 768, 11: 128, 12: 1585, 13: 1570, 14: 2795, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 3072, 21: 930, 22: 828, 23: 654})])",MACs,6599.4112,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 384, 1: 768, 2: 768, 3: 256, 4: 256, 5: 576, 6: 704, 7: 512, 8: 448, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 3046, 15: 2314, 16: 1679, 17: 2215, 18: 3072, 19: 2114, 20: 1188, 21: 930, 22: 2868, 23: 1301})])",MACs,7030.507008,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 384, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 3072, 14: 3046, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,7654.475264,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,6489.376256,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5299.17696,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 704, 7: 512, 8: 448, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6066.537984,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2768, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,4988.012032,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 256, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 3046, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 2158, 23: 1301})])",MACs,7892.698624,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 448, 9: 768, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 3043, 17: 3038, 18: 2786, 19: 1406, 20: 3072, 21: 930, 22: 828, 23: 1301})])",MACs,7135.168,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 256, 5: 576, 6: 704, 7: 512, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 3046, 15: 1717, 16: 1679, 17: 2215, 18: 3072, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6249.514496,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 256, 4: 576, 5: 576, 6: 192, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 2362, 15: 3042, 16: 1679, 17: 2215, 18: 3072, 19: 1406, 20: 2506, 21: 1585, 22: 828, 23: 654})])",MACs,6541.477376,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 2296, 17: 2215, 18: 2786, 19: 1406, 20: 1188, 21: 2924, 22: 1501, 23: 654})])",MACs,5731.190272,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 384, 1: 384, 2: 256, 3: 256, 4: 256, 5: 384, 6: 384, 7: 384, 8: 768, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 2190, 14: 1775, 15: 2791, 16: 2764, 17: 1580, 18: 1621, 19: 2114, 20: 3072, 21: 930, 22: 2868, 23: 654})])",MACs,6398.477824,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 384, 5: 192, 6: 768, 7: 768, 8: 448, 9: 256, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 1775, 15: 2791, 16: 1679, 17: 2215, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6060.574208,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 704, 7: 768, 8: 768, 9: 192, 10: 768, 11: 128, 12: 2227, 13: 1570, 14: 3046, 15: 2314, 16: 1679, 17: 2215, 18: 3072, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,7393.773056,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 512, 8: 448, 9: 320, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 2236, 22: 828, 23: 1301})])",MACs,6842.811904,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4692.903424,top1_acc,-91.28440366972477 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 704, 7: 512, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 3036, 14: 3046, 15: 2314, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 828, 23: 654})])",MACs,6964.381184,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 256, 5: 576, 6: 128, 7: 512, 8: 256, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 2362, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 1585, 22: 3072, 23: 654})])",MACs,6539.576832,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2114, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,6811.551232,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 256, 5: 576, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2764, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 2236, 22: 3072, 23: 1301})])",MACs,6931.875328,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 384, 6: 384, 7: 384, 8: 768, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 3072, 16: 2764, 17: 1580, 18: 1621, 19: 2694, 20: 3072, 21: 930, 22: 1501, 23: 654})])",MACs,6095.308288,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 256, 5: 576, 6: 192, 7: 320, 8: 448, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5582.161408,top1_acc,-91.5137614678899 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 256, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 3072, 15: 2791, 16: 1679, 17: 2768, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5371.397632,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 512, 4: 576, 5: 192, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 768, 12: 1585, 13: 2190, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 3072, 21: 930, 22: 1501, 23: 1301})])",MACs,6751.12704,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 3040, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,7864.321536,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 512, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4992.79616,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 256, 5: 576, 6: 704, 7: 320, 8: 448, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 2158, 23: 654})])",MACs,6451.037696,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 3036, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7778.338304,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 384, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 2795, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,6128.141824,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 3072, 23: 1301})])",MACs,6069.093888,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 576, 5: 576, 6: 704, 7: 512, 8: 256, 9: 256, 10: 128, 11: 768, 12: 2227, 13: 3072, 14: 2362, 15: 1717, 16: 2296, 17: 1580, 18: 3072, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7757.891072,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 576, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 3036, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6148.064768,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 3046, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 2158, 23: 1301})])",MACs,7756.383744,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 3072, 15: 1717, 16: 1679, 17: 2768, 18: 1621, 19: 2114, 20: 2506, 21: 1585, 22: 828, 23: 654})])",MACs,6519.522816,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 384, 4: 576, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 2994, 21: 930, 22: 1501, 23: 654})])",MACs,6824.723968,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 384, 4: 576, 5: 192, 6: 704, 7: 384, 8: 768, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 2795, 15: 2314, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 3072, 23: 1301})])",MACs,8000.636416,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 384, 4: 576, 5: 576, 6: 768, 7: 768, 8: 256, 9: 192, 10: 768, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6691.751424,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 384, 4: 384, 5: 576, 6: 704, 7: 384, 8: 448, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 930, 22: 3072, 23: 654})])",MACs,6507.00544,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5375.002112,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 768, 7: 320, 8: 448, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 3072, 14: 3046, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,7849.444864,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 576, 6: 128, 7: 320, 8: 448, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 3046, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 2158, 23: 654})])",MACs,6329.533952,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 768, 2: 384, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 3072, 23: 654})])",MACs,5973.476864,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 3046, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,6793.594368,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 512, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 3046, 15: 1717, 16: 2296, 17: 3038, 18: 1621, 19: 2114, 20: 2506, 21: 930, 22: 828, 23: 654})])",MACs,5997.594112,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 768, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5292.361216,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 320, 3: 192, 4: 384, 5: 576, 6: 192, 7: 384, 8: 768, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6565.463552,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 384, 5: 192, 6: 128, 7: 384, 8: 448, 9: 768, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 3042, 16: 2296, 17: 2215, 18: 2268, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5598.545408,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 704, 7: 512, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 2190, 14: 3046, 15: 2314, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 828, 23: 654})])",MACs,6579.947008,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 256, 4: 384, 5: 192, 6: 768, 7: 768, 8: 448, 9: 256, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 1775, 15: 2791, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6022.36672,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 192, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 3072, 23: 654})])",MACs,5425.00608,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 256, 5: 576, 6: 704, 7: 320, 8: 448, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 2296, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 2158, 23: 1301})])",MACs,6717.310464,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2768, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5015.275008,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 192, 4: 384, 5: 576, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5538.448896,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 256, 5: 192, 6: 128, 7: 320, 8: 768, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 3046, 15: 2314, 16: 1679, 17: 3038, 18: 3072, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,6311.577088,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 128, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 2268, 19: 1406, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6051.923456,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 384, 5: 576, 6: 768, 7: 512, 8: 448, 9: 320, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 2764, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 2236, 22: 2158, 23: 1301})])",MACs,7971.931648,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7696.15616,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,7611.418112,top1_acc,-93.69266055045871 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 256, 5: 192, 6: 704, 7: 768, 8: 448, 9: 256, 10: 768, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 2215, 18: 2268, 19: 1406, 20: 1188, 21: 930, 22: 2868, 23: 1301})])",MACs,6746.21184,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 384, 4: 384, 5: 576, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5494.47424,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 192, 4: 256, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 3046, 15: 2791, 16: 2296, 17: 1580, 18: 1621, 19: 2114, 20: 2506, 21: 2236, 22: 3072, 23: 1301})])",MACs,7347.045888,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 576, 5: 192, 6: 128, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 1501, 23: 654})])",MACs,6369.05216,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,4836.230656,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 704, 7: 768, 8: 768, 9: 192, 10: 768, 11: 128, 12: 1585, 13: 3036, 14: 3046, 15: 2314, 16: 1679, 17: 2215, 18: 3072, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,7423.460864,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 384, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5515.511296,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 768, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5691.213312,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 576, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 3036, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7860.127232,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 576, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2114, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7436.30592,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 768, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 2314, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,8001.422848,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 512, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 3072, 15: 1717, 16: 1679, 17: 2768, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5132.977664,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 256, 5: 576, 6: 704, 7: 768, 8: 448, 9: 256, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 2236, 22: 2158, 23: 1301})])",MACs,7758.611968,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 320, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,7164.265984,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 512, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5210.899968,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 192, 6: 192, 7: 320, 8: 256, 9: 256, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 2768, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5608.113664,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 704, 7: 512, 8: 448, 9: 192, 10: 768, 11: 128, 12: 2227, 13: 1570, 14: 3046, 15: 2314, 16: 1679, 17: 2215, 18: 3072, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,7148.406272,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 828, 23: 654})])",MACs,6920.603136,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 768, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 3072, 23: 654})])",MACs,6482.822656,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 576, 5: 576, 6: 704, 7: 320, 8: 448, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 2296, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 2158, 23: 1301})])",MACs,6908.151296,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5461.247488,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2768, 18: 1621, 19: 2114, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7072.384512,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 384, 4: 256, 5: 576, 6: 704, 7: 384, 8: 448, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2768, 18: 1621, 19: 2694, 20: 2506, 21: 930, 22: 3072, 23: 654})])",MACs,6686.049792,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 704, 7: 512, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 3046, 15: 2314, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 1501, 23: 654})])",MACs,6934.693376,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 576, 5: 768, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6113.723904,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4774.364672,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 384, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5559.944704,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 192, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,7239.566848,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 2795, 15: 1717, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5448.205824,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4992.79616,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 192, 6: 768, 7: 512, 8: 448, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 1775, 15: 2791, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5804.262912,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2768, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5435.16416,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 3036, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7560.234496,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 2190, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5020.583424,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 384, 4: 256, 5: 576, 6: 704, 7: 768, 8: 768, 9: 192, 10: 768, 11: 64, 12: 2227, 13: 1570, 14: 3046, 15: 2314, 16: 1679, 17: 2215, 18: 3072, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,7366.51008,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 3072, 23: 654})])",MACs,5396.301312,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 576, 5: 192, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 3072, 15: 1717, 16: 1679, 17: 2768, 18: 1621, 19: 2114, 20: 2506, 21: 930, 22: 828, 23: 654})])",MACs,6346.311168,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5450.8928,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 384, 4: 576, 5: 768, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5278.598656,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 192, 4: 256, 5: 576, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 3072, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 2158, 23: 654})])",MACs,5706.15552,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 192, 6: 768, 7: 384, 8: 256, 9: 256, 10: 128, 11: 128, 12: 2227, 13: 2190, 14: 1775, 15: 2791, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5766.907392,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 384, 4: 576, 5: 192, 6: 704, 7: 384, 8: 256, 9: 320, 10: 768, 11: 128, 12: 3040, 13: 3036, 14: 2795, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,7518.291456,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5019.731456,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,6299.059712,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 2236, 22: 3072, 23: 1301})])",MACs,8246.65856,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 2296, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5746.329088,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 768, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,5794.170368,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 384, 4: 576, 5: 768, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6455.88736,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5046.994432,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 768, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5046.994432,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 320, 8: 448, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,7436.895744,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 384, 4: 256, 5: 192, 6: 704, 7: 512, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 3036, 14: 3046, 15: 2314, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 1501, 23: 654})])",MACs,7151.22432,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 768, 2: 384, 3: 256, 4: 384, 5: 192, 6: 128, 7: 384, 8: 448, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5074.585088,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 3036, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 3072, 23: 654})])",MACs,6223.56224,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7914.259968,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 384, 4: 384, 5: 576, 6: 704, 7: 384, 8: 768, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 3036, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 3072, 23: 1301})])",MACs,8122.271232,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 384, 5: 576, 6: 704, 7: 384, 8: 768, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 3072, 23: 654})])",MACs,7210.403328,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4828.759552,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5341.12,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 384, 4: 576, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 3040, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,7455.376896,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4747.101696,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5019.731456,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4720.1664,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5328.66816,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 576, 6: 704, 7: 320, 8: 256, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 930, 22: 3072, 23: 654})])",MACs,6125.323776,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 192, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 828, 23: 654})])",MACs,6574.50752,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 828, 23: 654})])",MACs,6702.499328,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 384, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 2190, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5313.398272,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 384, 4: 256, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 2768, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 2158, 23: 654})])",MACs,7057.966592,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,6053.824,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 384, 4: 576, 5: 768, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6359.090688,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,6925.583872,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 576, 1: 384, 2: 256, 3: 384, 4: 576, 5: 768, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6401.361408,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 448, 9: 256, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7239.501312,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 256, 5: 576, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 2694, 20: 2506, 21: 930, 22: 828, 23: 654})])",MACs,5886.510592,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 3040, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,7618.954752,top1_acc,-93.69266055045871 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,4722.198016,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 256, 4: 256, 5: 768, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5890.115072,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 384, 5: 192, 6: 192, 7: 320, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 2694, 20: 1188, 21: 1585, 22: 2158, 23: 654})])",MACs,6231.164416,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5305.533952,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 576, 5: 576, 6: 704, 7: 512, 8: 448, 9: 768, 10: 768, 11: 128, 12: 1585, 13: 3072, 14: 3046, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 2236, 22: 2158, 23: 1301})])",MACs,8516.3392,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 256, 5: 576, 6: 704, 7: 320, 8: 448, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 1621, 19: 1406, 20: 2506, 21: 930, 22: 828, 23: 654})])",MACs,5952.833024,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4703.913472,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 1585, 22: 3072, 23: 654})])",MACs,6856.64,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7070.221824,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 384, 4: 576, 5: 768, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 3072, 23: 654})])",MACs,7185.9584,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 384, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,4901.570048,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 192, 4: 576, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 3036, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 3072, 23: 654})])",MACs,7410.157056,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,6430.393856,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 192, 4: 576, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7282.230784,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 2190, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5082.973696,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 384, 2: 768, 3: 256, 4: 384, 5: 576, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,6300.173824,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 384, 4: 576, 5: 768, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6077.941248,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5510.53056,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 768, 2: 320, 3: 192, 4: 384, 5: 576, 6: 192, 7: 384, 8: 768, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 2236, 22: 3072, 23: 1301})])",MACs,7135.82336,top1_acc,-91.5137614678899 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 384, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5119.804928,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 828, 23: 654})])",MACs,6866.077184,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 320, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,7584.155136,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 3040, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,7332.300288,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 2296, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5713.888768,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 384, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5144.905216,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 576, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 2190, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5318.706688,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 768, 2: 384, 3: 192, 4: 384, 5: 192, 6: 128, 7: 384, 8: 448, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4929.947136,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 576, 5: 768, 6: 128, 7: 384, 8: 256, 9: 768, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 1501, 23: 654})])",MACs,6557.14048,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4813.424128,top1_acc,-91.5137614678899 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 384, 5: 768, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 1501, 23: 654})])",MACs,6605.9648,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 576, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 2190, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5510.399488,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 1301})])",MACs,7015.958016,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4766.36928,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 576, 5: 192, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 2158, 23: 654})])",MACs,6639.912448,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,6894.585344,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 256, 5: 768, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 2190, 14: 1775, 15: 2791, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5510.727168,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 2768, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5399.44704,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5045.093888,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7750.682112,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,7191.52896,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 384, 4: 384, 5: 576, 6: 704, 7: 384, 8: 448, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 1621, 19: 2694, 20: 2506, 21: 930, 22: 3072, 23: 654})])",MACs,6793.659904,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,5790.565888,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5790.0416,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5343.610368,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,6834.947584,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 448, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 2190, 14: 1775, 15: 2791, 16: 2296, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,6628.378112,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 256, 4: 576, 5: 768, 6: 128, 7: 384, 8: 448, 9: 192, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 2314, 16: 2296, 17: 2215, 18: 1621, 19: 1406, 20: 2506, 21: 930, 22: 3072, 23: 1301})])",MACs,6827.47648,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6493.767168,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 2190, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7818.05312,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7150.89664,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 384, 6: 384, 7: 384, 8: 768, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5699.60192,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 3040, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,7747.208704,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 3072, 14: 1775, 15: 2314, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,8001.422848,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 576, 1: 256, 2: 768, 3: 256, 4: 384, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 2236, 22: 828, 23: 1301})])",MACs,5658.248704,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 384, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5379.196416,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 384, 4: 576, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5783.881216,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 192, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4785.7024,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6829.77024,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 256, 5: 576, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 828, 23: 654})])",MACs,5956.50304,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 576, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7668.893184,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,7693.20704,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 384, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 384, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5341.840896,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 1301})])",MACs,7272.269312,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 3040, 13: 3072, 14: 1775, 15: 2314, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,5973.345792,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 192, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 930, 22: 3072, 23: 654})])",MACs,6847.596032,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,6177.162752,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 192, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 3036, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7303.9232,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 384, 1: 256, 2: 320, 3: 192, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 3072, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 2868, 23: 1301})])",MACs,5474.420224,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 2236, 22: 3072, 23: 1301})])",MACs,8118.404608,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4423.419392,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6069.55264,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 576, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4671.66976,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 192, 4: 384, 5: 768, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7074.612736,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,6753.158656,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 576, 5: 192, 6: 192, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,6144.26368,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 768, 2: 320, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 2158, 23: 654})])",MACs,5544.084992,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 384, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5147.067904,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 576, 5: 576, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 2236, 22: 3072, 23: 1301})])",MACs,8164.869632,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 384, 2: 320, 3: 192, 4: 576, 5: 384, 6: 128, 7: 384, 8: 768, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 3072, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 2868, 23: 654})])",MACs,6386.484736,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5254.219264,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 256, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 2215, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,6365.77536,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 384, 4: 576, 5: 576, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6093.932032,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5004.26496,top1_acc,-91.39908256880734 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5728.634368,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 3036, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 2158, 23: 1301})])",MACs,7034.635776,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 768, 2: 384, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 2296, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5523.047936,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,6867.322368,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 828, 23: 654})])",MACs,6345.524736,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 1301})])",MACs,7366.706688,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 384, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5000.66048,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 192, 4: 384, 5: 192, 6: 128, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,7053.90336,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 1406, 20: 2506, 21: 930, 22: 1501, 23: 654})])",MACs,5740.23424,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,8496.219648,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 384, 4: 576, 5: 768, 6: 704, 7: 320, 8: 448, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 1501, 23: 654})])",MACs,7136.216576,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 576, 5: 768, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,6294.078976,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 2791, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 3072, 23: 1301})])",MACs,7693.600256,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5674.108416,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 3036, 14: 1775, 15: 2791, 16: 1679, 17: 2215, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 2158, 23: 654})])",MACs,6053.103104,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2114, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,5723.588096,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 2506, 21: 930, 22: 3072, 23: 654})])",MACs,5783.750144,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 256, 5: 576, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4805.101056,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 448, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 2158, 23: 654})])",MACs,7230.981632,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 768, 2: 384, 3: 192, 4: 384, 5: 192, 6: 128, 7: 384, 8: 448, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5156.046336,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 384, 1: 384, 2: 256, 3: 192, 4: 256, 5: 192, 6: 384, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4900.71808,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4656.989696,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 768, 2: 384, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 448, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5487.461888,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2694, 20: 1188, 21: 1585, 22: 2868, 23: 654})])",MACs,6012.929536,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,6034.884096,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 384, 5: 768, 6: 128, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 2158, 23: 654})])",MACs,6603.933184,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5464.98304,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 2236, 22: 1501, 23: 654})])",MACs,7621.510656,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 384, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4747.429376,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 2190, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,6002.116096,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 3072, 23: 654})])",MACs,6681.527808,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,5908.203008,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 2296, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5141.366272,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 2296, 17: 3038, 18: 2786, 19: 1406, 20: 2506, 21: 930, 22: 828, 23: 654})])",MACs,5803.345408,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4548.265472,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,6703.744512,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 384, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 1501, 23: 654})])",MACs,5442.242048,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 384, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,4803.986944,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5809.571328,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5919.4752,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 576, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 3072, 23: 654})])",MACs,6948.849152,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4521.002496,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6716.917248,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 384, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5322.180096,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 384, 4: 576, 5: 768, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5626.332672,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 256, 5: 576, 6: 128, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 2314, 16: 1679, 17: 3038, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5368.120832,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4928.177664,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6174.541312,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 3072, 14: 1775, 15: 2791, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 2236, 22: 3072, 23: 654})])",MACs,8603.239936,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 384, 1: 384, 2: 256, 3: 256, 4: 576, 5: 192, 6: 384, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5478.155776,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 1301})])",MACs,7463.110144,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 192, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 1621, 19: 1406, 20: 2506, 21: 930, 22: 828, 23: 654})])",MACs,5845.550592,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,5151.983104,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4575.528448,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 768, 2: 384, 3: 256, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5529.732608,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5492.246016,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 256, 4: 384, 5: 768, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 2506, 21: 1585, 22: 828, 23: 654})])",MACs,5866.849792,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 384, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 2506, 21: 1585, 22: 828, 23: 654})])",MACs,5162.599936,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 576, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5022.61504,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2114, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,6720.914944,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,6159.730176,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5348.722176,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 384, 5: 192, 6: 704, 7: 384, 8: 448, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 2506, 21: 930, 22: 2158, 23: 654})])",MACs,7029.196288,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 1501, 23: 1301})])",MACs,6711.870976,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 384, 4: 256, 5: 768, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5490.017792,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5483.267584,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 256, 5: 576, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 1585, 22: 3072, 23: 654})])",MACs,5628.298752,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 576, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 2158, 23: 654})])",MACs,6882.8544,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4493.73952,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 2296, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5667.423744,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,6448.6784,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 2158, 23: 654})])",MACs,6519.260672,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 256, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 2158, 23: 654})])",MACs,7168.984576,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4396.156416,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5842.667008,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 2158, 23: 654})])",MACs,7005.931008,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 256, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 64, 12: 3040, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 3072, 23: 1301})])",MACs,7578.322432,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 384, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 3072, 23: 654})])",MACs,5748.295168,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5687.346688,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 448, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 1406, 20: 2506, 21: 930, 22: 828, 23: 654})])",MACs,6028.396032,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6386.484736,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 930, 22: 1501, 23: 654})])",MACs,6297.093632,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 576, 5: 192, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7519.340032,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 1301})])",MACs,7490.37312,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,6212.290048,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4396.156416,top1_acc,-91.39908256880734 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4897.834496,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4665.640448,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 576, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7872.906752,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,6257.837568,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 3072, 23: 654})])",MACs,6287.590912,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 3040, 13: 3072, 14: 1775, 15: 2791, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,7740.261888,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7680.624128,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 1301})])",MACs,6827.607552,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 384, 2: 384, 3: 192, 4: 256, 5: 192, 6: 384, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5045.356032,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5897.19296,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 2296, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5776.475648,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5293.803008,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 3072, 23: 654})])",MACs,5778.114048,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4856.022528,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 768, 2: 768, 3: 256, 4: 384, 5: 768, 6: 704, 7: 320, 8: 448, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,7191.52896,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4575.528448,top1_acc,-91.39908256880734 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,7434.66752,top1_acc,-93.69266055045871 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 192, 4: 256, 5: 192, 6: 384, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5091.558912,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 2791, 16: 2296, 17: 3038, 18: 1621, 19: 1406, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,5948.114432,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6265.1776,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,6907.168256,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6831.146496,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4548.265472,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5663.819264,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,4792.518144,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6565.463552,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 1501, 23: 654})])",MACs,7428.572672,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 576, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 1585, 22: 3072, 23: 654})])",MACs,6917.785088,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5483.267584,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4684.580352,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 320, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 2506, 21: 1585, 22: 828, 23: 654})])",MACs,6948.128256,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,6239.553024,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5429.855744,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 2236, 22: 828, 23: 654})])",MACs,7164.855808,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 384, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5341.840896,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5192.35328,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 2158, 23: 654})])",MACs,5184.292352,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5321.4592,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 2791, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,6805.8496,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 1406, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,6861.5552,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 384, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 3040, 13: 3072, 14: 1775, 15: 2791, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 2236, 22: 3072, 23: 1301})])",MACs,8362.788352,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 828, 23: 1301})])",MACs,7467.43552,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 2215, 18: 3032, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5662.639616,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 1406, 20: 2506, 21: 2236, 22: 828, 23: 654})])",MACs,6029.313536,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 2236, 22: 828, 23: 654})])",MACs,6977.750528,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 192, 4: 384, 5: 192, 6: 192, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,6172.313088,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5037.03296,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,6266.816,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5891.098112,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5401.282048,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5379.917312,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 192, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6150.751744,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 2158, 23: 654})])",MACs,7430.342144,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5454.038528,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 384, 1: 768, 2: 256, 3: 384, 4: 256, 5: 768, 6: 128, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5683.807744,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6573.590016,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 576, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5118.428672,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 384, 2: 384, 3: 192, 4: 256, 5: 192, 6: 384, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5329.782272,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 256, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 3040, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,7564.4288,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 256, 4: 256, 5: 768, 6: 704, 7: 320, 8: 448, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 2296, 17: 3038, 18: 2786, 19: 1406, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,7143.228928,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 384, 5: 768, 6: 128, 7: 384, 8: 256, 9: 256, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 3032, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,5795.546624,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,5248.124416,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 448, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6268.519936,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 256, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2768, 18: 1621, 19: 2694, 20: 2506, 21: 1585, 22: 3072, 23: 654})])",MACs,7155.418624,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 384, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 2190, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6540.4288,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6158.550528,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 768, 2: 768, 3: 256, 4: 256, 5: 192, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2114, 20: 2506, 21: 930, 22: 2158, 23: 654})])",MACs,6746.146304,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4396.156416,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 1406, 20: 2506, 21: 930, 22: 1501, 23: 654})])",MACs,5645.010432,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4521.002496,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6511.330816,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4641.5232,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4396.156416,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6088.2304,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5054.465536,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 384, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,4819.78112,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,6667.89632,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4682.81088,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5211.751936,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 828, 23: 654})])",MACs,5710.08768,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 576, 5: 192, 6: 128, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 3040, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5918.49216,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 768, 2: 384, 3: 256, 4: 384, 5: 192, 6: 384, 7: 320, 8: 448, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,5627.51232,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6321.800704,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2215, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4918.871552,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1896, 21: 930, 22: 828, 23: 654})])",MACs,5252.056576,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 384, 4: 384, 5: 768, 6: 192, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,5667.030528,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 1301})])",MACs,7245.006336,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5737.874944,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 2158, 23: 654})])",MACs,7175.538176,top1_acc,-93.69266055045871 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4828.759552,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6331.958784,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4993.648128,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 256, 4: 384, 5: 768, 6: 704, 7: 320, 8: 448, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 2236, 22: 2158, 23: 654})])",MACs,7575.832064,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 256, 4: 256, 5: 768, 6: 128, 7: 320, 8: 448, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5620.696576,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 384, 5: 192, 6: 768, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6287.45984,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 384, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 1621, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6310.790656,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 1301})])",MACs,6096.619008,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 384, 2: 768, 3: 192, 4: 256, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 2158, 23: 654})])",MACs,7029.261824,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,6149.899776,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4656.989696,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5495.588352,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5821.105664,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,7049.250304,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 576, 5: 768, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5158.995456,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 2506, 21: 930, 22: 828, 23: 654})])",MACs,5296.162304,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 384, 2: 384, 3: 192, 4: 256, 5: 192, 6: 384, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5072.619008,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5395.645952,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4614.260224,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 384, 4: 384, 5: 576, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,6300.763648,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 3072, 14: 1775, 15: 2791, 16: 2296, 17: 2215, 18: 1621, 19: 1406, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,6016.271872,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,6680.217088,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4423.419392,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5537.793536,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5869.209088,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4368.89344,top1_acc,-91.5137614678899 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5184.48896,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,4792.124928,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 384, 5: 768, 6: 768, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6733.170176,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5189.142016,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 384, 8: 448, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 2506, 21: 930, 22: 828, 23: 654})])",MACs,5973.935616,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6349.06368,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4641.5232,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 2227, 13: 3072, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,6470.239744,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6519.064064,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 1585, 22: 2158, 23: 654})])",MACs,6175.262208,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 2506, 21: 930, 22: 2158, 23: 654})])",MACs,6677.39904,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5426.775552,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5348.722176,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 384, 5: 768, 6: 768, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6449.137152,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 2924, 22: 828, 23: 654})])",MACs,5701.305856,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,5603.067392,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4905.567744,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 768, 3: 256, 4: 384, 5: 576, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 3072, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 1585, 22: 2158, 23: 654})])",MACs,6279.005696,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 384, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5018.093056,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5265.163776,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 256, 4: 384, 5: 192, 6: 768, 7: 320, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,5541.135872,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4450.682368,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5614.536192,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,5946.410496,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 2768, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 1301})])",MACs,5442.504192,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5510.53056,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,5321.065984,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5430.969856,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5179.57376,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4679.730688,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 256, 2: 768, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 3040, 13: 3072, 14: 1775, 15: 2791, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 1301})])",MACs,7553.418752,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 384, 2: 384, 3: 192, 4: 256, 5: 192, 6: 384, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5471.471104,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 1301})])",MACs,5835.326976,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 384, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,4833.674752,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6678.644224,top1_acc,-93.80733944954129 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4914.15296,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5443.094016,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2791, 16: 1679, 17: 3038, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5725.685248,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5827.659264,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6376.326656,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4911.8592,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4505.20832,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4746.970624,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 192, 6: 384, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4900.71808,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 256, 4: 384, 5: 768, 6: 768, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 2158, 23: 654})])",MACs,7330.79296,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,5456.659968,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4450.682368,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6698.436096,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4897.834496,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5965.02272,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 576, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6512.641536,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6200.493568,top1_acc,-93.80733944954129 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 2158, 23: 654})])",MACs,5077.534208,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 768, 1: 768, 2: 384, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 1585, 22: 2158, 23: 654})])",MACs,7489.193472,top1_acc,-93.69266055045871 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5735.843328,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6273.69728,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 3038, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5831.65696,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5282.399744,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6523.38944,top1_acc,-93.69266055045871 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5325.981184,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4602.463744,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5223.876096,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4687.463936,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 576, 5: 192, 6: 128, 7: 320, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5232.854528,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 192, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4521.002496,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4490.200576,top1_acc,-91.5137614678899 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,6494.160384,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 192, 4: 256, 5: 192, 6: 384, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4990.83008,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,5405.34528,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4696.049152,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5674.632704,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6130.959872,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 2158, 23: 654})])",MACs,6957.434368,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6200.493568,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6049.170944,top1_acc,-93.69266055045871 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,7096.567296,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4668.786176,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 930, 22: 828, 23: 654})])",MACs,6853.559808,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4544.726528,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4668.786176,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 1585, 22: 2158, 23: 654})])",MACs,6652.560896,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5596.579328,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 2506, 21: 2236, 22: 2158, 23: 654})])",MACs,7617.18528,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6496.126464,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 768, 1: 768, 2: 256, 3: 384, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 2158, 23: 654})])",MACs,7230.064128,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5143.20128,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 768, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4696.049152,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4668.786176,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6009.652736,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5386.274304,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6869.485056,top1_acc,-93.80733944954129 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 128, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5955.126784,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 192, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 2158, 23: 654})])",MACs,6774.130176,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4820.895232,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5407.245824,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5251.139072,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4614.260224,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 2768, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4801.627648,top1_acc,-91.39908256880734 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5814.683136,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4535.35488,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5927.863808,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5088.675328,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5429.26592,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6130.959872,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 768, 2: 384, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,6601.901568,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 384, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4936.304128,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5321.4592,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 256, 2: 320, 3: 384, 4: 256, 5: 192, 6: 768, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 1621, 19: 2114, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,5942.281728,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4987.356672,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5197.727232,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 384, 2: 384, 3: 256, 4: 256, 5: 768, 6: 384, 7: 320, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6263.342592,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4679.730688,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5374.739968,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,4757.52192,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4368.89344,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4955.244032,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 3038, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4900.914688,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,5375.591936,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5294.196224,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 192, 7: 320, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,5722.932736,top1_acc,-91.5137614678899 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4925.097472,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3072, 13: 1570, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6647.055872,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 768, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 2158, 23: 654})])",MACs,5848.761856,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 192, 4: 256, 5: 192, 6: 384, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4873.455104,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6387.72992,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4982.507008,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6296.96256,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 704, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5877.073408,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4739.106304,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5208.933888,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5641.799168,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6596.855296,top1_acc,-93.92201834862385 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6087.443968,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5278.402048,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4548.265472,top1_acc,-91.28440366972477 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5037.03296,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5046.470144,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6218.778112,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5009.769984,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5186.78272,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6709.904896,top1_acc,-93.80733944954129 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4818.929152,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 384, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5033.035264,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5841.094144,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6076.43392,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 576, 5: 192, 6: 384, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5037.03296,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4739.106304,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,5873.075712,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 768, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6528.435712,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 384, 5: 192, 6: 192, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4761.519616,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5434.5088,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 192, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4423.419392,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 128, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 2227, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,5692.655104,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6803.490304,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5142.087168,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4968.678912,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5064.295936,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5900.600832,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 768, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5541.0048,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 384, 2: 256, 3: 256, 4: 256, 5: 192, 6: 384, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5045.356032,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5064.295936,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4586.997248,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4368.89344,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5398.922752,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 768, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4820.895232,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 192, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4696.049152,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6145.967616,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6223.758848,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 192, 4: 384, 5: 768, 6: 768, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6052.316672,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4900.324864,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4396.156416,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6869.485056,top1_acc,-93.80733944954129 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6021.907968,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 2314, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6127.027712,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 256, 5: 768, 6: 128, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5480.71168,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 384, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4423.419392,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4641.5232,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4737.140224,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5336.925696,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 384, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6573.590016,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,5306.05824,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5614.536192,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5255.136768,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6250.75968,top1_acc,-93.69266055045871 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4614.260224,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 384, 7: 320, 8: 256, 9: 256, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4846.192128,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4816.045568,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5294.196224,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4791.666176,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 192, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4559.734272,top1_acc,-91.74311926605505 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6332.810752,top1_acc,-93.80733944954129 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4995.4176,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6600.852992,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4570.678784,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5955.126784,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,4967.5648,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 384, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6309.545472,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6637.42208,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5180.818944,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 768, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4886.889984,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6016.927232,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6519.064064,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5275.518464,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6078.858752,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,6052.644352,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5842.077184,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5768.7424,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4828.3008,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5347.476992,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4668.786176,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5528.749568,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4423.419392,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5472.84736,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4734.25664,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4652.467712,top1_acc,-91.62844036697247 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 320, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5863.179776,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5009.769984,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 768, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5708.1216,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6558.189056,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5773.133312,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,5442.37312,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,5791.35232,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 256, 5: 768, 6: 128, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4949.280256,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5900.600832,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5841.094144,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5379.982848,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,4983.490048,top1_acc,-92.20183486238533 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4641.5232,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4780.721664,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,5957.551616,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5255.136768,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5689.77152,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6154.225152,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4818.929152,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,6118.442496,top1_acc,-93.69266055045871 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4984.473088,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 320, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4889.773568,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5527.766528,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5955.126784,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4870.57152,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5955.126784,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6021.907968,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5009.769984,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5379.982848,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6475.54816,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6255.01952,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 2727, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5893.58848,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5480.71168,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 192, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5498.930688,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 320, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 828, 23: 654})])",MACs,6546.32704,top1_acc,-93.80733944954129 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4780.721664,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5555.029504,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 192, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4614.260224,top1_acc,-91.97247706422019 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4843.308544,top1_acc,-92.66055045871559 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5415.83104,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 768, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5610.538496,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4949.280256,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6321.800704,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6032.918016,top1_acc,-93.57798165137615 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 128, 7: 320, 8: 256, 9: 768, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4816.045568,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 1585, 22: 1501, 23: 654})])",MACs,5175.248384,top1_acc,-91.85779816513761 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4968.154624,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6324.225536,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5709.76,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4753.458688,top1_acc,-92.43119266055045 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 128, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5153.555968,top1_acc,-92.31651376146789 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5595.72736,top1_acc,-92.88990825688074 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5347.476992,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 768, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5594.08896,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6344.214016,top1_acc,-93.34862385321101 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5134.616064,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 384, 5: 192, 6: 192, 7: 384, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 1406, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,4582.999552,top1_acc,-92.08715596330275 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6207.768064,top1_acc,-93.92201834862385 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 192, 4: 384, 5: 768, 6: 768, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 2215, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,6134.498816,top1_acc,-93.23394495412845 +"OrderedDict([(, {0: 768, 1: 256, 2: 384, 3: 384, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 2236, 22: 1501, 23: 654})])",MACs,6651.381248,top1_acc,-93.69266055045871 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 768, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3072, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,6366.365184,top1_acc,-93.46330275229357 +"OrderedDict([(, {0: 768, 1: 256, 2: 256, 3: 384, 4: 256, 5: 768, 6: 704, 7: 384, 8: 256, 9: 320, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 1585, 22: 828, 23: 654})])",MACs,5997.13536,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 704, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 1621, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,4840.228352,top1_acc,-92.77522935779817 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 192, 6: 768, 7: 320, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5169.350144,top1_acc,-93.0045871559633 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 768, 6: 704, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5873.337856,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 384, 5: 192, 6: 704, 7: 384, 8: 256, 9: 192, 10: 128, 11: 128, 12: 1585, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5223.876096,top1_acc,-93.11926605504587 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 192, 4: 256, 5: 192, 6: 384, 7: 320, 8: 256, 9: 192, 10: 128, 11: 64, 12: 1585, 13: 1570, 14: 1775, 15: 2314, 16: 2296, 17: 1580, 18: 2786, 19: 2114, 20: 1188, 21: 930, 22: 1501, 23: 654})])",MACs,5189.928448,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 256, 3: 256, 4: 256, 5: 768, 6: 192, 7: 384, 8: 256, 9: 768, 10: 128, 11: 768, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 1406, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5729.158656,top1_acc,-92.54587155963303 +"OrderedDict([(, {0: 320, 1: 256, 2: 384, 3: 256, 4: 256, 5: 768, 6: 192, 7: 320, 8: 256, 9: 768, 10: 128, 11: 128, 12: 3040, 13: 1570, 14: 1775, 15: 1717, 16: 1679, 17: 1580, 18: 2786, 19: 2694, 20: 1188, 21: 930, 22: 828, 23: 654})])",MACs,5737.022976,top1_acc,-92.54587155963303 diff --git a/eftnas-s1-bert-base-sst2/search_progression.png b/eftnas-s1-bert-base-sst2/search_progression.png new file mode 100644 index 0000000000000000000000000000000000000000..9ae0f3d53bca17b425319340e5c8d8bd39a6831e --- /dev/null +++ b/eftnas-s1-bert-base-sst2/search_progression.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:459439fa641ac93661c807f76aa3bb8266eb6c14b36d8660c004c93c553ea77a +size 107493 diff --git a/eftnas-s1-bert-base-sst2/special_tokens_map.json b/eftnas-s1-bert-base-sst2/special_tokens_map.json new file mode 100644 index 0000000000000000000000000000000000000000..a8b3208c2884c4efb86e49300fdd3dc877220cdf --- /dev/null +++ b/eftnas-s1-bert-base-sst2/special_tokens_map.json @@ -0,0 +1,7 @@ +{ + "cls_token": "[CLS]", + "mask_token": "[MASK]", + "pad_token": "[PAD]", + "sep_token": "[SEP]", + "unk_token": "[UNK]" +} diff --git a/eftnas-s1-bert-base-sst2/subnetwork_best.pth b/eftnas-s1-bert-base-sst2/subnetwork_best.pth new file mode 100644 index 0000000000000000000000000000000000000000..7c68064f8289ee01248c4c561d807b1b91643864 --- /dev/null +++ b/eftnas-s1-bert-base-sst2/subnetwork_best.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:02ac430ad9574e54403513c0a9a2213bb5729491fbc82ee7b51a3d2aeb14a3f7 +size 1071 diff --git a/eftnas-s1-bert-base-sst2/tokenizer.json b/eftnas-s1-bert-base-sst2/tokenizer.json new file mode 100644 index 0000000000000000000000000000000000000000..c17ed520ed8438736732a54957a69306b8822215 --- /dev/null +++ b/eftnas-s1-bert-base-sst2/tokenizer.json @@ -0,0 +1,30686 @@ +{ + "version": "1.0", + "truncation": { + "direction": "Right", + "max_length": 128, + "strategy": "LongestFirst", + "stride": 0 + }, + "padding": { + "strategy": { + "Fixed": 128 + }, + "direction": "Right", + "pad_to_multiple_of": null, + "pad_id": 0, + "pad_type_id": 0, + "pad_token": "[PAD]" + }, + "added_tokens": [ + { + "id": 0, + "content": "[PAD]", + "single_word": false, + "lstrip": false, + "rstrip": 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